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AI Strategies for Leaders

  • 3 days
  • For Executives
  • On site · On campus

A three-day program in which your CEO and executive team build your company's AI strategy together, with your own data, on your own decisions, guided by faculty sessions and coached throughout. It follows the full path from ambition to execution: where AI changes your industry, which bets are worth making, what they cost and return, what to build or buy, and how to organize and govern it. On the third day you present the strategy and its expected return to the people who decide on the investment.

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Is this for you?

Who it is for

The CEO and executive team of one company: midsize companies and multinationals that use AI in places but do not yet have a company-wide plan, or have a plan that has not yet delivered measurable results.

Group size
  • In-company: your CEO and executive team, typically 6 to 12 leaders; owners, investors or directors can join on the third day
  • On campus: your leadership team at Columbia Business School in New York
Prior knowledge

No technical background is needed. The program is about decisions on strategy, money and organization.

Core objectives

  1. 01Set the ambition. Decide what AI must achieve for your company, and where to defend, extend or reinvent your business.
  2. 02Find where value moves. Map where AI creates and shifts value across your value chain and industry, including who could use it to enter your market.
  3. 03Choose and fund the bets. Select a balanced portfolio of AI initiatives, each with an investment case that shows its expected return.
  4. 04Make the technology choices. Decide what to build, buy or partner on, with a quick prototype of your most important bet in hand.
  5. 05Organize to scale. Set the decision rights, incentives and team structure that move AI from pilots into daily work.
  6. 06Commit to measurable results. Tie every initiative to KPIs and its contribution to the P&L, with an 18-month roadmap and a 100-day plan.
Why it matters

Most companies have AI pilots.

Few can show what they add to the P&L. AI Strategies for Leaders helps one leadership team at a time close that gap, inside your own company.

  • 9 in 10organizations use AI regularly in at least one business function
  • 37%of organizations report at least some impact of AI on their EBIT
  • 7.5%of companies are future-built for AI, with 2.4 times the revenue growth of laggards

Source: McKinsey & Company, The state of AI in 2026: On the road to ROI, August 2026 · Boston Consulting Group, AI Is Starting to Pay Off, September 2026

Questions you will answer for your company

  1. 01Where should AI change our business first?
  2. 02How much should we invest, and in what stages?
  3. 03What do we build, buy or partner on?
  4. 04Who owns AI, and who decides what?
  5. 05Which rules apply to us, and how do we stay in control?
  6. 06What return do we expect, and how will we measure it?

Who is in the room

  • CEO and executive team

    The leaders who set strategy and allocate capital, typically 6 to 12 people.

  • CFO

    Owns the investment case and the funding stages.

  • The executive who will run AI

    Often the CIO, CDO or COO, or the head of a business unit.

  • Owners and decision-makers

    The founder, owner, investors or directors can join on the third day to hear the strategy and challenge its return.

How the three days work

From ambition to an investment-ready plan

About 40% of the time is faculty sessions. The other 60% is work on your own plan, with coaching and challenge from peers.

  1. Before Preparation

    A company fact pack, short questionnaires for your HR, legal and technology leaders, and a framing call with the faculty.

  2. Day 1 Ambition and value

    You draft your ambition and map where AI changes your value chain, then sub-teams test each other's thinking.

    Chapters 1 and 2
  3. Day 2 Bets and money

    You choose your bets, write the investment case and prototype your top bet. One sub-team acts as the investment committee for another.

    Chapters 3 to 5
  4. Day 3 Organization and results

    You design the organization, set governance and KPIs and complete the roadmap, then present the strategy and its expected return to your decision-makers.

    Chapters 6 to 9
  5. After Follow-up

    A faculty review of your final plan within 30 days, and a check-in after 90 days on the first measurable results.

The rhythm of every session

  1. Faculty session

    Frameworks, evidence and examples, ending in one question for your plan.

  2. Work session

    Your team writes the chapter with your own data, with a coach at the table.

  3. Peer challenge

    Another sub-team reads your draft and tests it the way an investment committee would.

Six sessions, one plan

Each session starts with a faculty session and continues with work on your own plan.

