Agentic AI Strategy Training Course: Value Cases, Operating Model and Roadmap

Programme Summary

Agentic AI strategy is the subject of this one-week training course for executives and transformation sponsors, ending in an agentic AI roadmap pack for one business unit. Boards are asked to fund agents that act on customers, suppliers and records, yet few organisations have settled where agents belong, who owns them and how value will be shown. The programme links value cases, portfolio choices, operating model, workforce impact and governance into one sequence, applying each tool to a unit the participant leads. Mars Training Centre UK delivers this programme on agentic AI strategy to mixed-organisation cohorts.

The Business Case

Agents differ from earlier automation because they take decisions and actions across several systems, so investment choices, accountability and workforce effects all change at once. Where agentic AI strategy is left to separate technology pilots, organisations accumulate overlapping projects, unclear ownership and savings nobody can verify. Executives who set a shared portfolio, funding rule and oversight model can stop weak initiatives early and scale the few that earn their place.

• Value Realisation: Improves as every initiative carries an owner, a baseline and a measure.
• Investment Efficiency: Improves as overlapping pilots are merged or stopped against portfolio criteria.
• Risk Exposure: Falls as accountability and oversight are agreed before agents act at scale.

Principles and Evidence Base

• NIST AI Risk Management Framework: Its govern, map, measure and manage functions shape the oversight model drafted in Session 4.
• ISO/IEC 42001: The standard for AI management systems frames policy, roles and records for the operating model in Sessions 3 and 4.
• Portfolio management: Ranking initiatives by value, feasibility and risk guides the choices made in Session 2.

Intended Participants

• Executives who allocate transformation budgets and answer to a board.
• Transformation sponsors who own cross-functional change programmes.
• Business unit leaders who decide where agents will take over work.
• Strategy and planning leaders who build multi-year roadmaps.
• Finance and risk leaders who challenge benefits and control claims.

Typical sectors include banking, utilities, healthcare and public administration.

Learning Outcomes

1. Participants will be able to evaluate where agentic AI creates value in their own business unit.
2. Participants will be able to prioritise initiatives within a portfolio using value, feasibility and risk.
3. Participants will be able to construct an operating model that assigns agent ownership and decision rights.
4. Participants will be able to assess workforce effects and plan the change they require.
5. Participants will be able to design a funding and measurement approach for staged investment.
6. Participants will be able to justify a roadmap and oversight model to a board.

Programme Structure

Day 1: Agentic AI Strategy and Value Cases

Where can agents change how the business earns, spends or serves?

• Agent Capability Map
• Value Driver Tree
• Use Case Long List
• Baseline and Benefit Sheet
• Strategic Fit Test

Day 2: Portfolio, Readiness and Data Foundations

Which initiatives should proceed first, and is the organisation ready for them?

• Value and Feasibility Matrix
• Readiness Assessment Grid
• Data Access and Quality Review
• Dependency and Sequencing Chart
• Stage-Gate Criteria

Day 3: Operating Model, Roles and Decision Rights

Who owns agents, and how do people and agents share work?

• Agent Ownership Model
• Decision Rights Matrix
• Human-Agent Task Split
• Central and Business Unit Roles Chart
• Vendor and Platform Choice Criteria

Day 4: Workforce, Funding and Governance

How are people, money and risk managed as agents scale?

• Role Impact Assessment
• Reskilling and Transition Plan
• Staged Funding Model
• Oversight and Escalation Framework
• Benefits Tracking Dashboard

Day 5: Applying the Tools to One Business Unit

Do the value, portfolio, operating and governance tools support one roadmap?

• Applying the Session 1 Value Driver Tree
• Using the Session 2 Value and Feasibility Matrix
• Testing the Session 3 Decision Rights Matrix
• Checking the Session 4 Staged Funding Model
• Completing the Agentic AI Roadmap Pack

Methodology

The programme uses a case analysis method built on anonymised transformation cases from several sectors, sample portfolio lists and board paper extracts. Participants work in peer groups on a shared business unit, challenge each other's value claims and rankings, and receive written facilitator comments on each exercise set.

• Suggested activity: Ranking twelve candidate initiatives and defending the order to a mock investment committee.
• Suggested activity: Redrawing decision rights after an agent takes over an approval step.
• Suggested activity: Drafting a staged funding request with stop conditions.

Capstone Output

Each participant completes an agentic AI roadmap pack for one business unit. It holds a value driver tree, a ranked portfolio, an operating model sketch, a workforce transition outline, a staged funding model and an oversight framework. The pack is used at work to brief a board, open budget discussions and set the order of delivery for the first agent initiatives.

Frequently Asked Questions

Is agentic AI strategy training suitable for executives without a technical background?

Yes. Agentic AI strategy training assumes senior responsibility for a business unit or programme and builds the needed technical vocabulary as the programme proceeds, without requiring any coding.

Which frameworks does agentic AI strategy rest on in this programme?

Agentic AI strategy rests on the NIST AI Risk Management Framework and ISO/IEC 42001 for oversight, together with portfolio management for ranking initiatives.

How is the pack from agentic AI strategy used at work?

You use the agentic AI roadmap pack to brief a board, open budget discussions and set the delivery order for the first agent initiatives.

How does agentic AI strategy training differ from agent design training?

Agentic AI strategy training centres on value, portfolio, operating model and governance decisions, while agent design training centres on building and testing individual agent workflows.