The State AI Readiness Divide: Which States Are Actually Helping Their People Learn and Use AI?

An Underwood Partners Collaboration Evangelist White Paper

By Craig Underwood in collaboration with ChatGPT

Artificial intelligence is often discussed as if it were a single national wave: ChatGPT appears, companies scramble, schools debate cheating, workers worry, and everyone tries to keep up.

But that is not what is happening.

AI adoption is not spreading evenly across the United States. It is being shaped by public choices — by whether states are giving government employees secure AI tools, helping educators understand how to teach with AI, investing in public higher education, and making AI training available to residents.

In other words, the next AI divide may not be just between people who use AI and people who do not.

It may be between states that help their people learn AI — and states that leave them to figure it out alone.

That was the hypothesis behind this research. I wanted to know whether states differ meaningfully in their investment in and support for AI, and whether Massachusetts — my home commonwealth — is at or near the top.

The short answer: yes.

The longer answer is more interesting.

State AI readiness evaluation criteria.

For this analysis, we ranked all 50 states plus Washington, D.C. on a 100-point AI readiness index. The index was not designed to measure private-sector AI activity alone. Silicon Valley venture capital, university research labs, and AI startups matter, but they were not the core question.

 

The question was civic and public:

Which states are helping their residents, students, educators, public employees, and institutions actually learn and use AI?

The ranking used four categories:

 

We gave the most credit for concrete implementation: secure AI tools, training programs, statewide public AI portals, public higher-ed credentials, K–12 AI guidance, workforce-development programs, and published use cases.

We gave much less credit for task forces, commissions, executive orders, or legislation unless they were tied to real funding, training, tool access, implementation, or public-facing programs.

We also distinguished among three policy postures:

Policy posture Meaning
Responsible AI enablement The state encourages AI adoption while providing guardrails, training, privacy protections, and human oversight.
Neutral risk management The state is studying or regulating AI but has limited public evidence of broad adoption support.
Restrictive or chilling policy The state’s actions appear more likely to discourage useful AI adoption than to enable it.

That distinction matters. AI governance is not automatically anti-AI. In fact, the most impressive states are not choosing between innovation and responsibility. They are trying to do both.

The top 10 states and jurisdictions

The highest-ranked states are not merely “interested” in AI. They are putting AI into public systems.

Rank State / Jurisdiction Score Tier
1 Massachusetts 91 AI Readiness Leader
2 Utah 88 AI Readiness Leader
3 New York 86 AI Readiness Leader
4 New Jersey 84 AI Readiness Leader
5 California 82 AI Readiness Leader
6 District of Columbia 80 AI Readiness Leader
7 Maryland 78 AI Readiness Leader
8 Colorado 77 AI Readiness Leader
9 Ohio 76 AI Readiness Leader
10 Georgia 75 AI Readiness Leader

Massachusetts ranks first because it appears to have the most complete public AI readiness strategy. The Commonwealth has launched a secure enterprise AI assistant for executive-branch employees, partnered with Google and the Massachusetts AI Hub to offer no-cost AI training to residents, and developed K–12 AI guidance and educator resources through the Department of Elementary and Secondary Education.[1]

Utah ranks second and may be the national leader in education-focused AI readiness. Utah has announced a statewide AI Workforce Credential for public college and university graduates and a statewide partnership to bring Gemini for Education to K–12 schools.[2]

New York ranks third because of the scale of its state workforce rollout. The state has expanded AI training and a secure AI tool, AI Pro, to more than 100,000 state employees, while also investing in Empire AI, a major public-interest AI research consortium.[3]

New Jersey ranks fourth because it has one of the clearest examples of practical public-sector AI implementation. Its NJ AI Assistant has been used by about 20,000 state employees, with more than 300,000 sessions and 1 million prompts as of February 2026.[4]

California ranks fifth because it combines a massive AI economy with state and local government training, K–12 guidance, higher-ed activity, and workforce-disruption planning. But California’s posture is more complex than the top four because it is also heavily focused on regulation and labor-market disruption.

The bottom 10 states

The bottom states should not be described as “anti-AI.” That would overstate the evidence. In many cases, they are better described as states with limited public evidence of broad statewide AI enablement.

Rank State Score Tier
42 West Virginia 42 Limited / Early
43 Wyoming 41 Limited / Early
44 New Hampshire 40 Limited / Early
45 Alaska 39 Limited / Early
46 North Dakota 38 Limited / Early
47 Louisiana 37 Limited / Early
48 Nebraska 36 Limited Public Evidence
49 Kansas 34 Limited Public Evidence
50 South Dakota 32 Limited Public Evidence
51 Arkansas 30 Limited Public Evidence

This is an important methodological point. A low ranking does not prove that nothing is happening. It means I found less recent public evidence that the state is combining AI tool access, training, education strategy, workforce development, and responsible-use infrastructure into a coherent statewide approach.

That distinction matters because the AI landscape is changing fast. A state could move from the bottom tier to the middle quickly if it launched a statewide AI training portal, gave public employees secure AI access, published K–12 guidance, and used community colleges to scale workforce credentials.

The map tells the story.

The lead map shows a striking pattern: AI readiness is not evenly distributed.

Some states are already treating AI as a public-capacity project. They help people learn, practice, and use AI responsibly. Others are still closer to the study-and-watch stage.

National research supports this uneven picture. Code for America’s 2026 Government AI Landscape Assessment concluded that states are at different stages of AI adoption, ranging from readiness and piloting to implementation and impact.[5] The National Conference of State Legislatures has also tracked a surge in state AI activity, reporting that all 50 states, Puerto Rico, the Virgin Islands, and D.C. introduced AI-related legislation in 2025, while 38 states adopted or enacted around 100 measures.[6]

But legislation alone is not the same as readiness.

The leading states are doing more than passing bills. They are creating tools, training people, building public infrastructure, and giving educators and public employees permission to experiment within guardrails.

What the K–12 comparison adds

We also compared each state’s AI readiness rank with its K–12 education rank, using WalletHub’s 2026 public school system ranking as the K–12 comparison source.[7]

The result is one of the most interesting parts of the analysis.

Good schools help, but they do not automatically produce AI readiness.

Some states have both strong K–12 systems and strong AI readiness. Massachusetts is the clearest example: it ranked first in both our AI readiness index and the WalletHub K–12 ranking. New Jersey, New York, Maryland, Virginia, Connecticut, Rhode Island, Wisconsin, Pennsylvania, and Utah also appear in the high-education / high-AI zone.

These states are in the strongest strategic position. They have educational capacity and are beginning to convert that capacity into AI readiness.

But the scatterplot also reveals two other important patterns.

First, some states appear to be using AI as a leapfrog strategy. California, Georgia, Ohio, North Carolina, Colorado, Oregon, Arizona, Texas, and New Mexico do not rank at the very top on K–12 education, but they show stronger public evidence of AI support and investment than their education rankings alone would predict.

That may be strategically wise. AI training can scale faster than traditional education reform. Community colleges, public universities, workforce boards, libraries, and state agencies can help adults, small businesses, and public employees gain practical AI skills quickly.

Second, some states with relatively strong K–12 systems appear to be underleveraging that advantage. New Hampshire, Nebraska, North Dakota, Montana, Wyoming, Indiana, and Vermont all have educational strengths, but weaker public evidence of broad AI readiness.

That is the danger for high-education states: yesterday’s education advantage does not automatically become tomorrow’s AI advantage.

Four strategic positions for states

The AI readiness vs. K–12 education scatterplot creates four useful strategic categories.

  1. High K–12 / High AI: Compounding advantage

These states have the strongest starting position. They have relatively strong education systems and are also investing in public AI readiness.

Strategic imperative: move from AI readiness to AI advantage.

These states should publish public AI use-case libraries, scale AI literacy expectations, train public employees, support educator professional development, fund public higher-ed credentials, and measure productivity and learning gains.

The risk is complacency. Strong schools and strong universities are not enough. AI advantage requires structured implementation.

  1. Lower K–12 / High AI: Leapfrog opportunity

These states may be using AI as a way to accelerate workforce development and public-sector modernization.

Strategic imperative: use AI as a human-capital accelerator.

These states should focus on community colleges, adult learners, small-business training, teacher productivity, student supports, and accessible AI credentials.

The opportunity is speed. A state does not need to wait 20 years to improve every K–12 metric before helping people build useful AI skills.

The risk is inequity. If AI programs primarily benefit already-advantaged residents, AI may widen internal gaps.

  1. High K–12 / Lower AI: Underleveraged education advantage

These states may have strong educational foundations but less visible statewide AI implementation.

Strategic imperative: convert education strength into AI readiness.

The playbook is straightforward: issue practical K–12 AI guidance, train educators, give public employees secure tools, create public AI learning portals, and use public universities and community colleges as AI training engines.

The risk is losing ground to states with weaker traditional education systems but stronger AI implementation strategies.

  1. Lower K–12 / Lower AI: Double catch-up challenge

These states face the hardest strategic position.

Strategic imperative: start with practical, low-cost, high-leverage AI readiness moves.

