AI for C-level Executives and Owners: Strategy, ROI, and a Portfolio of Use Cases
An advanced workshop for CEOs, COOs, CFOs, and business owners that takes you from selecting the right AI initiatives to a 10-page implementation strategy with an ROI model, governance principles, a vendor checklist, and a “pilot → scale” plan.
This course is not a review of trendy tools or a general introduction to AI. It was designed for people responsible for business performance, capital allocation, and the pace of change in the company. It starts from an observation from recent market reports: boards are increasing AI spending, but many organizations still struggle to translate investment into measurable productivity and lasting returns, while the advantage appears more often when a company redesigns end-to-end processes instead of implementing isolated experiments. In BCG research from 2025 and 2026, leaders report high AI usage intensity and growing pressure for measurable business impact, while Gartner emphasizes that productivity growth expectations often need to be adjusted, and McKinsey points out that the greatest value is concentrated in selected functions and specific applications, not in scattered initiatives. That is why the course takes a portfolio-of-investment-decisions perspective: how to select 15 use-case candidates, how to compare value against risk, how to calculate ROI and TCO, when to buy ready-made solutions and when to build internal advantage, how to assess vendor quality, how to structure responsibilities, and how to plan the first 90 days so you do not end up with a showcase pilot. Participants work on management artifacts, not technical demos: a use-case portfolio, an ROI model, a vendor checklist, a KPI dashboard, and a final 10-page AI strategy for their own company.
What you will learn
- You will build a portfolio of AI initiatives organized by business value, risk, and feasibility.
- You will distinguish image-building activities from use cases that truly affect revenue, margin, costs, productivity, or decision quality.
- You will calculate an initial ROI and TCO for AI initiatives, including implementation, organizational change, oversight, and maintenance costs.
- You will make a more informed build vs buy decision for key applications.
- You will prepare governance principles, accountability roles, and a risk escalation path.
- You will conduct vendor due diligence using a procurement checklist and evaluation criteria.
- You will design a “pilot → scale” plan with KPIs, milestones, and continuation criteria.
- You will create a 10-page AI strategy for the company along with a 90-day roadmap.
Prerequisites
Experience in managing a company, business unit, or budget; familiarity with the basics of management finance; willingness to work in a workshop format using examples from your own organization. No technical knowledge is required.
Course syllabus
- Why the board is responsible today for AI outcomes, not just experiments
- What the latest reports show: rising investment, pressure on ROI, and disappointment with productivity alone
- Where fashion ends: how to distinguish a strategic initiative from costly distraction
- Three company ambition profiles: defensive, selective, and offensive
- The workshop’s contrarian thesis: fewer pilots, more process redesign
- Quiz: Recognizing High-Value and Low-Value-Perceived Initiatives
- How to map the areas of a company where AI can improve P&L performance
- Five types of value: revenue, margin, costs, decision speed, and decision quality
- Seven dimensions for evaluating a use case: value, risk, data, change, time, sponsor, scalability
- Exercise: scoring 15 use cases on a shared priority matrix
- How to talk about use cases with the CFO, operations, and sales to avoid local optimization
- Workshop artifact: portfolio of use cases for the board
- Quiz: which initiatives go into the first wave and which into the strategic backlog
- Why Most AI ROI Claims Are Too Vague to Support an Investment Decision
- ROI model for the board: revenue, savings, avoided costs, and option value
- TCO Without Surprises: Implementation, Oversight, Organizational Change, and Maintenance Costs
- How to distinguish time savings from a real financial impact
- Before and after: a weak business case vs. a business case ready for the investment committee
- Exercise: building a business case for one use case from your own company
- ROI model template to use after the workshop
- Quiz: which financial assumptions are credible and which are wishful thinking
- Four decision scenarios: buy, configure, co-create, or defer
- What questions to ask before a company decides it must have a “tailor-made” solution
- What Really Determines the Decision: Process Uniqueness, Risk, Speed, and Internal Capabilities
- Comparison of two paths: quick purchase vs slower advantage building
- How to Avoid the Single-Vendor Trap Without Decision Paralysis
- Mini-workshop: sourcing decision for three types of use cases
- Quiz: Identifying the Right Purchase Model for a Business Situation
- How to assess whether a company is ready for implementation without getting bogged down in data chaos
