About This Course
Artificial intelligence is no longer a technology project confined to the IT department — it is a boardroom imperative that is reshaping industries, redefining competitive advantage, and fundamentally altering how organisations create and capture value. Senior executives who lack a working understanding of AI risk making uninformed strategic decisions, misallocating capital, and ceding ground to more AI-savvy competitors.
This five-day intensive programme, AI for Senior Executives, is designed specifically for leaders who need to lead AI transformation without necessarily becoming data scientists. It delivers a clear, jargon-free grounding in how AI works, where it creates measurable business value, and how to build the organisational capabilities — people, processes, data, and governance — required to scale it responsibly.
Through executive case studies, boardroom simulations, and structured strategy workshops, participants will develop a personal AI leadership agenda and a practical roadmap for embedding AI across their business units. The programme draws on real-world examples from finance, healthcare, retail, manufacturing, government, and professional services, making the learning immediately applicable regardless of sector.
By the end of the programme, participants will leave with the strategic vocabulary, evaluation tools, and leadership confidence to champion AI initiatives at the highest levels of their organisations — and to hold their technology teams, vendors, and boards accountable for results.
Who Should Attend
- Chief Executive Officers and Managing Directors
- Chief Operating Officers and Chief Strategy Officers
- Chief Financial Officers and Finance Directors
- Chief Human Resources Officers and People Directors
- Chief Marketing Officers and Commercial Directors
- Senior Vice Presidents and General Managers
- Board Members and Non-Executive Directors seeking AI literacy
- Public sector Permanent Secretaries and Director Generals
- Senior government officials responsible for national digital transformation
- Entrepreneurs and founders scaling AI-enabled businesses
Learning Objectives
- Articulate how AI, machine learning, and generative AI work at a conceptual level sufficient to engage credibly with technical teams and vendors
- Identify high-value AI use cases within your organisation and prioritise them using a structured business case framework
- Evaluate the readiness of your organisation's data infrastructure, talent, and processes to support AI deployment
- Apply ethical and governance frameworks to manage AI risk, bias, regulatory compliance, and reputational exposure
- Design a phased AI adoption roadmap aligned to corporate strategy, budget cycles, and change management realities
- Lead cross-functional AI initiatives by fostering collaboration between business units, data science teams, and technology partners
- Assess and negotiate AI vendor proposals, partnerships, and build-vs-buy decisions with confidence
- Measure the ROI and performance of AI investments using appropriate KPIs and value realisation metrics
- Anticipate the workforce implications of AI and lead a human-centred transformation that retains talent and builds new capabilities
- Communicate a compelling AI vision to boards, investors, regulators, and employees to build alignment and drive adoption
Course Modules
Module 1: The AI Landscape: What Every Executive Must Know
- Demystifying AI, machine learning, deep learning, and generative AI in plain business language
- The evolution of AI from rule-based systems to large language models and autonomous agents
- Key AI capabilities relevant to business: prediction, classification, generation, optimisation, and personalisation
- How AI differs from traditional software and why that changes how you manage it
- The current state of AI adoption across sectors in Africa, the Middle East, and globally
- Common executive misconceptions about AI and how to correct them
Module 2: AI Business Value: Where the Real Opportunities Lie
- Frameworks for identifying AI use cases with the highest strategic and financial impact
- Revenue-generating AI applications: personalisation, dynamic pricing, demand forecasting, and customer acquisition
- Cost-reduction AI applications: process automation, predictive maintenance, fraud detection, and supply chain optimisation
- AI for competitive differentiation versus AI for operational parity — knowing the difference
- Prioritisation tools: the AI opportunity matrix and effort-value scoring
- Case study: how a leading African bank deployed AI to reduce loan default rates by 30%
Module 3: Understanding Your Data: The Foundation of AI Success
- Why data is the raw material of AI and what makes data AI-ready
- Assessing your organisation's current data maturity using a structured readiness diagnostic
- Data governance essentials: ownership, quality standards, lineage, and access controls
- The role of data lakes, data warehouses, and cloud platforms in enabling AI at scale