They should create a statewide AI learning portal, train state employees in responsible AI use, publish K–12 AI guidance, partner with community colleges on short credentials, and build a public use-case library.

The risk is that AI becomes another driver of regional inequality.

The deeper point: AI readiness is public infrastructure.

The best states are not treating AI as a gadget. They are treating AI readiness as a form of civic infrastructure.

That means giving people:

  • access,
  • training,
  • permission,
  • examples,
  • guardrails, and
  • time to practice.

A state employee who has access to a secure AI assistant can learn by doing. A teacher with practical guidance can move beyond fear and confusion. A community college student with an AI credential can enter the labor market with greater confidence. A small business owner with free training can experiment without hiring a consultant. A resident with access to a public AI learning portal can begin without needing to be part of the technology sector.

That is the difference between AI as a private advantage and AI as a public capability.

Why Massachusetts matters

Massachusetts is a particularly useful case because it already had advantages: great universities, strong K–12 performance, a dense innovation economy, world-class hospitals, and a highly educated workforce.

But those advantages alone are not what made Massachusetts rank first.

What matters is that Massachusetts appears to be converting its existing advantages into public AI readiness.

The Commonwealth is giving executive-branch employees secure AI access. It is offering residents no-cost AI training. It is building a public AI Hub. It is supporting K–12 educators with guidance and resources.

That combination is the key.

Massachusetts is not simply an AI-rich state. It is investing to become an AI-ready Commonwealth.

The policy lesson

The policy lesson is not that every state should copy Massachusetts exactly. States differ in size, economy, demographics, politics, education systems, and fiscal capacity.

But every state can do five things:

  1. Give public employees safe AI access and training.
  2. Publish practical K–12 AI guidance.
  3. Use public higher education and community colleges to scale AI credentials.
  4. Create a public AI learning portal for residents and small businesses.
  5. Measure outcomes and publish use cases.

The first states to do these things well will have an advantage.

Not just a technology advantage. A civic advantage.

Final thought

AI adoption is often framed as an individual responsibility: learn the tools, keep up, do not fall behind.

But this research suggests that public leadership matters enormously.

Some states are making AI learning easier, safer, and more accessible. Others are leaving residents, teachers, workers, and public employees to navigate the AI era largely on their own.

That is the state AI readiness divide.

And it may become one of the most important competitiveness and equity issues of the next decade.

 

 

Endnotes

[1] Massachusetts state AI assistant materials; Massachusetts-Google free AI training announcement; Massachusetts AI Hub; Massachusetts Department of Elementary and Secondary Education AI resources.

[2] Utah System of Higher Education announcement of statewide AI Workforce Credential; Google announcement of Gemini for Education partnership with Utah K–12 schools.

[3] New York Governor’s Office announcement of AI Pro and AI training expansion to state workforce; Empire AI materials.

[4] New Jersey Innovation Authority, NJ AI Assistant project page and 2026 update.

[5] Code for America, 2026 Government AI Landscape Assessment.

[6] National Conference of State Legislatures, 2025 AI legislation summary and AI legislation database.

[7] WalletHub, 2026 public school system ranking.

Source links for the article endnotes

Massachusetts has an official enterprise AI assistant page, and Google announced no-cost AI training for Massachusetts residents through the Massachusetts AI Hub and Grow with Google. (Massachusetts Government)

Utah’s higher-ed system announced a no-cost AI Workforce Credential for more than 50,000 public college and university graduates, and Google announced Gemini for Education access for every Utah K–12 school beginning in the 2026–2027 school year. (Utah System of Higher Education)

New York announced expansion of AI education and AI Pro to more than 100,000 state employees, while New Jersey reported about 20,000 state employees using its AI Assistant, with more than 300,000 sessions and 1 million prompts as of February 2026. (Governor Kathy Hochul)

Code for America’s 2026 Government AI Landscape Assessment evaluates state AI adoption across readiness, piloting, implementation, and impact, while NCSL tracks AI legislation across states and reported that 38 states adopted or enacted around 100 AI-related measures in 2025. (Code for America)

For education context, Playlab reports that 36 states plus Puerto Rico had official K–12 AI guidance or policy frameworks as of May 2026, and FutureEd tracked 71 AI-in-education bills across 27 states during the 2026 legislative session. (learn.playlab.ai

Summary / Net

Most senior executives do not have a productivity problem. They have an overload, attention, energy, relationship, and prioritization problem. The CHU Management System — CHUMS — is my personal operating system for getting shit done without letting the loudest, most urgent, or most emotionally reactive issue take over my life.

CHUMS is not a software platform, productivity app, or universal template. It is a weekly paper-and-Google-Sheet discipline I use to manage work, family, relationships, health, values, commitments, follow-up, and focus. The specific system is mine. The larger point is universal: every serious leader needs a system.

Why I Built CHUMS

I originally developed what became the CHU Management System during the seven years I founded and led The Loyalty Group, that created, launched and grew the AIR MILES Canada shopping reward program and database/ internet marketing business. Like many entrepreneurs and CEOs, I had too many priorities, too many people depending on me, too many ideas, too many meetings, too many relationships to maintain, and too many chances for something important to fall through the cracks.

Later, in 2016, I began using the system again while working at Year Up, where my work involved roughly 60 internal colleagues, more than 100 external partners, and 12 locations. That was the kind of operating environment where “I’ll remember that” is not a system. It is a fantasy.  It also served me well when I used it in 2020 as Vice Chair of Alan Khazei’s congressional campaign in Massachusetts 4th District.  I have described well-funded competitive political campaigns are like an “internet start-up on speed.”  Personal management systems are a life saver in these environments.

CHUMS is heavily influenced by Stephen Covey’s The 7 Habits of Highly Effective People, David Allen’s Getting Things Done, Jim Loehr and Tony Schwartz’s The Power of Full Engagement, James Clear’s Atomic Habits, conversations with friends and colleagues, and a lot of agile trial and error. It is also influenced by a simple, humbling reality I have learned repeatedly in my life: when I use my system, things get done. When I don’t, things fall off my plate, and I drift into a growing pile of “urgent and important” crises.

The “triple-infinity” symbol represents the need for leaders to keep the most important things, actions, tasks, and priorities among your business, your family, and yourself in balance.  This was something emphasized for me personally during the many years I was a member of The Young Presidents Organization, while CEO of The Loyalty Group in Toronto.

The name is slightly tongue-in-cheek: CHUMS stands for CHU Management System. But the point is serious. CHUMS is a personal operating system for self-leadership.

And for senior executives, self-leadership is not optional. If you cannot manage your own attention, energy, values, relationships, commitments, and follow-up, you will eventually transfer your internal disorganization to the organization you lead.

The Big Idea: Senior Executives Need a Personal Operating System

Most executives already have organizational systems. They have strategic plans, dashboards, CRM systems, board packets, financial models, Slack channels, calendars, and performance reviews. But many do not have an equally disciplined personal system for deciding what deserves attention this week, what must happen today, who needs care and connection, what values must be lived, and what can safely wait.

That gap is dangerous.

Without a personal operating system, leaders become reactive. They chase whatever is loudest. They answer the latest email. They respond to the most anxious stakeholder. They spend too much time in Covey’s “urgent and important” quadrant and not enough time on the important-but-not-yet-urgent work that actually builds a life, a team, a strategy, and an institution.

CHUMS is my attempt to solve that problem for myself.

It has 11 parts:

  1. Daily and weekly self-monitoring
  2. Personal must-dos
  3. Weekly to-do list
  4. Strategic priorities and relationships
  5. Calendar blocking
  6. Must do today before I sleep
  7. Rolling discussion lists, house list, and someday/maybe
  8. Live your values
  9. Feedback is a gift
  10. Weekly must-do / three priorities per day
  11. The 86,400 reminder

Here is how each part works.

1. Daily and Weekly Self-Monitoring

What is it?

The first section of CHUMS is a simple weekly tracker. It includes the people and practices I want to stay connected to each week.

For me, the initials and abbreviations on the left-hand side are personal:

J = Jordan, my oldest child.
M = Myles, my youngest child.
LEZ = my wife, Laura.
X = exercise.
S/G = spiritual practice and gratitude.
SSU = my sister Sharon.
CUF = my sister Cecilia.

This section is influenced by Stephen Covey’s “Sharpen the Saw” habit — the idea that we must renew ourselves across the physical, mental, emotional/social, and spiritual dimensions if we want to remain effective.

How do I use it in practice?

Each week, I track whether I have engaged with these people or practices. Did I connect with my kids? Did I connect meaningfully with Laura? Did I exercise? Did I do anything spiritual or gratitude-oriented? Did I check in with my sisters?

This is not meant to be a guilt machine. It is a visibility tool.

A senior executive can easily spend the week serving clients, employees, donors, investors, board members, political allies, or external stakeholders — and then realize that the people and practices that matter most personally received the least intentional attention.

This section makes that visible.

Why include it?

Because what gets tracked gets attention.

