About This Course
Artificial intelligence is no longer a distant technological frontier — it is reshaping industries, redefining competitive advantage, and transforming how organisations operate, compete, and serve their customers. For executives and managers, the challenge is not to become data scientists, but to become informed, confident leaders who can ask the right questions, make sound investment decisions, and steer their organisations through an era of unprecedented technological change.
This five-day programme, AI Literacy for Executives and Managers, delivers exactly that capability. Designed specifically for senior and mid-level leaders with little or no technical background, the course demystifies AI — from machine learning and natural language processing to generative AI and predictive analytics — and translates these concepts into the language of business strategy, risk, and value creation. Participants leave with a coherent mental model of what AI can and cannot do, grounded in real-world organisational contexts.
Beyond conceptual understanding, the programme addresses the critical leadership decisions that AI adoption demands: how to identify high-value AI use cases, how to evaluate vendor proposals, how to govern AI responsibly, and how to build the internal capabilities and culture needed to sustain AI-driven transformation. Through case studies drawn from Africa, the Middle East, and global markets, participants explore how organisations similar to their own are using AI to drive efficiency, improve decision-making, and unlock new revenue streams.
TrainingComplex has designed this course to be immediately actionable. Every module connects AI concepts to the strategic and operational realities participants face in their own roles. By the end of the programme, delegates will be equipped not only to understand AI but to champion it — translating executive insight into organisational momentum.
Who Should Attend
- Chief Executive Officers, Managing Directors, and C-Suite Executives
- Directors and Senior Managers across all functional areas
- Department Heads and Division Leaders
- Strategy, Innovation, and Transformation Managers
- HR and Talent Development Leaders responsible for building AI-ready workforces
- Finance and Operations Managers evaluating AI-driven process improvements
- Public sector leaders and government officials overseeing digital transformation initiatives
- Entrepreneurs and business owners seeking to integrate AI into their ventures
Learning Objectives
- Articulate core AI concepts — including machine learning, deep learning, natural language processing, and generative AI — in plain business language
- Distinguish between genuine AI capabilities and common myths or vendor overpromises
- Identify and prioritise high-value AI use cases relevant to their specific industry and organisational context
- Apply structured frameworks to evaluate AI investment proposals and assess the readiness of their organisation for AI adoption
- Develop a practical AI strategy aligned with broader organisational goals and risk appetite
- Establish governance structures and ethical guidelines for responsible AI deployment
- Manage the human dimensions of AI adoption, including change management, upskilling, and stakeholder communication
- Critically assess AI-generated outputs and understand the role of human oversight in AI-assisted decision-making
- Navigate key legal, regulatory, and data privacy considerations associated with AI use
- Design a roadmap for initiating or scaling AI initiatives within their team or organisation
Course Modules
Module 1: Understanding Artificial Intelligence — Concepts Every Leader Must Know
- What AI actually is — and what it is not: separating fact from fiction
- Key branches of AI: machine learning, deep learning, natural language processing, and computer vision
- How AI systems learn from data: supervised, unsupervised, and reinforcement learning explained simply
- Generative AI and large language models — capabilities, limitations, and business relevance
- The AI maturity continuum: from rule-based automation to autonomous systems
- Common AI terminology decoded for non-technical executives
Module 2: The AI Landscape — Tools, Platforms, and Market Realities
- Overview of leading AI platforms and tools available to organisations today
- SaaS AI solutions versus custom-built models — how to choose the right approach
- How major technology vendors (Microsoft, Google, Amazon, IBM) position their AI offerings
- Emerging AI applications across sectors: healthcare, finance, agriculture, logistics, and government
- The African and Middle Eastern AI ecosystem — local players, regional initiatives, and opportunities
- How to read AI market research and analyst reports critically
Module 3: AI Use Case Identification and Prioritisation
- Mapping the organisational value chain to identify where AI creates the most impact
- Categories of AI use cases: efficiency, decision support, personalisation, prediction, and automation