- Privacy regulations and cross-border data compliance considerations for AI (GDPR, Kenya Data Protection Act, NDPR)
- How to have a productive conversation with your CDO or CTO about data infrastructure investment
Module 4: AI Technology Landscape: Platforms, Tools, and Vendors
- Overview of leading AI platforms: Google Cloud AI, Microsoft Azure AI, AWS, and IBM Watson
- Generative AI tools shaping the executive workplace: ChatGPT, Microsoft Copilot, Gemini, and sector-specific solutions
- Build vs. buy vs. partner: a decision framework for AI capability acquisition
- How to evaluate vendor AI claims, proof-of-concept proposals, and contract terms
- Avoiding vendor lock-in and ensuring portability of AI investments
- Key questions every executive should ask before signing an AI technology contract
Module 5: AI Strategy: Aligning Artificial Intelligence with Corporate Goals
- Translating corporate strategy into an AI roadmap with clear milestones and ownership
- The AI strategy canvas: mapping use cases, capabilities, data assets, and success metrics
- Integrating AI planning into existing annual strategy and budgeting cycles
- Choosing between centralised AI centres of excellence and decentralised business-unit AI teams
- Building the internal business case for AI investment: ROI modelling and risk-adjusted returns
- Workshop: participants draft an AI strategic priority statement for their own organisation
Module 6: AI Ethics, Governance, and Responsible Use
- Understanding AI bias: where it comes from, how it manifests, and how executives must respond
- The business and reputational risks of deploying unethical or ungoverned AI
- Regulatory developments: the EU AI Act, proposed African AI frameworks, and sector-specific rules
- Building an AI ethics policy and governance committee at board level
- Human-in-the-loop principles: when AI should and should not make final decisions
- Case study: high-profile AI failures and the executive accountability lessons they reveal
Module 7: AI and the Workforce: Leading People Through Transformation
- Understanding which roles AI will augment, which it will displace, and which it will create
- Conducting a workforce AI impact assessment across business units
- Reskilling and upskilling strategies: building AI literacy at all levels of the organisation
- Managing employee anxiety and resistance during AI-driven change
- Attracting and retaining AI talent in a competitive labour market
- Designing a human-centred AI adoption programme that sustains morale and productivity
Module 8: AI in Core Business Functions: Finance, HR, Operations, and Marketing
- AI applications in financial management: forecasting, audit, fraud detection, and investor reporting
- AI in human resources: talent acquisition, performance analytics, attrition prediction, and workforce planning
- AI in operations and supply chain: demand sensing, logistics optimisation, and quality control
- AI in marketing and sales: customer segmentation, content generation, lead scoring, and churn prediction
- Cross-functional AI integration challenges and how to overcome organisational silos
- Executive panel discussion: real-world AI deployments across functional areas
Module 9: Measuring AI Performance and Managing AI Risk
- Defining the right KPIs for AI initiatives: accuracy, efficiency gains, revenue impact, and customer outcomes
- Building an AI performance dashboard for executive oversight and board reporting
- Understanding model drift, data degradation, and the need for continuous AI monitoring
- Technical and operational risk categories in AI: cybersecurity, model failure, and third-party dependency
- Establishing escalation protocols when AI systems produce unexpected or harmful outputs
- Conducting an AI post-investment review: lessons from implementations that delivered and those that did not
Module 10: Your AI Leadership Agenda: From Insight to Action
- Synthesising programme learning into a personal AI leadership philosophy and communication narrative
- Crafting an AI vision statement for your organisation that resonates with board, staff, and stakeholders
- Building a 90-day AI quick-win plan and a 12-month strategic AI roadmap
- Securing board and investor buy-in for AI initiatives using a structured executive presentation framework
- Establishing an ongoing AI learning habit: curated resources, networks, and peer communities
- Participant presentations: each delegate shares their AI leadership action plan and receives peer feedback
Requirements & Prerequisites
Participants should hold a senior leadership or executive management role and be involved in strategic decision-making within their organisation. No technical background in data science, programming, or IT is required — this programme is explicitly designed for business leaders, not technologists. A basic familiarity with digital tools and an openness to engaging with emerging technology concepts is all that is needed to participate fully.