Day 1Ambition and value
Session 1

Strategy meets AI

What AI can and cannot do today, what it costs, and what earlier digital waves teach about where advantage ends up. You set your company's AI ambition.

Your plan · Chapter 1
Session 2

Where AI creates value

How AI reshapes value chains, business models and industry boundaries, and who could use it to enter your market. You map the impact on your own business.

Your plan · Chapter 2
Day 2Bets and money
Session 3

Choosing the bets

How to score initiatives on value, feasibility, risk and time to value, and why a portfolio needs more than efficiency gains. You select five to seven bets.

Your plan · Chapter 3
Session 4

Funding and technology

Total cost, baselines, value tracking and funding in stages. Build, buy or partner, data foundations and vendor lock-in. You write the investment case.

Your plan · Chapters 4 and 5
Day 3Organization and results
Session 5

Organization and people

Decision rights between group, business units and countries. Central or federated AI teams. Roles, skills, incentives and trust. You design the organization.

Your plan · Chapter 6
Session 6

Governance and results

Oversight, AI risk appetite and the rules that apply, from the EU AI Act to US state laws. You set the KPIs, complete the roadmap and present your strategy.

Your plan · Chapters 7 to 9
What you take home

Your AI strategy in nine chapters

An investment-ready draft with the expected return of every initiative. You complete six chapters during the program. The other three leave as a structured outline and are finished within 30 days, with a review by the faculty.

  1. Chapter 1

    Ambition

    What AI must achieve, and where to defend, extend or reinvent.

  2. Chapter 2

    Value map

    Where AI creates and shifts value in your industry and value chain.

  3. Chapter 3

    Portfolio

    Five to seven bets, scored on value, feasibility, risk and time.

  4. Chapter 4

    Investment case

    Costs, expected returns and funding in stages.

  5. Chapter 5

    Technology

    What to build, buy or partner on, and the data you need.

  6. Chapter 6

    Organization

    Decision rights, teams, skills and incentives.

  7. Chapter 7

    Governance

    Risk appetite, oversight and the rules that apply.

  8. Chapter 8

    Roadmap

    Eighteen months of milestones, owners and KPIs.

  9. Chapter 9

    ROI case and first 100 days

    Expected P&L impact, how you will measure it, and the first 100 days.

  • Completed during the program
  • Outlined during the program, finished within 30 days

Also: a quick prototype of your most important bet, a faculty review of your final plan and a check-in after 90 days.

Our approach

Your plan, your data, your results

  1. 01

    Your own plan

    Every session ends in work on your company's strategy. The examples and the debate are about your industry, your markets and your numbers.

  2. 02

    Decisions with numbers

    Every bet has a cost, an expected return and a funding stage, so its contribution to the P&L is clear from the start.

  3. 03

    Governance from day one

    Oversight, risk appetite and the rules that apply to you are part of the plan from the start, so risks are managed before anything is built.

Lead advisor
Marc De Kuyper

Marc De Kuyper

  • Founder & CEO, Praexo Group
  • Adjunct Professor, Columbia Business School
  • Partner, StellarIQ (private equity)

Marc has spent more than two decades as a founder, operator and investor. He brings the view of someone who has had to make AI pay in his own companies, and the discipline of someone who teaches it to executives and boards.

  • Columbia Business School

    Adjunct Professor. Teaches AI strategy in the MBA program and in executive programs.

  • Technology & AI

    16 years as a technology founder and operator, focused on business systems in which AI agents do the work, on commercial excellence and on predictive analytics.

  • Consumer goods

    20 years in the consumer packaged goods sector, from fast-moving consumer goods to alcoholic beverages.

  • Family business governance

    Co-led ABN AMRO's Family Business Center. Guest lecturer at INSEAD, Harvard Business School, Kennesaw State University, the University of British Columbia and Columbia Business School.

Coaching in every work session. Praexo coaches work with your sub-teams during every work session, so the plan keeps moving between faculty sessions.

Everything you share stays confidential and is used only for your program. Program content and faculty may change.

What comes next

3 days

AI Strategies for Leaders

An investment-ready AI strategy in nine chapters, with the expected return of every initiative, an 18-month roadmap and a plan for the first 100 days.

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