- The AI opportunity canvas — a structured tool for surfacing and evaluating use cases
- Prioritisation criteria: feasibility, data availability, ROI potential, and strategic alignment
- Avoiding the common trap of pursuing AI for its own sake rather than for business value
- Workshop: Participants identify and rank three AI opportunities within their own organisation
Module 4: Data — The Foundation of Every AI Initiative
- Why data quality, quantity, and governance determine AI success or failure
- Types of data organisations hold and how they can be leveraged for AI
- Data readiness assessment — how to evaluate whether your organisation's data is AI-ready
- Data privacy, sovereignty, and compliance considerations for African and global organisations
- Building a data culture: encouraging data literacy and responsible data practices at all levels
- Working constructively with your IT and data teams — what executives need to ask and understand
Module 5: Evaluating AI Solutions and Vendor Proposals
- How to structure an AI due-diligence process as a non-technical buyer
- Key questions every executive must ask an AI vendor before signing a contract
- Understanding AI model performance metrics without needing a data science background
- Total cost of ownership: beyond licensing fees to implementation, maintenance, and change costs
- Red flags in AI vendor pitches — recognising overpromised capabilities and hidden risks
- Exercise: Participants critique a simulated AI vendor proposal using a structured evaluation rubric
Module 6: AI Strategy — Aligning AI with Organisational Goals
- What an organisational AI strategy is and how it differs from a technology roadmap
- Framework for developing an AI strategy: vision, capabilities, governance, and roadmap
- Aligning AI initiatives with corporate strategy, competitive positioning, and stakeholder expectations
- Building the business case for AI investment — financial and non-financial value articulation
- Setting realistic timelines and managing expectations for AI project outcomes
- The AI strategy canvas: a practical tool participants complete for their own organisation
Module 7: Governing AI Responsibly — Ethics, Bias, and Accountability
- Why AI governance is a leadership responsibility, not just a technical or legal one
- Sources of bias in AI systems and how biased outputs manifest in real-world decisions
- Ethical AI principles: fairness, transparency, accountability, explainability, and human oversight
- Establishing an AI governance structure — roles, policies, and review mechanisms
- Regulatory developments globally and in Africa: what executives need to monitor
- Scenario discussion: participants navigate an AI ethics dilemma drawn from a real-world case
Module 8: Legal, Regulatory, and Data Privacy Considerations
- Overview of key AI-relevant regulations: GDPR, African Union data frameworks, and emerging national AI laws
- Intellectual property considerations when using AI-generated content and outputs
- Liability and accountability when AI systems cause harm or make erroneous decisions
- Contracting for AI: key clauses executives should insist upon in technology agreements
- Employee rights, surveillance, and the legal limits of AI-driven workforce management
- Building a compliance-aware approach to AI deployment without stifling innovation
Module 9: Leading the Human Side of AI Adoption
- Why most AI initiatives fail due to people and culture, not technology
- Change management frameworks applied to AI transformation programmes
- Communicating AI initiatives to employees, boards, and external stakeholders with clarity and confidence
- Addressing employee fears about job displacement — honest conversations and retention strategies
- Building AI capability across the workforce: upskilling strategies and learning pathways
- Leadership behaviours that model and reinforce an AI-positive organisational culture
Module 10: Building Your AI Roadmap and Leading from the Front
- Synthesising course learning into a coherent, actionable AI leadership agenda
- Designing a phased AI adoption roadmap with clear milestones, owners, and success metrics
- Monitoring and evaluating AI initiative performance — KPIs, dashboards, and review cadences
- Sustaining momentum: governance rhythms, innovation forums, and continuous learning practices
- Personal leadership commitments — each participant articulates their 90-day AI action plan
- Course review, peer feedback, and close: next steps in the AI literacy journey
Requirements & Prerequisites
Participants should hold a managerial or senior leadership role and have general familiarity with business strategy, operations, or administration. No prior technical background in AI, data science, or programming is required — this course is specifically designed for non-technical leaders. A willingness to engage with new concepts and apply learning to real organisational challenges is all that is needed.