Executives are usually very good at tracking business metrics. Revenue. Margin. Retention. Pipeline. Fundraising. Cash runway. Employee engagement. Customer satisfaction. But we often fail to track the personal relationships and renewal practices that keep us grounded and human.

This section reminds me that productivity is not just doing more work. It is living the right life while doing the work.

If I say my family matters, my system should reflect that. If I say health matters, my system should reflect that. If I say spirituality, gratitude, or reflection matters, my system should reflect that.

Otherwise, my stated values and my calendar can be in conflict.

2. Personal Must-Dos

What is it?

This is the short list of the most important personal things I must get done this week.

Not someday. Not eventually. This week.

These are not necessarily the biggest strategic projects. They are the personal commitments that matter enough to deserve explicit weekly attention.

How do I use it in practice?

When I update CHUMS on Sunday night, I ask: what personal things must happen this week for me to feel I have honored my commitments to myself and the people closest to me?

That might include a family follow-up, a personal finance task, a health appointment, a home issue, a difficult conversation, a commitment to Laura, a call with one of my kids, or something I have been avoiding.

The key is that it gets written down in a place I will see all week.

Why include it?

Because personal obligations do not become less important because they are not professional.

Many senior leaders unconsciously privilege work commitments over personal commitments because work commitments come with meetings, deadlines, assistants, board pressure, customers, and money attached. Personal commitments are often quieter. They do not always send calendar invites.

But neglected personal commitments create stress, guilt, friction, and emotional drag. They also erode integrity. If I repeatedly fail to do what I told myself or my family I would do, I become less trustworthy to myself.

This section protects my personal credibility.

3. Weekly To-Do List

What is it?

This is the classic weekly capture list, heavily influenced by David Allen’s Getting Things Done. Allen’s GTD method emphasizes capturing what has your attention, clarifying what it means, organizing it where it belongs, reviewing it regularly, and then engaging with the right work.  Allen advises against keeping a long daily to-do list, as spending time on most nights moving things that did not get done that day to the next can become energy sapping.

In CHUMS, this becomes a weekly written list of work and personal to-dos.

How do I use it in practice?

The list is organized along the right-hand side of the matrix roughly by my most important clients, projects, and people.  CHUDOW – stands for CHU (to) Do Other Work related and CHUDOP – for CHU (to)Do Other Personal.  IC/ AI is a bucket to make sure I build intellectual capital every week and AI to remind me to keep up with the latest developments in artificial intelligence.

The point is to avoid what I call the “four-year-old soccer problem”: every kid chases the same ball.

Organizations do this. Leaders do this. I do this. The urgent issue gets the ball, and suddenly every person, meeting, and ounce of energy is chasing it while other important areas are neglected.

During the week, whenever something comes up, I write it down. I do not rely on memory. I do not assume I will magically remember it after the meeting, after the bike ride, after walking Izzy, or after the next call.

On Sunday night, I update the system in Google Sheets, print it, and carry it with me. Yes, I am trying to eliminate paper from much of my life. But for this, paper still works. I can fold it in half and keep it in my jacket pocket.  A few more folds and it fits in my jeans or cycling jersey pocket.  If something occurs to me while walking the dog, riding my bike, sitting in a meeting, or thinking through a client issue, I can write it down quickly and get it out of my head.

Why include it?

Because the brain is a terrible office.

It is wonderful for creativity, empathy, pattern recognition, judgment, and strategy. It is not wonderful as a storage facility for 73 unrelated commitments.

David Allen’s core insight is that unprocessed commitments create mental residue. The more open loops we carry in our heads, the less fully present we are for the task or person in front of us.

For senior executives, this matters enormously. Your attention is one of the most valuable assets in the organization. If your mind is cluttered with unrecorded obligations, you are spending executive attention on memory management instead of judgment.

Writing things down is not clerical. It is strategic.

4. Most Important Strategic Relationships and Priorities

What is it?

The last two columns force me to list 1-3 relationships in appropriate areas of focus that I must invest in during the week and to whittle down the many to-do items under each to the 1-3 that simply must get done by the end of the week.

How do I use it in practice?

I use the categories to force a broader scan.  The most important relationships and priorities in each category ensure that I narrow down and prioritize those actions and people that are most important for the period.

What needs attention in each major area? What am I ignoring? Which relationships need follow-up? Which strategic priority is quietly drifting? Which area has become too dominant? Which important work is not urgent enough to scream yet?

This section turns my week from a random pile of tasks into a portfolio.

Why include it?

Because executive work is portfolio work.

A CEO or senior leader is rarely responsible for one thing. You are responsible for strategy, people, capital, culture, customers, operations, governance, risk, external relationships, and often your own health and family system at the same time.

If you only manage the loudest category, you will underperform in the quieter ones.

This section creates balance. It forces me to ask: am I paying attention to the whole field, or am I chasing the ball?

5. Calendar Blocking

What is it?

I use this section to block out my calendar, identify major client and board meetings, presentations, and color-code travel dates. It gives me a high-level overview of the most important personal and business events that will require major prep work or personal planning over the next two months.

How do I use it in practice?

At the beginning of the week, I look at the major events and commitments coming up over the next 8 weeks and make sure the requisite pre-work is somewhere on the list above or elsewhere recorded in the system.

Why include it?

This section helps me connect intention to time. It also helps me see overcommitment before it becomes failure. If I have 30 hours of meetings and 50 hours of work I claim must get done, the math is not going to work. Pretending otherwise does not make me ambitious. It makes me irresponsible.

Calendar visibility is a form of honesty.

6. Must Do Today Before I Sleep

What is it?

This is the daily hard-stop section: what must I do today before I go to sleep?  With all due respect to David Allen, this is my daily to do list.  I use an erasable pen to fill it in each morning before starting my day and clear it by the end.

This includes any true Covey Quadrant I items — things that are both urgent and important. But it is not limited to crisis work. It can also include one or two actions that simply cannot be allowed to slip another day.

How do I use it in practice?

Each day, I identify the small number of things that must happen before I sleep. Not 20 things. Not everything. The real must-dos.

This is the section that confronts the day directly.

At the end of a long day, when I am tired, distracted, or tempted to postpone something uncomfortable, this section asks: what did I promise myself would get done today?

Why include it?

Because weeks are won or lost in days.

A beautiful weekly plan can still fail if there is no daily commitment mechanism. This section turns the system into action.

It also helps distinguish between “I was busy” and “I did what mattered.” Senior executives can be busy every minute of the day and still avoid the one conversation, decision, note, workout, apology, or follow-up that actually mattered most.

The phrase “before I sleep” creates useful pressure. It makes the commitment concrete.

7. Rolling Discussion Lists, House Perfect List, and Someday/Maybe

What is it?

The right side of the front page is a set of rolling lists.

I use it to track topics I need to discuss with team members, client contacts, consultants, family members, friends, and collaborators. Instead of immediately calling or texting every time a thought occurs to me, I write it down under the relevant person or project.

This section also includes ideas for articles, my “House Perfect List” — smaller or larger things I need to do around the house or yard — and a “Someday/Maybe” list, borrowed directly from David Allen’s Getting Things Done framework.

How do I use it in practice?

When I think of something I need to discuss with someone, I put it in that person’s box. Then, when we meet or talk, I have a ready-made agenda.

This improves the quality of meetings and reduces the number of interruptive one-off communications. Instead of spraying texts, emails, and half-formed thoughts throughout the week, I batch topics for the right moment.

For the Collaboration Evangelist articles, House Perfect List and Someday/Maybe list, the same principle applies: capture without overcommitting. Not everything belongs on this week’s must-do list. Some things simply need a trusted parking place.

Why include it?

Because not every thought deserves immediate action.

This is especially important for senior leaders. Executives generate a lot of ideas, questions, concerns, and follow-ups. If every thought becomes an immediate interruption for someone else, the leader becomes a chaos machine.

A rolling discussion list creates discipline. It respects other people’s attention. It makes meetings better. It lets me remember without reacting.

The Someday/Maybe list is equally important because it gives ideas a place to live without letting them hijack the week. That is a critical distinction. A good idea is not always a current priority.

8. Live Your Values

What is it?

The left side of the back page is my values reminder. It lists the personal values and commitments I am trying to live.

The emphasis is on trying.

This section is not a declaration that I am fully living these values every day. It is a reminder of who I want to be and how I want to show up.

For me, this includes being the best father I can be, being a good brother, honoring my parents by how I live and work, being respectfully and graciously honest, taking care of myself physically, emotionally, intellectually, and spiritually, using my experience and resources to help others, fighting for justice, being conscious of the impact of my words and actions, not judging others, being the best partner to Laura and best human to Izzy I can be, and passionately promoting what I believe in.

How do I use it in practice?

I keep it on the back page so I see it repeatedly. It is not a framed statement on a wall. It is part of the weekly system.

That matters. Values should not be separated from execution. They should shape execution.

When I review my week, I am not only asking, “What do I need to get done?” I am also asking, “Who am I trying to become while I get it done?”

Why include it?

Because productivity without values can become efficient selfishness.