- Which processes are worth connecting to AI right away, and which should be organized first
- Warning signs: the initiative looks attractive, but it won’t survive operational realities
- Dependency map: systems, process owners, decisions, and risk points
- How to talk to your team about data and integrations without getting into technical details
- Exercise: assessing the organization’s readiness to launch the first wave of initiatives
- Quiz: which barriers are critical at the start, and which can be addressed after the pilot
- Minimal decision governance for a company: sponsor, process owner, finance, risk, operations
- How to assign responsibilities so AI doesn’t become a “nobody’s project”
- Risks the board should see: reputation, bad decisions, compliance, vendor, people
- Adaptive governance: how to maintain control without killing implementation speed
- Usage policy and incident escalation path — what should be ready before scaling
- Workshop: responsibility and steering committee design for an AI portfolio
- Quiz: matching the appropriate responsibility to the type of risk and the implementation stage
- How to evaluate a supplier: not promises, but evidence, references, and readiness to implement
- Management questions for the supplier before signing the contract
- What to look for in references and case studies so you don’t buy a presentation instead of a result
- Weak vs. strong proposal: what should be included in scope, KPIs, and responsibilities
- Supplier checklist: security, implementation quality, change support, measuring results
- Exercise: comparing three offers and choosing a pilot partner
- Quiz: warning signs in the purchasing and negotiation process
- How to plan the first 90 days to deliver a decision, not just a demo
- Conditions for moving from pilot to scale: what results must appear and when
- Board KPI dashboard for management: adoption, quality, financial impact, risk, implementation speed
- Plan “pilot → scale”: milestones, decision gates, and owners
- Capstone: the structure of a 10-page AI strategy for a company
- Final workshop: preparing your own AI strategy based on the course templates
- Final quiz: management decisions in the first 12 months of the AI program
FAQ
For CEOs, board members, business owners, heads of business functions, and people responsible for performance, capital allocation, and the pace of change. This is a program for decision-makers who want to treat AI as a tool for growth, productivity, and operational advantage, not just a technology experiment.
It does not focus on trendy tools or general definitions. The emphasis is on management decisions: where AI can really improve the economics of the business, how to build a portfolio of use cases, how to calculate value, and how to avoid a situation in which the company funds many initiatives but sees no lasting return.
Because the market has entered a phase of value selection. In Deloitte research from 2025, 91% of organizations reported increased AI spending, but the advantage is built primarily by those who combine investment with decision governance, KPIs, and execution at the level of entire processes, not individual implementations. McKinsey, in turn, indicates that the greatest impact on EBIT comes from workflow redesign, meaning redesigning how the company operates, rather than simply adding technology to existing patterns.
The course helps structure investment decisions around AI: from selecting areas with the highest potential, through assessing costs and risks, to defining the sequence of implementations. This makes it easier to distinguish high-value initiatives from those that mainly improve local productivity but do not change the company’s result across the entire process.
Yes — especially when an organization has already run its first pilots but lacks a common prioritization model, success metrics, and a coherent scaling strategy. This is a common moment when the board needs to move from scattered experiments to a portfolio of use cases linked to financial and operational goals.
Among other things: how to assess use cases through the lens of value and feasibility, how to understand the difference between point automation and end-to-end transformation, how to talk about ROI under uncertainty, how to set up governance, and how to make decisions that increase the chance of measurable business impact.
No. The course is designed for business leaders, not technical specialists. It explains AI from the perspective of strategy, investment, organization, and results — so that participants can make better decisions without getting into complex architecture or programming details.
Because that is where real advantage most often materializes. Current analyses by consulting firms show that the greatest return appears when a company redesigns full workflows, roles, decisions, and metrics, instead of limiting AI to individual tools or isolated improvements. In other words: it is not about “adding AI,” but about translating it into a new way of operating the company.
- 12 hours
- Advanced
- Certificate on completion
- Access immediately after purchase
- Lifetime access and updates
30-day money-back guarantee