Chief AI Officer Programme
What will you learn
01 Define enterprise AI ambition Connect AI priorities to business strategy and establish a clear enterprise direction. | 02 Assess AI maturity Evaluate organisational readiness across data, technology, process, people and governance. | |
03 Prioritise the AI portfolio Identify and sequence high-value use cases based on value, feasibility, risk and readiness. | 04 Design governance and operating model Establish decision rights, roles, policies, controls and an operating model for AI at scale. | |
05 Lead workforce adoption Define capability needs, process redesign and change interventions for sustained human-AI adoption. | 06 Build value and roadmap Develop business cases, KPIs and a 90-, 180- and 365-day enterprise AI roadmap. |
Who should attend?
- C-suite executives and senior leaders
- Current and aspiring Chief AI Officers
- Chief Data Officers and Chief Digital Officers
- CIOs and technology leaders
- Transformation and innovation leaders
- Strategy leaders
- Business-unit leaders with AI transformation responsibilities
- Heads of AI, analytics or automation
- Senior professionals responsible for enterprise AI programmes
- Leaders responsible for AI governance and operating-model design
- Executives seeking to move from experimentation to scaled AI adoption
Pre-requisites
- No programming or technical background required
- Senior management or leadership experience recommended
- Participants should have responsibility for, or significant involvement in, AI, digital, data or transformation initiatives
- Access to organisational strategy, priorities and current transformation initiatives recommended
- Ability to engage internal stakeholders between sessions strongly recommended
- Participants should be prepared to work on a real organisational AI agenda throughout the programme
- Laptop required for practical exercises and programme assignments
Delivery format
- Hybrid – face-to-face + live stream
- Delivered over six consecutive weeks
- One half-day/evening session per week
- Executive-level instructor-led sessions
- Strategic frameworks and practical case discussions
- Organisational diagnostics and assessments
- Individual and group exercises
- Peer learning and executive discussion
- Workplace assignments between sessions
- Participants build their own enterprise AI blueprint throughout the programme
- 1-hour individual mentorship session for every participant
- Final strategy and roadmap presentation
Explore the nineteen modules designed to help senior leaders define enterprise AI ambition, assess organisational maturity, prioritise use cases, design governance and operating models, drive adoption and build a practical enterprise AI roadmap.
Module 1: The Enterprise AI Shift
What you'll explore:
- Understanding the evolution from traditional AI to generative and agentic AI
- Examining how AI is changing organisational capabilities and competitive dynamics
- Distinguishing AI experimentation from enterprise transformation
- Understanding the implications for leadership, work and decision-making
- Identifying the strategic questions senior leaders need to address
Module 2: AI Ambition & Organisational Maturity
What you'll explore:
- Defining the organisation's AI ambition
- Assessing current AI maturity across key capability dimensions
- Identifying gaps in data, technology, process, people and governance
- Understanding current initiatives and fragmentation risks
- Establishing a baseline for the enterprise AI journey
Module 3: Organisational AI Baseline Assessment
What you'll explore:
- Complete the enterprise AI maturity assessment
- Map current AI initiatives across the organisation
- Interview selected internal stakeholders
- Identify major organisational pain points and opportunities
- Draft the organisation's preliminary AI ambition
Module 4: Developing the Enterprise AI Strategy
What you'll explore:
- Connecting AI priorities to business strategy
- Identifying strategic value pools for AI
- Defining where the organisation should lead, follow or selectively invest
- Establishing strategic principles for AI investment
- Translating AI ambition into strategic priorities
Module 5: AI Use-Case Discovery & Portfolio Prioritisation
What you'll explore:
- Systematically identifying AI opportunities across the organisation
- Distinguishing productivity, decision-support, customer and transformation use cases
- Assessing value, feasibility, risk and readiness
- Prioritising quick wins versus strategic initiatives
- Building a balanced enterprise AI portfolio
Module 6: Build the Organisational AI Use-Case Portfolio
What you'll explore:
- Identify potential use cases within the participant's organisation
- Assess opportunities against agreed prioritisation criteria
- Validate shortlisted opportunities with business stakeholders
- Identify potential business owners and sponsors
- Select priority initiatives for further development
Module 7: Data & Technology Foundations for Enterprise AI
What you'll explore:
- Understanding why AI performance depends on data readiness
- Assessing data quality, structure, accessibility and governance
- Understanding AI architecture and platform choices
- Evaluating integration requirements across enterprise systems
- Developing principles for build, buy and partner decisions
Module 8: Responsible AI, Risk & Governance
What you'll explore:
- Defining enterprise responsible AI principles
- Understanding key AI risks including bias, privacy, security and reliability
- Establishing governance roles and accountability
- Designing policies, controls and approval mechanisms