Many senior executives are extremely productive by conventional measures. They clear inboxes, make decisions, hit numbers, raise capital, close deals, and move fast. But speed and volume are not the same as leadership.

This section forces me to connect action to identity. James Clear’s Atomic Habits argues that lasting behavior change is connected to identity — not merely what goal we want to achieve, but what kind of person we believe we are becoming.

For me, CHUMS is not just a task system. It is an identity system. It reminds me that the goal is not simply to get more shit done. The goal is to get the right shit done in a way that is consistent with the person I am trying to be.

9. Feedback Is a Gift

What is it?

This section captures some of the most important feedback I have received from supervisors, mentors, colleagues, friends, and role models.

It includes short reminders — phrases that mean something specific to me. Some are blunt. Some are cryptic to anyone else. Some are deeply personal. The point is not that the phrases would work for everyone. The point is that they work for me.

How do I use it in practice?

I keep the feedback visible so I cannot conveniently forget it.

Most of us say feedback is a gift. But in practice, we often treat feedback like a gift we would like to return, exchange, reinterpret, or bury in a drawer!

This section makes feedback operational. It turns lessons learned into recurring prompts.

Why include it?

Because leaders repeat avoidable mistakes when feedback is not converted into practice.

Senior executives often receive a lot of feedback, but not always honest feedback. The more senior you become, the more people manage you, flatter you, fear you, or soften the message. So, when you do receive real feedback, you should treat it as valuable data.

But insight fades. A hard lesson learned in March can be forgotten by June. This section keeps the lesson alive.

It also reinforces humility. No matter how experienced I am, I still have things to work on. The system reminds me of that every week.

10. Weekly Must-Do / Three Priorities Per Day

What is it?

The top right side of the back page can be used to list three priorities per day for the week. I have also used it as a blank note-taking space or as a place to list annual goals.

The three-priorities structure is intentionally simple.

How do I use it in practice?

For each day, I write the three things that would make the day successful.

Not 12. Not 27. Three.

This creates focus without pretending the day is clean, predictable, or fully controllable. It gives me a simple way to answer: if everything goes sideways, what are the few things that still matter?

Why include it?

Because constraints create clarity.

Executives are vulnerable to over-listing. We confuse ambition with volume. We put too much on the list and then feel behind before the day starts.

Three priorities force choice. Choice is the essence of strategy.

This section also creates a bridge between weekly planning and daily execution. The weekly system sets the field. The daily priorities define the play.

11. The 86,400 Reminder

What is it?

The final section is a visual reminder: 86,400; Be The Buffalo: Make The Next Best Choice; Proverbs 3:27.

There are 86,400 seconds in a day. Something I learned from my Pastor and Spiritual Entrepreneur friend Ray Hammond. For me, this symbol is a reminder to make the most of each day, confront challenges directly, not dwell endlessly on mistakes, and help others when I am able.

How do I use it in practice?

I do not use this as a productivity hack. I use it as a perspective hack.

Some days go well. Some do not. Some include progress. Some include mistakes. Some include conflict, disappointment, fatigue, or frustration.

The 86,400 reminder helps me reset. It says: this day is finite. Use it. Do not waste it in avoidance, resentment, self-pity, distraction, or fear.

Why include it?

Because time is the only non-renewable leadership resource.

Money can sometimes be raised. Staff can sometimes be hired. Strategy can sometimes be revised. Reputation can sometimes be rebuilt. But the day is spent once.

This does not mean every second should be optimized. That would be exhausting and inhuman. It means the day should be honored.

For a senior executive, the question is not merely “How do I get more done?” The deeper question is: “How do I make choices worthy of the time I have?”

Why the Whole System Works

CHUMS works for me because it integrates five things that are often separated:

  1. Tasks
  2. Time
  3. Energy
  4. Relationships
  5. Values

Most productivity systems over-focus on tasks. They help you capture, sort, and complete work. That is useful, but incomplete.

Senior executive effectiveness is not just task completion. It is sustained judgment, emotional regulation, strategic focus, relationship management, physical and mental energy, and values-based action under pressure.

That is why The Power of Full Engagement is such an important influence on CHUMS. Loehr and Schwartz argue that managing energy, not just time, is central to high performance. A leader with a perfectly organized calendar but depleted physical, emotional, mental, or spiritual energy is not operating at full strength.

CHUMS also works because it is reviewed weekly. A system that is not reviewed becomes clutter. A system that is reviewed becomes trusted.

My Sunday night practice matters. I update the Google Sheet, print the system, and carry it with me. That ritual turns CHUMS from a document into a discipline.

James Clear’s Atomic Habits emphasizes the power of small, repeatable systems. The point is not heroic motivation. The point is designing a structure that makes the desired behavior more likely. CHUMS does that for me. It makes remembering, reviewing, prioritizing, connecting, and acting easier.

It also creates accountability. Even when no one else sees the sheet, I see it. I know what I wrote down. I know what I said mattered. I know what I avoided.

That is powerful.

What Happens When I Do Not Use It

When I do not use CHUMS, my productivity does not collapse all at once. It degrades gradually.

First, I start relying on memory. Then I miss small things. Then I become more reactive. Then important-but-not-urgent work slips. Then relationships become less intentional. Then my day gets captured by other people’s priorities. Then I feel behind. Then I start chasing the crisis of the day. Or, at worst, fall into a state of depression or anxiety paralysis.

Eventually, I end up with exactly what Covey warned about: too much time in the urgent and important quadrant because I failed to invest enough time in preparation, prevention, relationships, renewal, and planning.

When I do not use CHUMS, I also become more likely to confuse motion with progress. I answer emails, create PowerPoint slides, attend meetings, respond to texts, and knock off visible tasks, but I may not be moving the most important priorities forward.

Worst of all, I become more likely to drift away from my values. Not because I stop believing in them, but because I stop seeing them.

That is how it happens for many leaders. They do not abandon their values dramatically. They simply get busy. Then they get reactive. Then they get tired. Then they rationalize. Then the urgent crowds out the important. Then, slowly, the life they are living stops matching the life they say they believe in.

CHUMS is my defense against that drift.

The System Is Mine. The Need Is Universal.

I do not recommend that everyone copy my exact system.

In fact, you should not. CHUMS is highly tailored to my priorities, family, relationships, passions, work, quirks, and flaws. Your system should be tailored to yours.

But I strongly believe every senior executive needs some kind of personal operating system.

It does not have to be paper. It does not have to be a spreadsheet. It does not have to have 11 parts. It does not have to use my language. It does not have to be called anything clever.

But it should help you answer these questions every week:

What matters most?
Who needs my attention?
What must get done?
What can wait?
What am I avoiding?
Where is my energy going?
Am I living my values?
What feedback am I trying to practice?
What must I do today before I sleep?

If your system cannot answer those questions, it is not yet a leadership system. It is just a task list.

A Note for CEOs and Senior Leaders

The higher you rise, the less anyone else can fully manage your attention for you.

An assistant can manage your calendar. A chief of staff can manage your meeting flow. A COO can manage execution rhythms. A board can help set accountability. A coach can ask hard questions.

But no one else can decide, week after week, what kind of leader you are trying to be.

That is your work.

CHUMS is one way I do that work.

It helps me get shit done. But more importantly, it helps me get the right shit done, with the right people in mind, for the right reasons, while trying — imperfectly but seriously — to live the values I claim to hold.

For me, that is the real productivity challenge.

Not just doing more.

Doing what matters.

Building Your Own GSD System

In my CEO coaching and productivity accountability partner (PAP) practice, this is one of the places where I believe I can be most helpful.

Not by handing leaders my system and pretending it will fit their lives.

But by helping them build their own.

A strong executive productivity system should be personal, practical, visible, reviewable, and honest. It should include the work, but not only the work. It should include relationships, energy, renewal, values, feedback, and follow-through. It should be simple enough to use when life gets busy, because that is exactly when the system matters most.

The goal is not to become a productivity robot.

The goal is to become a more intentional leader.

A leader who knows what matters.
A leader who writes it down.
A leader who follows up.
A leader who protects time and energy.
A leader who lives values in practice, not just in speeches.
A leader who gets shit done without losing himself or herself in the process.

That is what CHUMS does for me.

And that is why I still use it.  To paraphrase my son Myles, when I don’t use it, “Shit goes left.”

Here’s a link to the front page google spreadsheet you can edit to start building your own system.