Training Methodology
- Executive briefings that translate complex AI concepts into strategic business language, using analogies drawn from familiar leadership and management contexts
- Real-world case studies from African, Middle Eastern, and global organisations showcasing successful and failed AI implementations, with structured debrief discussions
- AI use-case identification workshops where participants map AI opportunities to their own organisation's value chain and strategic priorities
- Vendor proposal critique exercises in which participants evaluate simulated AI product pitches using a structured due-diligence framework
- Ethics and governance scenario discussions that surface the real-world dilemmas executives face when deploying AI in sensitive or high-stakes environments
- Peer learning panels drawing on the diverse industry experience of participants to compare AI adoption challenges across sectors
- Hands-on demonstration sessions using leading AI tools — including generative AI platforms — so leaders can experience capabilities firsthand without writing code
- Personal AI Readiness Assessment to help each participant benchmark their organisation's current AI maturity and identify priority gaps
- AI strategy canvas exercises where participants draft a high-level AI roadmap for their own team or department
- Reflective journalling and action-planning sessions at the close of each day to consolidate learning and identify immediate next steps
Organisational Benefits
- Leaders who can confidently guide AI strategy without depending solely on technical specialists
- Reduced risk of costly AI investments driven by hype, misalignment, or insufficient due diligence
- Faster identification of high-return AI opportunities across business functions
- Stronger internal alignment between technology, operations, HR, and finance on AI priorities
- Improved organisational readiness for AI adoption through better-informed change leadership
- More ethical, transparent, and compliant AI practices that protect organisational reputation
- Enhanced competitive positioning in industries undergoing AI-driven disruption
- A culture of informed curiosity and innovation that attracts and retains forward-thinking talent
Where Is AI Literacy for Executives and Managers Training Offered?
This course runs in-person across: Nairobi, Dubai, Naivasha, Johannesburg, Nakuru, Zanzibar, Kigali, Riyadh, Cape Town, Lagos, Kampala, Abuja, Mombasa, Dar es Salaam, Accra, Arusha, Pretoria, Kisumu, Addis Ababa, plus Live Virtual (online) cohorts. Browse live dates for your city below.
Upcoming Schedules
| Location | Format | Dates | Price |
|---|
| Live Virtual |
Online |
5 Oct 2026 – 9 Oct 2026 |
KES 80,000 |
| Nairobi, Kenya |
In-Person |
12 Oct 2026 – 16 Oct 2026 |
KES 105,000 |
| Dubai, United Arab Emirates |
In-Person |
12 Oct 2026 – 16 Oct 2026 |
USD 4,100 |
| Naivasha, Kenya |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
KES 115,000 |
| Johannesburg, South Africa |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 3,500 |
| Live Virtual |
Online |
24 Oct 2026 – 15 Nov 2026 |
KES 80,000 |
| Nakuru, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
| Zanzibar, Tanzania |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,500 |
| Kigali, Rwanda |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 1,900 |
| Riyadh, Saudi Arabia |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 4,500 |
| Cape Town, South Africa |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 3,800 |
| Lagos, Nigeria |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,500 |
| Kampala, Uganda |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 1,900 |
| Abuja, Nigeria |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,800 |
| Mombasa, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
+231 more dates — view live schedule →
Frequently Asked Questions
Do I need a technical background to attend this course?
Absolutely not. This programme is designed specifically for executives and managers with no prior knowledge of AI, data science, or programming. All technical concepts are explained in plain business language, and the focus throughout is on strategy, decision-making, and leadership rather than coding or mathematics.
Will I receive a certificate upon completing the course?
Yes. Participants who attend and complete the full five-day programme will receive a Certificate of Completion from TrainingComplex, confirming their participation in the AI Literacy for Executives and Managers programme. This certificate can be shared on professional profiles and used for continuing professional development records.
How is this course different from an IT or data science training?
This course is not a technical training — it is a strategic leadership programme. Rather than teaching you how to build AI models, it equips you to make informed decisions about AI, lead adoption initiatives, evaluate vendors, govern AI responsibly, and build organisational capability. Think of it as the boardroom lens on AI, not the engineering lab.
Is the course content relevant to my specific industry or region?
Yes. The programme incorporates case studies from a wide range of sectors — including finance, healthcare, agriculture, logistics, government, and retail — and draws on examples from African, Middle Eastern, and global markets. Facilitators encourage participants to apply every framework and tool directly to their own organisational context throughout the five days.
Can my organisation send a group of managers to attend together?
Absolutely, and we actively encourage it. Group attendance accelerates shared understanding and makes it much easier to implement AI initiatives back in the workplace, since participants return with a common language and aligned strategic perspective. TrainingComplex also offers bespoke in-house delivery of this programme for organisations wishing to train larger leadership cohorts at their own premises.