- Balancing innovation with appropriate oversight
Module 9: Foundation & Governance Assessment
What you'll explore:
- Assess data and technology readiness for priority use cases
- Identify major foundation gaps
- Map key AI risks and control requirements
- Draft an initial AI governance structure
- Define governance priorities for the next stage of implementation
Module 10: Designing the AI Operating Model
What you'll explore:
- Comparing centralised, federated and hybrid AI operating models
- Defining roles across business, technology, data, risk and transformation teams
- Establishing decision rights and accountability
- Designing the AI use-case delivery lifecycle
- Defining the relationship between internal capability and external partners
Module 11: Process Redesign & Scaling AI into Operations
What you'll explore:
- Moving beyond task automation toward process redesign
- Identifying where humans and AI should collaborate
- Redesigning workflows around AI-enabled capabilities
- Defining human approval, escalation and exception points
- Establishing a pathway from pilot to scaled operational adoption
Module 12: Target Operating Model & Process Redesign
What you'll explore:
- Draft the target AI operating model
- Define key roles and ownership structures
- Select one priority process for AI-enabled redesign
- Map the future-state human-AI workflow
- Identify barriers to implementation and scaling
Module 13: People, Skills & Workforce Transformation
What you'll explore:
- Understanding how AI changes roles and baseline skills
- Identifying AI literacy requirements across the workforce
- Defining specialist and leadership capability needs
- Assessing where roles may be augmented, redesigned or newly created
- Building an organisational AI capability-development approach
Module 14: AI Adoption & Change Leadership
What you'll explore:
- Understanding why access to AI tools does not equal adoption
- Moving employees from awareness to confident usage
- Identifying barriers related to trust, capability and incentives
- Designing champion networks, communication and enablement interventions
- Measuring behavioural adoption and sustained usage
Module 15: AI Capability & Adoption Plan
What you'll explore:
- Assess workforce AI capability requirements
- Identify priority employee populations for upskilling
- Map key stakeholder groups and adoption barriers
- Design targeted enablement and communication interventions
- Define adoption metrics and ownership
Module 16: AI Business Cases, Value & Performance Management
What you'll explore:
- Building robust AI business cases beyond technology cost savings
- Quantifying productivity, revenue, customer and risk benefits
- Establishing baseline measures before implementation
- Defining leading and lagging AI performance indicators
- Governing benefits realisation across the AI portfolio
Module 17: Enterprise AI Roadmap & Executive Action Plan
What you'll explore:
- Translating strategy into sequenced initiatives
- Balancing foundational investments with high-value use cases
- Prioritising near-, medium- and longer-term actions
- Establishing key milestones, ownership and dependencies
- Building a practical 90-, 180- and 365-day AI roadmap
Module 18: Enterprise AI Blueprint
Each participant develops an organisation-specific blueprint covering:
- AI ambition and strategic priorities
- Organisational AI maturity and foundation gaps
- Prioritised AI use-case portfolio
- Data and technology requirements
- Responsible AI and governance model
- AI operating model and decision rights
- Human-AI process redesign priorities
- Workforce capability and upskilling agenda
- Adoption and change approach
- Business-value and KPI framework
- 90-, 180- and 365-day implementation roadmap
Module 19: 1-hour One-to-One Mentorship Session per Participant
What you'll explore:
- Review of the participant's enterprise AI blueprint
- Discussion of organisation-specific challenges and constraints
- Feedback on use-case portfolio and prioritisation
- Guidance on governance and operating-model choices
- Review of implementation priorities and executive next steps
PRACTICAL TOOLS & RESOURCES
You will walk away with
A practical toolkit to help you identify, design, build, test and implement agentic AI solutions in your organisation.
| ✓ | Final Enterprise AI Blueprint A practical organisation-specific blueprint developed throughout the programme. |
01 Enterprise AI Maturity Assessment covering strategy, data, technology, process, people and governance | 02 AI Strategy Canvas |
03 Enterprise AI Use-Case Library | 04 Use-Case Discovery and Prioritisation Framework |
05 AI value-versus-feasibility assessment template | 06 Data and technology readiness assessment |
07 Responsible AI Governance Framework | 08 AI risk and controls checklist |
09 AI Operating Model Design Canvas | 10 Roles and decision-rights template |
11 Human-AI process redesign framework | 12 AI workforce capability assessment |
13 AI literacy and upskilling framework | 14 Stakeholder and adoption-planning templates |
15 AI business-case template | 16 Benefits-realisation and KPI framework |
17 AI portfolio-management template | 18 Weekly workplace assignments tied to the participant's organisation |
19 1-hour individual mentorship per participant | 20 90-, 180- and 365-day AI roadmap |
Practical resources you can keep using beyond the programme and apply directly to agentic AI opportunities in your organisation.
Schedule
Programme details to be announced soon; watch this space.
Connect with our team
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Dhisha Viswanathan
Programme Advisor - Digital Programme
