Artificial Intelligence for Business Leaders and Senior Executives

Course overview

Artificial Intelligence and Emerging Technologies for Managers Training equips executives, department heads and organisational leaders with practical skills for evaluating and adopting AI, automation and digital technologies. The workshop covers generative AI, AI agents, enterprise platforms, business intelligence, cloud computing, cybersecurity, AI governance, technology investment and workforce transformation. Participants learn how to identify high-value use cases, develop technology business cases, manage implementation risks and create an actionable AI and digital transformation roadmap for their organisations.

Artificial intelligence is transforming decision-making, customer engagement, business operations, financial management, human resource management, project delivery, risk management and service provision. Technologies such as generative AI, AI agents, intelligent automation, cloud computing, advanced analytics, the Internet of Things (IoT), blockchain and digital platforms are creating new opportunities for productivity, innovation and organisational competitiveness. However, successful adoption requires more than acquiring technology. Managers must identify high-value use cases, evaluate investment returns, establish governance arrangements, protect organisational data, manage cybersecurity and regulatory risks, oversee technology vendors and prepare employees for changing workflows.

Course objectives

Explain the business implications of artificial intelligence and emerging technologies and identify relevant opportunities across organisational functions.
Develop an actionable implementation roadmap covering process redesign, workforce readiness, technology procurement, change management and performance measurement.
Establish appropriate AI governance, data protection, cybersecurity, ethical use, human oversight and technology risk management arrangements.
Evaluate AI tools, enterprise technology platforms, automation opportunities and technology investments using structured business cases and return-on-investment criteria.
Develop an AI and digital transformation strategy aligned with organisational objectives, operational priorities and measurable business outcomes.

Who should attend

Chief executive officers, managing directors, senior executives, department managers, operations managers, finance managers, human resource managers, marketing managers, strategy and planning officers, project and programme managers, business development managers, public sector managers, government department heads, banking and financial services managers, NGO and development programme managers, risk and compliance managers, digital transformation leaders, IT managers, innovation officers, procurement and supply chain managers, customer experience managers, business consultants, board members and organisational change leaders.

Course content

Module 1: Understanding Artificial Intelligence and the Emerging Technology Landscape Artificial intelligence concepts and terminology, differences between traditional AI, machine learning, deep learning and generative AI, large language models and found
Module 2: AI Strategy and Digital Transformation Leadership Aligning AI adoption with organisational strategy, identifying strategic business priorities, evaluating organisational digital maturity, mapping business functions to technology opportunities,
Module 3: Generative AI and AI Copilots for Managerial Productivity How generative AI systems work, selecting appropriate enterprise AI assistants, prompt design for management tasks, AI-assisted research and information synthesis, preparing reports and
Module 4: AI Agents and Intelligent Business Process Automation Understanding AI agents and agentic workflows, differences between chatbots, copilots and autonomous agents, identifying repetitive and decision-intensive workflows, AI-assisted task plannin
Module 5: Data-Driven Management, Business Intelligence and Predictive Analytics Data as a strategic organisational asset, data-driven decision-making, descriptive and diagnostic analytics, predictive and prescriptive analytics, executive dashboards and
Module 6: AI Applications Across Business and Organisational Functions AI in strategic planning and executive decision support, AI in finance and budgeting, forecasting and expenditure analysis, AI in human resource management and workforce planning, rec
Module 7: Evaluating Enterprise AI Tools and Technology Platforms Categories of enterprise AI platforms, cloud-based and privately hosted AI services, comparing Microsoft Azure AI Foundry, Amazon Bedrock, Google Vertex AI and IBM watsonx, enterprise prod
Module 8: Cloud Computing, Digital Platforms and Enterprise Architecture Cloud computing concepts and service models, public cloud, private cloud and hybrid cloud, software as a service, platform as a service and infrastructure as a service, cloud-based
Module 9: Emerging Technologies Beyond Generative AI Internet of Things and connected devices, sensor-driven monitoring and predictive maintenance, digital twins for operational planning, blockchain and distributed ledger applications, smart contracts an
Module 10: AI Governance, Ethics, Privacy and Responsible Use Principles of responsible AI, organisational AI governance structures, executive and board accountability, acceptable-use policies, AI system inventories and use-case registers, privacy and pe
Module 11: Cybersecurity, Technology Risk and Business Resilience AI-related cybersecurity threats, phishing and AI-enabled social engineering, deepfakes and impersonation risks, prompt injection and sensitive data leakage, unauthorised access to AI syst
Module 12: Financial Evaluation, Investment Decisions and Business Value Identifying technology investment opportunities, defining the business problem before selecting a solution, developing technology business cases, capital expenditure and operating e
Module 13: AI in Strategy, Innovation and Competitive Advantage AI-enabled business model innovation, identifying unmet customer and stakeholder needs, using AI to analyse markets and competitors, strategic forecasting and scenario planning, developing n
Module 14: Workforce Transformation, Change Management and AI Skills How AI changes jobs, roles and organisational workflows, identifying tasks suitable for augmentation or automation, workforce impact assessments, AI literacy for managers and employees,
Module 15: Capstone — Developing an Organisational AI and Emerging Technology Roadmap Assessing organisational digital maturity, identifying strategic business and service delivery challenges, mapping potential AI and emerging technology use cases, sco