Endnotes

  1. Stephen R. Covey, The 7 Habits of Highly Effective People. CHUMS is especially influenced by Habit 7, “Sharpen the Saw,” and Covey’s distinction between urgent/important work and important-but-not-yet-urgent work.
  2. David Allen, Getting Things Done: The Art of Stress-Free Productivity. CHUMS draws heavily on GTD’s core practices of capturing commitments, clarifying next actions, organizing reminders, reviewing regularly, and maintaining a “Someday/Maybe” list.
  3. Jim Loehr and Tony Schwartz, The Power of Full Engagement: Managing Energy, Not Time, Is the Key to High Performance and Personal Renewal. CHUMS reflects the book’s core argument that sustainable high performance requires managing energy across physical, emotional, mental, and spiritual dimensions.
  4. James Clear, Atomic Habits. CHUMS reflects Clear’s emphasis on systems, small repeatable practices, identity-based behavior change, and designing structures that make desired behaviors more likely.
  5. Gail Matthews, Dominican University of California, research on goal achievement and accountability. The CHUMS presentation cites Matthews’ findings that written goals and weekly accountability increased the percentage of participants who accomplished at least half of their goals.
  6. Craig Underwood, CHU Management System aka CHUMS — Overview, updated June 12, 2026. The structure, 11-part framework, personal examples, and CHUMS descriptions are based on the author’s original presentation.

APPENDIX I – FULL FRONT PAGE (BEFORE FOLDING)

APPENDIX II – FULL BACK PAGE (BEFORE FOLDING)

FOMAT & THE AI PRODUCTIVITY TSUNAMI: WHY AI ISN’T MAKING SOME OF US WORK LESS

By Craig Underwood | collaborationevangelist.com

Net/ Summary:

Artificial intelligence can absolutely make us more productive. But for executives, consultants, entrepreneurs, nonprofit leaders and other ambitious “power users,” increased productivity does not necessarily mean increased leisure. It can mean more ideas to evaluate, more opportunities to pursue, more reports to read, more decisions to make and more AI “staff” to manage.

The leadership challenge is no longer simply learning how to use AI. It is learning how to manage the tsunami of valuable output AI can create — without sacrificing judgment, relationships, focus or our lives outside work.

 

Figure 1. FOMAT — Fear of Missing Agent Time! A humorous beginning to a very real AI-era management problem.

A few months ago, I created a cartoon with AI called FOMAT: Fear of Missing Agent Time! In the cartoon, I awaken in a panic at 2:47 a.m. with a horrifying thought: “OMG, my agent doesn’t have anything to work on!”

OK, the joke is bit absurd. But, for those of us who have learned how to use generative AI well — through iterative prompt engineering, deep research and custom agents — it may also feel disturbingly familiar.

I use ChatGPT, Gemini and, most prominently, Claude Cowork, where I have begun creating my own custom agents. I also use a Plaud device to record, transcribe and summarize meetings. These tools have not made me less engaged in my work. They have increased my energy and engagement and expanded what I believe I can accomplish.

That is exhilarating. It is also a little exhausting.

Because once you discover that an AI agent can research a market, analyze a strategic question, summarize a meeting, develop a donor profile, create a first draft, recommend next steps or identify ten new opportunities before you have finished your coffee, your problem changes.

The question is no longer: “How can I get this work done?” The new question becomes: “How do I possibly keep up with all the valuable work my AI tools can now help me generate?”

Welcome to the AI Productivity Tsunami.

AI IS MAKING MANY OF US MORE PRODUCTIVE. THAT DOESN’T MEAN WE ARE WORKING LESS.

There is increasingly strong evidence that generative AI can improve productivity.

In a controlled experiment involving professional writing tasks, researchers Shakked Noy and Whitney Zhang found that people using ChatGPT completed tasks approximately 40% faster while producing work rated 18% higher in quality.[1]

In another major workplace study, researchers Erik Brynjolfsson, Danielle Li and Lindsey Raymond examined the use of a generative AI assistant by more than 5,000 customer-support agents. Workers using AI resolved approximately 15% more customer issues per hour.[2]

Research conducted with Boston Consulting Group consultants found similar benefits — but also an important warning. Consultants using GPT-4 performed substantially better on tasks within AI’s capabilities, but performed worse when they relied on AI for tasks outside what researchers called its “jagged technological frontier.”[3]

In other words, AI can help us do more, faster and sometimes better. But productivity does not automatically turn into free time. For ambitious people, productivity frequently creates more ambition.

A ten-hour research project that once seemed impractical may now become feasible. A strategic analysis that once required weeks may now be developed in days. A promising idea that previously remained on the “someday” list can suddenly become an active project. And every new project creates more material to read, test, edit, prioritize, validate, and act upon.

Figure 2. Separate studies find meaningful productivity and quality gains from generative AI; they do not measure a single combined effect.

MY OWN EXAMPLE: AN AI AGENT THAT CREATES OPPORTUNITY — AND MORE WORK

I currently help lead fundraising work for Sportsmen’s Tennis & Enrichment Center (STEC), a Boston nonprofit that provides tennis, academic support, health and wellness programs and community opportunities for thousands of young people and their families.

One important assignment is identifying companies and foundations in Greater Boston that may be strong prospective donors or sponsors.

Historically, researching hundreds of companies from the Boston Business Journal’s Book of Lists would require enormous staff time or outsourced to a charitable consulting firm: identifying companies, researching corporate citizenship priorities, determining whether they give directly or through foundations, reviewing charitable contributions and tax filings when available, assessing connections to youth development or Boston communities, and prioritizing outreach.

Today, I have created an AI-enabled workflow to help research and evaluate more than 500 companies and prioritize those most likely to contribute to STEC.

That is a remarkable capability. But it does not mean I now have nothing to do. Quite the opposite.

The agent can help identify prospects, summarize evidence, assemble information and suggest rankings. But a human still must decide whether the information is accurate and current; which opportunities deserve immediate attention; what kind of contribution to request; who might know someone inside the company; and how to convert intelligence into genuine human connection and financial support.

The agent produces information. The leader must still exercise judgment. And when the information is excellent, the temptation is to pursue more of it. That is exactly how the tsunami begins.

Figure 3. The AI Agents’ Productivity Tsunami: when valuable output creates a new prioritization challenge.

RESEARCH NOW SUPPORTS THE TSUNAMI HYPOTHESIS

My cartoon was intended to be humorous. Then I discovered research suggesting it may also be descriptive.

In February 2026, Harvard Business Review published an article by Aruna Ranganathan and Xingqi Maggie Ye of the University of California, Berkeley Haas School of Business. Based on an eight-month ethnographic study at a roughly 200-person U.S. technology company, their in-progress research found that generative AI did not simply free up time. Employees worked faster, broadened the scope of tasks they undertook and extended work into more hours of the day, often without being instructed to do so.[4]

The explanation is both simple and powerful: AI made doing more feel possible, accessible and rewarding. That is precisely the dynamic many AI power users are beginning to experience.

Figure 4. Recent Berkeley Haas research featured in Harvard Business Review closely mirrors the “productivity tsunami” hypothesis.

Microsoft’s 2025 Work Trend Index provides additional context. Its telemetry analysis found that the top 20% of Microsoft 365 users by ping volume received 275 meetings, emails or chats per workday — equivalent to one interruption approximately every two minutes during an eight-hour workday.[5]

Now add AI agents that can continuously create additional analyses, drafts, ideas, recommendations and action items. AI may help close the capacity gap. But unless leaders deliberately redesign how they work, it can also pour more water into an already overflowing ocean.

Figure 5. Microsoft finds severe input overload among its most highly pinged Microsoft 365 users.

To be clear, this is not everyone’s experience. OECD research on small and medium-sized enterprises using generative AI found that 32.7% reported decreased workload, while 11.8% reported increased workload.[6]

My hypothesis is narrower: for highly motivated leaders and professionals who become skilled AI users — especially those creating their own agents — AI may initially increase rather than decrease total work because it expands the frontier of worthwhile opportunity.

Figure 6. An important counterpoint: among SMEs using generative AI, more reported decreased workload than increased workload.

WHAT ABOUT JOB LOSS?

There is another side of this discussion that leaders should not ignore.

Some highly repetitive, process-oriented and entry-level roles are likely to shrink or change substantially as AI becomes better at routine research, summarization, document preparation, basic customer support, scheduling, data entry and administrative work.

The International Labour Organization has found that clerical occupations remain among those most exposed to generative AI transformation.[7] The World Economic Forum’s Future of Jobs Report 2025 similarly identified clerical and administrative positions — including data entry clerks, bank tellers, cashiers and administrative assistants — among the roles employers expect to decline most quickly through 2030.[8]

I believe leaders have the responsibility – some would say the moral imperative – to help employees learn how to use AI responsibly and efficiently and to move toward higher-value work involving judgment, relationships, creativity, influence, and accountability.  This is especially important for nonprofit leaders of work-force development and college access/ success organizations, and those whose missions include preparing those they serve for jobs of the future.  Imagine the different impression a young entry-level job or internship applicant would leave on a prospective employer when answering the question “Do you use AI?” between:

“[My training organization] has provided responsible AI literacy training and prompt engineering to all of its students.”

And

“I don’t use AI much at all.” Or even worse, “We are prohibited from using AI.”

 

THE SOLUTION: SURF. PRIORITIZE. IMPACT.

In the upper-left corner of my Productivity Tsunami cartoon is a simple phrase: Surf. Prioritize. Impact. I think this may be the practical leadership framework we need.