Training Methodology
- Executive case study analysis drawing on AI transformations at global organisations including Amazon, JPMorgan Chase, Safaricom, the NHS, and Unilever
- Boardroom simulation exercises in which participants debate and approve or reject AI investment proposals using real-world financial and strategic criteria
- AI strategy canvas workshops where each participant maps AI opportunities against their own organisation's value chain
- Facilitated peer-to-peer roundtables enabling executives to share sector-specific AI challenges and cross-pollinate solutions
- Vendor pitch role-plays that sharpen participants' ability to critically evaluate AI product claims and negotiate favourable terms
- Ethics and governance scenario discussions exploring real AI failures, regulatory actions, and reputational crises
- Personal AI leadership action planning, where each delegate leaves with a documented 90-day and 12-month agenda
- Guest perspectives via curated video interviews with AI-transformed executives sharing unfiltered lessons from the field
Organisational Benefits
- Executives return with a clear, actionable AI strategy aligned to corporate objectives rather than vague aspirations
- Organisations gain leaders capable of asking the right questions of AI vendors, consultants, and internal data teams
- Reduced risk of costly AI project failures driven by poor executive oversight or misaligned expectations
- Improved board-level confidence in approving and governing AI investments
- Faster identification and scaling of AI use cases that generate measurable revenue, cost savings, or efficiency gains
- Stronger cross-functional collaboration between business leadership and technology functions
- A more future-ready leadership team capable of attracting AI talent and partnerships
- Enhanced organisational reputation as an AI-responsible and innovation-led enterprise
- Better workforce transition planning, reducing disruption and retaining institutional knowledge during automation
- A peer network of senior executives across sectors sharing AI leadership insights and best practices
Where Is AI for Senior Executives Training Offered?
This course runs in-person across: Accra, Kigali, Dar es Salaam, Kampala, Naivasha, Cape Town, Riyadh, Mombasa, Johannesburg, Lagos, Dubai, Nairobi, Kisumu, Pretoria, Addis Ababa, Abuja, Arusha, Zanzibar, Nakuru, plus Live Virtual (online) cohorts. Browse live dates for your city below.
Upcoming Schedules
| Location | Format | Dates | Price |
|---|
| Accra, Ghana |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 3,800 |
| Kigali, Rwanda |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 1,900 |
| Dar es Salaam, Tanzania |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,300 |
| Kampala, Uganda |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 1,900 |
| Naivasha, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
| Cape Town, South Africa |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 3,800 |
| Riyadh, Saudi Arabia |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 4,500 |
| Mombasa, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
| Johannesburg, South Africa |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 3,500 |
| Lagos, Nigeria |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,500 |
| Kampala, Uganda |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
USD 1,900 |
| Accra, Ghana |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
USD 3,800 |
| Naivasha, Kenya |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
KES 120,000 |
| Dubai, United Arab Emirates |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
USD 4,100 |
| Nairobi, Kenya |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
KES 105,000 |
+227 more dates — view live schedule →
Frequently Asked Questions
Do I need a technical background to attend this programme?
Absolutely not. This programme is designed exclusively for business leaders, not technologists. All AI concepts are explained in plain business language, and the focus is entirely on strategy, leadership, and decision-making rather than coding or data science.
What will I leave with at the end of the five days?
You will leave with a personal AI leadership action plan, a draft AI roadmap for your organisation, practical evaluation frameworks for AI investments, and the strategic confidence to lead AI initiatives at board level. All course materials, tools, and templates are included.
Is this course relevant if my organisation is still in the early stages of AI adoption?
Yes — in fact, this is the ideal moment to attend. The programme is built around helping executives make sound decisions about where to start, how to prioritise, and how to build the right foundations, making it equally valuable whether your organisation is exploring AI for the first time or looking to scale existing pilots.
Will I receive a certificate upon completion?
Yes. Participants who complete the full five-day programme receive a Certificate of Completion in AI for Senior Executives from TrainingComplex, which can be shared on professional profiles and used for CPD documentation.
How is the programme structured across the five days?
The programme runs from Monday to Friday with structured morning and afternoon sessions covering ten modules in a logical progression — from AI fundamentals and strategy through to governance, workforce implications, and personal action planning. Sessions blend expert facilitation, executive case studies, peer discussions, and practical workshops.