General notes

This practical workshop focuses on the managerial rather than programming aspects of technology adoption. Participants learn how to develop an AI adoption strategy, evaluate enterprise technology platforms, redesign business processes, manage AI-enabled projects, measure business value and establish responsible AI governance.
Through case studies, management simulations and practical planning exercises, participants will develop an actionable technology adoption roadmap tailored to their organisation's priorities, resources and operating environment.
Practical Exercises and Management Case Studies AI opportunity assessment: Identify and prioritise five AI use cases within a participant's organisation using business value, feasibility, cost and risk. Executive AI assistant exercise: Use an approved AI environment to prepare a management briefing, summarise documents and develop an action plan, with accuracy and confidentiality checks. Workflow automation redesign: Map a repetitive organisational process and design an AI-assisted workflow with defined approval points and exception handling. Enterprise technology evaluation: Compare enterprise AI platforms against security, integration, governance, cost, scalability and vendor support criteria. AI governance simulation: Respond to a scenario involving inaccurate AI-generated advice, confidential data exposure or an automated decision that adversely affects a customer. Technology investment business case: Estimate implementation costs, expected benefits, key risks and measurable performance indicators for a proposed AI project. Capstone presentation: Present an organisational AI and emerging technology roadmap to a simulated management committee.
Expected Practical Outputs AI opportunity assessment matrix, organisational AI readiness assessment, enterprise AI adoption strategy, AI use-case inventory, technology prioritisation scorecard, enterprise AI platform evaluation matrix, AI investment business case, return-on-investment assessment template, AI governance policy outline, responsible AI checklist, AI risk register, data privacy and confidentiality checklist, third-party technology assessment template, AI-enabled workflow redesign, automation opportunity assessment, workforce AI skills development plan, digital transformation stakeholder map, technology procurement evaluation criteria, AI performance measurement framework, executive AI dashboard specification, 90-day AI implementation plan, phased organisational technology roadmap, capstone management presentation.

Frequently asked questions

1. Do I ne1. Who should attend the Artificial Intelligence and Emerging Technologies for Managers Training Workshop?ed coding experience?

The workshop is suitable for senior executives, department heads, operations and finance managers, HR managers, project managers, public sector leaders, banking professionals, NGO managers, consultants and other professionals responsible for organisational performance and technology-related decisions.

2. Will specific AI tools be demonstrated?

Yes, the course includes live demonstrations of common workplace AI tools and how to evaluate new ones.

3. 2. Is this a technical AI or programming course?

No. It is a management-focused programme. Participants learn to evaluate AI applications, lead adoption initiatives, manage technology investments and establish governance controls without needing programming or advanced mathematics.

4. 3. Which emerging technologies are covered?

The programme covers generative AI, AI agents, machine learning, intelligent automation, cloud computing, business intelligence, IoT, blockchain, digital twins, geospatial intelligence and other technologies relevant to organisational strategy and operations.

5. 4. Will participants learn how to use AI in everyday management?

Yes. Practical exercises demonstrate AI-assisted research, reporting, document analysis, planning, workflow redesign and decision support, subject to organisational policies and data protection requirements.

6. 5. Does the course cover AI risks and responsible adoption?

Yes. It covers AI governance, privacy, cybersecurity, bias, explainability, third-party risk, human oversight, employee use policies and incident management.

7. 6. What will participants gain from the workshop?

Participants will gain a practical understanding of emerging technologies and leave with management tools for evaluating AI opportunities, developing business cases, governing adoption and preparing an implementation roadmap for their organisations.

Schedule & fees

Dates	Location	Duration	Fee (USD)
23/11/2026 - 27/11/2026	Nairobi,kenya or Virtual	5 Days	$1,500
08/03/2027 - 12/03/2027	Kisumu,Kenya	5 Days	$1,500
07/06/2027 - 11/06/2027	Mombasa,Kenya	5 Days	$1,500