1. SURF: USE AI ENTHUSIASTICALLY — BUT PURPOSEFULLY.

The answer is not to run away from AI. It is too valuable. These tools can help leaders think better, research faster, communicate more clearly and identify opportunities that might otherwise go undiscovered.

But surfing a wave is different from letting it drown you.

Leaders should be explicit about what they want AI to help accomplish. Or, to borrow a phrase from Steven Covey’s The 7 Habits of Highly Effective People, “begin with the end in mind.”  Create agents around important outcomes, not simply because creating another agent is interesting. Keep a running “AI opportunity parking lot” for intriguing ideas that do not deserve immediate action.

2. PRIORITIZE: SCHEDULE MEETING TIME WITH YOUR AI OUTPUT.

If you manage human colleagues, you do not expect them to slide dozens of excellent reports under your door every night and assume you will process them all by morning. The same discipline should apply to AI agents.

Schedule regular “meeting time” to review AI-generated work: a weekly (or daily) review of agent findings and recommendations; a clear decision rubric for what moves forward, what gets delegated, deferred or discarded; limits on active AI-enabled projects; and a requirement that all AI research and other generated content receive human verification and reflection.

The ability to generate more options makes disciplined prioritization more important, not less.

3. IMPACT: PROTECT THE WORK ONLY HUMANS CAN DO.

AI can produce a donor prospect analysis. It cannot build trust with a prospective sponsor over coffee. AI can summarize a leadership challenge. It cannot look a struggling colleague in the eye and ask the compassionate question that changes a relationship. AI can generate executive coaching frameworks and meeting notes. It cannot replace the human wisdom, accountability and courage required to make a difficult choice.

Leaders should protect time for relationships, reflection and judgment — the very human activities that make AI-generated intelligence meaningful. And we should place boundaries around our AI-enabled work lives.  We must make sure that those of us who become highly productive through AI do not confuse increased output with increased impact — or silently turn every available evening, weekend, and quiet moment into additional time supervising our digital workforce.  Given my passion for and excitement about “living on an AI vertical learning curve, “ my wife and I often have “AI discussion timeouts,” where I am not allowed to talk about it – much less, fire up Claude on my laptop to show her the latest cool thing we generated together.

Not every new research question needs to be launched tonight. Not every good idea requires immediate development. Not every idle agent needs a new assignment before bedtime.

Sometimes the most productive instruction we can give our AI agents is: “Good work. We will review this tomorrow.”

THE HUMAN STILL HAS TO CHOOSE THE SHORE

Artificial intelligence is not simply reducing the burden of work. For many of us, it is revealing a much larger universe of work that could be done.

That is not necessarily bad news. It means that a small consulting firm, nonprofit leader, entrepreneur or executive can now access analytical, creative and research capacity once available only to organizations with large staffs and large budgets.

But abundance creates a new leadership obligation. The best leaders in the AI era will not be the people whose agents generate the most reports, the most ideas or the most activity. They will be the people who know which waves to ride, which opportunities to ignore, which decisions require human judgment and when to step out of the ocean entirely.

Because the goal of AI is not to keep every agent busy. The goal is to help human beings create meaningful impact — while still leaving enough time and energy to be fully human.

Footnotes

[1] Shakked Noy and Whitney Zhang, “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence,” Science 381, no. 6654 (2023): 187–192. Finding cited in the article abstract: average time decreased 40% and quality rose 18%.

[2] Erik Brynjolfsson, Danielle Li and Lindsey Raymond, “Generative AI at Work,” The Quarterly Journal of Economics 140, no. 2 (2025): 889–942. Published article reports a 15% productivity increase measured by issues resolved per hour.

[3] Fabrizio Dell’Acqua et al., “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality,” working paper, 2023; subsequently published in Organization Science.

[4] Aruna Ranganathan and Xingqi Maggie Ye, “AI Doesn’t Reduce Work—It Intensifies It,” Harvard Business Review, February 9, 2026; Laura Counts, “AI Promised to Free Up Workers’ Time. UC Berkeley Haas Researchers Found the Opposite,” Haas News, February 18, 2026.

[5] Microsoft WorkLab, “Breaking Down the Infinite Workday,” June 17, 2025; Microsoft, 2025 Work Trend Index Annual Report. The 275-per-day figure is based on the top 20% of Microsoft 365 users by ping volume received; the two-minute figure is calculated over an eight-hour workday.

[6] Organisation for Economic Co-operation and Development, Generative AI and the SME Workforce: New Survey Evidence (2025), Figure 3.5.

[7] International Labour Organization, Generative AI and Jobs: A Refined Global Index of Occupational Exposure (2025).

[8] World Economic Forum, Future of Jobs Report 2025 (2025).

Research Bibliography

Brynjolfsson, Erik, Danielle Li and Lindsey Raymond. “Generative AI at Work.” The Quarterly Journal of Economics 140, no. 2 (2025): 889–942.

Dell’Acqua, Fabrizio, et al. “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality.” Working paper, 2023; subsequently published in Organization Science.

International Labour Organization. Generative AI and Jobs: A Refined Global Index of Occupational Exposure. 2025.

Microsoft. 2025 Work Trend Index Annual Report. 2025.

Microsoft WorkLab. “Breaking Down the Infinite Workday.” June 17, 2025.

Noy, Shakked and Whitney Zhang. “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence.” Science 381, no. 6654 (2023): 187–192.

Organisation for Economic Co-operation and Development. Generative AI and the SME Workforce: New Survey Evidence. 2025.

Ranganathan, Aruna and Xingqi Maggie Ye. “AI Doesn’t Reduce Work—It Intensifies It.” Harvard Business Review. February 9, 2026.

University of California, Berkeley Haas School of Business. “AI Promised to Free Up Workers’ Time. UC Berkeley Haas Researchers Found the Opposite.” February 18, 2026.

World Economic Forum. Future of Jobs Report 2025. 2025.

 

CHU RECOMMENDS: 4 Books, 1 Novel, & 3 Podcasts to Learn About & Keep Up with AI

Net/ Summary:

The Books:

  • The AI Driven Leader by Geoff Woods
  • AI First by Adam Brotman and Andy Sack
  • The Experimentation Machine by Jeffrey Bussgang
  • Human + Machine by Paul R. Daugherty & H. James Wilson

The Novel:

  • Coded Justice, by Stacey Abrams

The Podcasts:

  • The Most Interesting Thing in AI
  • Beyond the Prompt – How To Use AI In Your Company
  • Practical AI

More Details:

The Books:

The AI Driven Leader by Geoff Woods
This book blends strategic frameworks with real-world applications to help leaders understand and implement AI initiatives. Woods distills complex concepts into approachable tools for decision-makers.
Best for those wanting to translate AI potential into actionable leadership strategies.

AI First by Adam Brotman and Andy Sack
A practical playbook for leaders in any industry, AI First lays out the mindset and operating model needed to integrate AI into every level of an organization. The authors focus on customer experience, organizational design, and cultural transformation.
Best for those wanting to shift their business mindset to lead with AI from the ground up.

The Experimentation Machine by Jeffrey Bussgang
Bussgang, a venture capitalist and Harvard professor, explores how top startups use experimentation and data—especially with AI—to drive innovation. The book includes case studies from the tech world and frameworks for iterative learning.
Best for those wanting to understand how AI powers experimentation, especially in fast-moving startups and product teams.

Human + Machine by Paul R. Daugherty & H. James Wilson
This foundational book from two Accenture executives lays out how companies can combine human ingenuity with AI’s capabilities to reinvent business processes. It introduces the concept of “missing middle” jobs and augmented intelligence.
Best for those wanting to explore how AI augments—not replaces—human work across industries.

 

 The Novel:

Coded Justice by Stacey Abrams
Abrams weaves a fast-paced legal thriller around a deepfake video and a high-stakes courtroom battle. Beneath the drama lies a thought-provoking look at AI, surveillance, and ethics.
Best for those wanting to grasp the real-world potential in health care and the risks of AI through a gripping, fictional lens.

The Podcasts:

The Most Interesting Thing in AI
Hosted by Nathan Benaich, this podcast offers sharp insights into the latest developments in AI, from research to policy. With guests from DeepMind, OpenAI, and VC firms, it’s both accessible and rigorous.
Best for those wanting to stay current on breakthroughs and big-picture trends in the AI ecosystem.

Beyond the Prompt – How To Use AI In Your Company
This podcast focuses on real-world implementations of AI tools across functions like sales, marketing, operations, and customer service. It’s geared toward business leaders and internal innovators.
Best for those wanting to learn practical, tactical ways to embed AI in daily business workflows.

Practical AI
Produced by Changelog, this long-running podcast brings together developers, data scientists, and entrepreneurs to discuss AI applications, tools, and ethics. Each episode balances technical depth with big-picture thinking.
Best for those wanting to understand how AI actually works—and how to build with it.

Please let me know your recommendations! 

PS/ Disclaimer: One of the major debates about AI is “Does it/ can it/ or will AI make people lazy?”  FYI, I have actually read all 5 books (and others I have not recommended) and listen to these podcasts every week, but after outlining the article, I asked ChatGPT to write the short summaries and “best for” recommendations for each bullet from the summary.  I did not feel the need to edit what she wrote. Am I lazy or productive????

Summary:

I recently completed Google’s Coursera course on prompt engineering to continue sharpening my use of AI—for both work and play. Like many of you, I want to get better, faster, and more reliable outputs from these powerful tools. To help me remember the core principles, I’ve adopted and modified a fun and memorable mnemonic (more on that in a second). But first, here’s the big idea:

To write effective prompts, you need to include seven core sections:

Teeny Tiny Crabs Riding Fat Enormous Iguanas
T = Task  T = Tone  C = Context  R = References  F = Format  E = Engage  I = Iterate

Include each of these elements in your prompt, and you’ll dramatically improve your results.

Where This Came From

Much of this is based on Tina Huang’s excellent YouTube summary, Google’s 9-Hour Prompt Engineering Course in 20 Minutes. (As someone once said: “If you steal from one person, it’s plagiarism. If you steal from many, it’s research.” I do a lot of research!)

The Google course itself is built around five inputs for effective prompt design:

Task, Context, References, Engage, Iterate

Their trainers introduced the mnemonic:

Thoughtfully Create Really Excellent Inputs

Tina found it hard to remember—and I agreed. She came up with a more vivid version:

Tiny Crabs Riding Really Enormous Iguanas

To that, I added two key concepts from my own experience—Tone and Format—to make it more complete.

The final version?

Teeny Tiny Crabs Riding Fat Enormous Iguanas

Why Add “Tone” and “Format”?

I’ve written hundreds of prompts across multiple platforms while using AI in professional consulting and nonprofit fundraising. Here’s why those two extra sections matter:

  • Tone is critical for anything involving writing. For example, when I want a professional yet conversational article (like this one), I say so in the prompt. Tone is often influenced by the Context section, especially when I open with something like:

“I am the head of a boutique consulting firm that specializes in…”
This helps the AI match voice, audience, and style.

  • Format becomes essential for large-scale research tasks. I’m currently using AI to research the charitable giving practices of 200+ companies to prioritize potential donors for several nonprofit clients. In this kind of work, it’s not enough to just get raw information—I need it delivered in tables, bulleted lists, or other clean formats that are easy to review and analyze.
    Gemini (Google’s AI) is particularly strong at formatting outputs into tables, and with one click, those can be exported into Google Sheets—saving tons of time.

A Quick Walkthrough of Each Section

  • #Task#: Be as specific as possible. Clearly define what you want the AI to do. I often assign the AI a role or persona, like:

“You are an expert content strategist writing a blog post on how to use AI in marketing research.”
This helps focus the AI’s responses.

  • #Tone#: Set the mood—professional, playful, technical, academic, or conversational. If your writing has a target voice, state it upfront.
  • #Context#: Describe who you are, why you’re asking the question, and who the audience is. The better the AI understands your intent, the better its output.
  • #References#: Upload or include everything relevant: job descriptions, resumes, bios, organizational goals, website URLs—whatever provides grounding for the AI’s output. The more context it has, the smarter it behaves.
  • #Format#: Be clear about how you want the information delivered. Want a comparison table? A checklist? A three-paragraph summary? Tell it.
  • #Engage#: Don’t copy and paste the output blindly. Engage with it. Review it. Challenge it. AI tools still make plenty of hallucinations (mistakes), so check citations, dates, and factual claims before you use them. Ask for sources. Fact-check relentlessly.
  • #Iterate#: Rarely do you get the perfect response on the first try. In my experience, it takes 2–3 iterations to get what I really want.

Here’s a fun example:
I used ChatGPT to create a cartoon for a party invitation featuring my American Bully, Izzy. I uploaded a photo and asked for a cartoon of her in a chef’s hat next to a grill.

  • Version 1: Looked like Izzy, but she was wearing her leather biker jacket from the photo.
  • Version 2: I asked for a chef’s jacket—got that—but the dog didn’t look like Izzy anymore.
  • Version 3: I asked to combine the head from version 1 and the jacket from version 2—and nailed it!

Iterating means providing clear, specific feedback. When the AI gets something wrong, tell it what and why. That’s how you teach it—and improve your results over time.

One Final Tip: Use Section Headers in Your Prompts

I have read several books and articles about AI and cannot remember where I learned this, but some recommend separating your prompts into the TTCRFEI sections and placing a “#” before and after the section title, e.g. #Task#.  Experts suggest this will improve the quality of your outputs by adding clarity and structure, focus, and reducing ambiguity.  By segmenting the prompt, you can make sure the AI knows what it is reading and how to use the information. For example, after reading # Task #, the AI knows the following text defines what it needs to do. After # Reference #, it understands that the text is supplementary information that it should consider. It also avoids or at least reduces misinterpretation.

Let’s Keep Learning Together

I hope this is helpful. If you’ve developed your own strategies for writing better prompts—or if you’ve tested this framework—I’d love to hear your thoughts. The more we share, the better we all get.

And Yes, I still recommend investing in the Coursera Google course.

One of my mantras as CEO of The Loyalty Group was “training without testing is little more than orientation.”  My (and Tina’s) shortened version/cartoons notwithstanding, if you are relatively new to AI, I would recommend taking the Coursera course.  It’s free, and if you have “fast ears” and can listen to the video portions at 1.5–2.0X speed, it takes far less than 9 hours.  The two things I like best about it are:

  1. Completing the course requires you to show actual prompts you have written, along with improvements you have made.
  2. The course has an exam at the end of each of the four major sections. If you score at least 80% on the exams, you receive this certificate:

Net/ Summary:

If it feels like AI came out of nowhere, is suddenly everywhere, and you somehow missed the bus—you’re right about the first two, and dead wrong about the third. While AI adoption has skyrocketed—faster than any technology in modern history—actual usage still varies widely by industry, age, and education. I’ve recently taken a deep dive into AI’s capabilities, and I’m here to tell you: it’s not too late to catch up. You can start using these powerful tools today.

The best way to learn AI is to use it. Tools like ChatGPT, Microsoft Copilot, and my favorite, Google Gemini, offer free versions and premium options (around $20/month) with expanded capabilities. The key is not to treat them like Google search boxes, but like smart collaborators.

Give AI context. Tell it who you are (e.g., “a nonprofit strategist”), how you’ll use the output (e.g., “to draft a fundraising plan”), and what tone you prefer (e.g., “professional but conversational”). Upload background documents and relevant data. Ask it to help you brainstorm, reword emails, rewrite resumes, analyze data, or even generate cartoons from photos.

Don’t know where to begin? Try:

  • Editing a recent cover letter and resume (include the job description in your uploads)
  • Rewriting an important email in a friendlier tone
  • Summarizing a report
  • Asking how AI could help with a work or personal challenge

I highly recommend reading the books The AI Driven Leader, by Geoff Woods and The Experimentation Machine, by my friend Jeff Bussgang.  It you want to jump start your learning from these books, consider reading Wood’s last Chapter 14 “”Go from 0 to 1: The Simple Path to Deliver Value with AI” and the Appendix “Prompt Library”   and Bussgang’s Appendix A “Prompt Tips and Examples” and D “AI Apps Unwrapped”  which contains a list of dozens of AI tools by usage category (e.g. “General Assistance,” “Get Creative,” and “Have Fun.” ) first.  There are also dozens of online courses on how to effectively and efficiently use AI, including Google’s AI Prompt Engineering Course on Coursera or – if you are as impatient as I – first watch the YouTube video “Google’s 9 Hour AI Prompt engineering Course in 20 Minutes.

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Summary: We drove over 3,000 miles last week from Boston to Atlanta, Jonesboro, Ellenwood, McDonough, Riverdale, Montgomery, Griffin, Lagrange, Oxford and Covington, Georgia and back home.  We travelled south to work door-to-door canvassing to help the Reverend Raphael Warnock and Jon Ossoff win their runoff races to represent Georgia in the US Senate.  The bulk of our time was invested in “curing” rejected ballots – mail-in ballots that had been rejected because the voter didn’t include the requisite ID or the Board of Elections reviewer decided that their signature did not match the one on file.

We realized that voter suppression was not only real, but much more insidious and painful than imagined.  Warnock and Ossoff won because their campaigns and the efforts of the Georgia Democratic Party were far superior to those of the Republicans, and because Stacey Abrams and her 2018 gubernatorial campaign manager Lauren Groh-Wargo provided the strategy and the intellectual, implementational and inspirational leadership to win the Georgia races and  flip the US Senate.  We also experienced the highs and lows of Wednesday, January 6th.  We woke to see data convincing us that both Warnock and Ossoff would win, were moved and inspired by the words and Memorial of Dr. King next to the  Ebenezer Baptist Church and then watched the horrific events unfold at our Nations Capitol throughout the afternoon and evening. As heartbreaking as those images and acts were, we remain optimistic about our future given both the impact of the leadership and work we saw in Georgia and the words of Dr. King who reminds us that “the moral arc of the universe bends slowly, but it bends in the direction of justice.”

 “We came to Georgia to do GOTV work, we were blessed to have the opportunity to do civil rights work.”

The 5 Observations from 8 Days on the Front Lines in Georgia

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I have had the great fortune to be a small part of the extraordinary success of Year Up over the past 16 years.  Year Up is the innovative workforce development organization started in 2001 by Gerald and Kate Chertavian that recruits, trains and places underserved inner city young adults in living wage careers with Fortune 500 companies and other leading enterprises.  Year Up started with 22 students in one Boston location and has grown to serving 3,700 young adults this year in 17 locations across the  country.

I am blessed to have had the opportunity to play many roles at Year Up, including serving on the National Board for a decade.  My current role is working with a handful of large US companies: GE, Comcast, Liberty Mutual and IBM to identify and fulfill their needs for entry-level middle skill talent.

A few weeks ago, we were given the opportunity to share this video at a conference attended by 300 GE IT Leaders from around the world:

Click on this image to view the GE Year Up video

Even though I have been doing this for over 16 years – the video literally sent chills down my spine.  As I have often said, I am one of the luckiest men in the world and appreciate so much the opportunity to work with Year Up’s students and corporate partners every day.

Last weekend, I thought a lot about the series of events and extraordinary level of collaboration that led to the creation of this video and wanted to share them with you.

All roads lead back to David and Gerald

Year Up was started in 2000 by Founder & CEO Gerald Chertavian.  After graduating from Bowdoin, Gerald worked on Wall Street and spent every Saturday with his “Little Brother” David Heredia.  He quickly realized that David and many of his friends were smart, motivated and capable, but didn’t have the opportunity to realize their potential to end up in prosperous, meaningful, fulfilling careers.  After selling his successful internet company in 1999, Gerald dedicated himself to creating Year Up to provide the “David’s” of our country with the skills, experience and support they need to succeed.

Gerald Chertavian and David Heredia 1988

Our founding corporate partners

In addition to GE, Year Up has supplied talent to over 250 leading enterprises across the country. Without them, Year Up couldn’t exist.  Today, we benefit from a tremendous 16-year track record of providing real, tangible value to our corporate partners and can back that up with a 60 Minutes episode about Year Up that includes testimonials from Ken Chenault, the Chairman of American Express and Jamie Dimon, Chairman and CEO of JP Morgan Chase.  But in the beginning, Gerald and I were void of any hard evidence that our model would work. Luckily for us and the 16,000+ students we have served, a few visionary leaders took a chance on our model and hired the first Year Up interns.

They included:

  • Phyllis Yale – then Managing Partner for Bain & Company’s Boston office
  • David Kenney – then CEO of Digitas
  • David Andre – then CIO of Upromise
  • Brett Browchek – then COO of Putnam Investments

With the initial support of these leading companies, we were able to secure commitments from enough companies to place our first class of students in their internships.

Founding Corporate Sponsors

Our extraordinary Founding Class of students

Without the grit and determination of our students, Year Up would not have made it to its second anniversary, much less to 17 cities.  The success of our students – from class one through those on internships today – is the real reason Year Up has been so successful.  Our corporate partners continue to hire Year Up interns and graduates and refer us to their colleagues at other enterprises because they have found that we have become a valuable pipeline of talent.

Year Up’s Founding Class February 2001

Our partnership with GE Digital and the creation of the video

The genesis of the partnership with GE Digital began in 2013 when our consultant Ed Solomon introduced Year Up to Bill Ruh, the CEO of GE Digital.  With Bill’s support, Alex Nguyen and Raul Cardenas became the first Year Up students placed at GE Digital in San Ramon in January 2014. Both had successful internships at GE and were offered and accepted full time positions.  Alex currently works as a software developer at OSU’s Open Source Lab and Raul has been promoted several times at GE and currently works as an Application Operations Engineer.

After seeing the 60 Minutes episode about Year Up, GE CIO Jim Fowler discovered that GE Digital had hired several students and graduates.  When GE made the decision to move their headquarters from Fairfield Connecticut to Boston’s Seaport area, Jim asked CTO Adam Radisch to consider placing Year Up interns in their My Tech Lounge at the new office.  Modeled after Apple’s Genius Bar, GE’s My Tech Lounges are walk-up help desks in attractive lounge areas where employees can quickly get support for laptop, tablet, phone and other hardware and software problems.

Last June, Year Up Boston’s Business Development executive Randi Kinsella and I traveled to meet with Adam to explain our program and discuss the opportunity to pilot our students in a GE My Tech Lounge.  Amidst Yankees memorabilia and moving boxes being packed for his impending move, Adam gave us 30 minutes to explain Year Up’s model.  We had a full presentation, but quickly made the decision to share only one slide:

Although he appeared supportive at the time, Adam later shared, “When I first heard about Year Up, I thought it was a second chance program for at risk kids, and probably not right for GE.  This slide changed my mind.  I decided to give a few students a chance in Boston, they knocked the ball out of the park and now I am Year Up’s executive champion at GE and want to help grow the program to as many divisions that need great entry level talent as we can.”

After returning to Boston, Randi and I met with Year Up Boston Executive Director Bob Dame and other Boston executives and worked with them to “match” the right students for an internship at GE’s new headquarters.  Adam had stressed the importance of strong interpersonal and communications skills when we met with him and our Boston team selected Angel, Cody and Ryan for this pilot program.  Guided by their incredibly supportive GE managers, Alex and Jesse, our three students were successful in their internship and all three received full time offers from GE.  At their graduation, Alex received the award for The Best New Supervisor and Angel was a featured graduation speaker.  From his remarks, I learned that Angel had originally turned down his acceptance to Year Up, but was contacted a week later by a staff member who convinced him to join the program.  If you listen to Angel’s speech, you will hear him give credit to his mom, his Year Up internship colleagues and the support of his GE managers for his success:

Click on the image to watch Angel’s speech

During our November monthly update with Adam, I shared some of the internal communications our other partners have developed to highlight their partnership with Year Up and asked him for an introduction to a GE marketing executive.  Adam introduced me to Jen Sampson, IT Communications & Engagement Leader for GE Digital.

Jen agreed to meet with us on the 23rd of December at Year Up’s Chicago offices.  While most of the country was winding down for the holidays, Roberto Zeledon, Year Up’s Director of Marketing, Randi and I flew to Chicago to meet with Jen, where we were hosted by Executive Director Jack Crowe.  As part of a short presentation about Year Up and our partnership with GE, we shared this JPMorgan Chase video that features CIO and Year Up champion John Galante and several of our graduates who have been hired by the bank:

 

 

Click on the image to see the JP Morgan Chase video


This video was the brainchild of John and my Year Up colleague Betsy Goodell, who leads our partnership with JPMorgan Chase executives.

After a tour of Year Up Chicago led by two students, Jen returned to her office.  Then, acting at what I now referred to as “GE Speed,” she emailed me less than an hour later and invited us to produce a similar video about GE’s partnership with Year Up. If we were able to create a short video by January 16th, Jen had already received approval from CIO Jim Fowler to “premier” it a their upcoming IT Leaders meeting in Phoenix, where 300 GE executives would be in attendance.

Within hours of receiving Jen’s email, Roberto confirmed with Year Up’s Brand Manager Kim Wheeler that we could create a video over the next 3 weeks, despite most people being on holiday between Christmas and New Year’s.  Kim and Randi managed the entire production of the video. I was visiting GE Digital in San Ramon and our Bay Area site when Gerald, our students and their fantastic managers were filmed.

Jen and Jim were also kind enough to invite us to have a Year Up booth at their conference outside the room where they showed the video. During the conference, we made over 20 GE executive contacts and are following up on new opportunities with 5 GE Divisions who have not yet hired Year Up students or graduates.

After hearing Angel’s graduation speech, I reached out to Ari (the social work intern who convinced him to join Year Up) to thank her for that fateful phone call.  She emailed me back, “As one of Year Up’s Co-Founders and head of Boston Student Services Linda Swardwick Smith always says ‘it takes a village to do this work’, and I’m very grateful Year Up and GE teamed up to form that village for these men, and again I’m honored to have been a part of it.”

Her email inspired this article, as it clearly took the entrepreneurial actions of many people to create our GE Year Up Partnership video. My primary reason for writing this was to thank all of those who helped it become a reality.  The more I do this work, the more I realize our success is driven by:

  1. Our students and alumni who make the sacrifices to join Year Up and power through their life challenges to demonstrate their capabilities during internship and graduate from our program.
  2. Our staff and instructors that teach, support and help our students prepare for internship success.
  3. Our extraordinary corporate partners who create the opportunities for our students to succeed.

What I do is relatively easy – I just observe, package and communicate what happens, connect students with partners and make the occasional inappropriate “ask” of our partners like, “Can I bring three of my friends to your internal meeting of 300 senior execs in Phoenix?”

Thanks so much to Cody, Angel and Ryan, to Jim, Adam, Alex, Jesse and Jen and to everyone at GE, our other partners and our team at Year Up who contributed to the creation of the video.