Be the first to know when new training courses are scheduled or dates are updated.
We run this course regularly across Nairobi, Mombasa, Kampala, Dar es Salaam, Kigali, Johannesburg, Dubai, Singapore, China and many more locations. The next intake dates will be published here shortly.
Need it sooner? Reach out and we'll fast-track a session for you or your team.
Prefer email? Submit a scheduling request and we'll get back to you shortly.
The Artificial Intelligence for Executives Executive Training Course is an intensive leadership development programme designed to equip senior executives, directors, business leaders, policymakers, and decision-makers with the strategic knowledge required to understand, evaluate, adopt, and govern Artificial Intelligence (AI) within modern organisations. As artificial intelligence, generative AI, machine learning, predictive analytics, intelligent automation, and data-driven decision-making continue to transform industries, executives need practical knowledge that enables them to distinguish genuine business opportunities from technology hype. The course provides a non-technical executive perspective on AI technologies, business applications, organisational transformation, competitive advantage, productivity improvement, innovation, and strategic leadership in the AI-driven economy.
The course explores Artificial Intelligence strategy, Generative AI, Large Language Models (LLMs), machine learning, natural language processing, computer vision, predictive analytics, intelligent automation, AI agents, business intelligence, data analytics, and emerging AI technologies from an executive leadership perspective. Participants examine how organisations can identify high-value AI use cases, assess organisational AI readiness, develop AI investment priorities, evaluate technology solutions, establish implementation roadmaps, and measure return on investment. Special attention is given to practical applications of AI in strategic planning, finance, human resources, marketing, customer experience, operations, procurement, project management, risk management, research, communication, and executive decision-making.
Participants will develop practical understanding of AI governance, responsible AI, data governance, cybersecurity, privacy, transparency, accountability, regulatory compliance, algorithmic bias, intellectual property, ethical AI, and organisational risk management. Executives will examine governance structures that enable organisations to deploy AI responsibly while protecting confidential information, maintaining stakeholder trust, managing third-party technology providers, and establishing appropriate human oversight. Through practical exercises and general case studies, participants will evaluate AI opportunities and risks, establish executive-level governance mechanisms, develop AI policies, prioritise investments, and consider the workforce, cultural, operational, and leadership implications of enterprise-wide AI adoption.
By the end of the Artificial Intelligence for Executives Executive Training Course, participants will be prepared to provide strategic leadership for AI-enabled organisational transformation and make informed decisions concerning AI investments, implementation, governance, partnerships, talent, data, and organisational capabilities. The programme combines executive presentations, strategic discussions, practical exercises, organisational assessments, demonstrations, case studies, and collaborative activities to help participants translate AI concepts into practical business strategies. Participants will develop an executive AI action plan that connects organisational priorities with measurable outcomes, responsible implementation, workforce development, innovation, operational efficiency, customer value, and sustainable competitive advantage.
By the end of the course, participants will be able to:
1. Understand the fundamental concepts, capabilities, limitations, opportunities, and strategic implications of Artificial Intelligence for executives and organisational leaders.
2. Evaluate Generative AI, Large Language Models, machine learning, predictive analytics, intelligent automation, AI agents, and other emerging AI technologies from a business leadership perspective.
3. Identify and prioritise high-value AI use cases aligned with organisational strategy, operational requirements, customer needs, and measurable business outcomes.
4. Develop an executive-level Artificial Intelligence strategy and implementation roadmap aligned with organisational priorities and digital transformation objectives.
5. Evaluate AI investments using business value, feasibility, organisational readiness, implementation risk, expected benefits, and return-on-investment considerations.
6. Apply AI-supported approaches to strategic planning, executive decision-making, forecasting, productivity improvement, innovation, and organisational performance management.
7. Establish effective AI governance frameworks addressing responsible AI, ethics, accountability, transparency, data protection, cybersecurity, regulatory compliance, and human oversight.
8. Lead organisational change associated with AI adoption, including workforce transformation, skills development, organisational culture, stakeholder engagement, and responsible technology adoption.
9. Evaluate AI vendors, technology platforms, partnerships, implementation models, and build-versus-buy decisions from an executive and organisational perspective.
10. Develop a practical executive AI action plan for responsible, scalable, measurable, and sustainable Artificial Intelligence implementation.
Organizations whose executives participate in this training will benefit through:
1. Improved executive understanding of Artificial Intelligence and its strategic implications for organisational competitiveness, innovation, productivity, and growth.
2. Stronger alignment between AI investments, corporate strategy, digital transformation initiatives, operational priorities, and measurable organisational outcomes.
3. Improved ability to identify, evaluate, prioritise, and implement high-value AI opportunities across different organisational functions.
4. More informed executive decision-making regarding AI technologies, Generative AI, automation, analytics, technology vendors, partnerships, and investment priorities.
5. Stronger AI governance, responsible AI practices, data governance, cybersecurity awareness, privacy protection, regulatory compliance, and organisational accountability.
6. Increased organisational productivity and operational efficiency through appropriate adoption of intelligent automation and AI-supported workflows.
7. Enhanced innovation capabilities through strategic application of Generative AI, machine learning, predictive analytics, intelligent systems, and emerging technologies.
8. Improved workforce preparedness through AI literacy, leadership development, change management, skills development, and effective human-AI collaboration.
9. Reduced technology, operational, reputational, ethical, compliance, and investment risks associated with poorly planned Artificial Intelligence implementation.
10. Development of an actionable AI transformation roadmap that enables sustainable adoption, measurable performance improvement, continuous innovation, and long-term organisational value creation.
This Artificial Intelligence for Executives Executive Training Course is designed for Chief Executive Officers (CEOs), Managing Directors, Executive Directors, Board Members, Directors, Deputy Directors, Commissioners, Permanent Secretaries, senior government officials, policymakers, Chief Operating Officers (COOs), Chief Financial Officers (CFOs), Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Digital Officers (CDOs), Chief Strategy Officers, Chief Risk Officers, Heads of Departments, senior managers, programme directors, project directors, business unit leaders, entrepreneurs, consultants, digital transformation leaders, innovation managers, strategy professionals, finance executives, HR executives, operations executives, public-sector leaders, development-sector executives, and other senior decision-makers responsible for organisational strategy, technology, innovation, transformation, investment, governance, or performance.
1. Understanding Artificial Intelligence, machine learning, deep learning, Generative AI, Large Language Models, natural language processing, computer vision, predictive analytics, intelligent automation, and AI agents.
2. Evolution of Artificial Intelligence and major developments shaping the future of business, government, development organisations, and global industries.
3. Understanding how modern AI systems work at an executive level, including data, algorithms, models, training, inference, prompts, outputs, and human oversight.
4. Assessing the capabilities, limitations, opportunities, misconceptions, and risks associated with current Artificial Intelligence technologies.
5. Exploring the strategic impact of AI on organisational productivity, competitiveness, innovation, customer experience, workforce transformation, and business models.
6. Executive Case Study: Evaluating how a diversified organisation identifies AI opportunities across operations, finance, customer service, human resources, and strategic planning.
1. Developing an enterprise Artificial Intelligence strategy aligned with corporate strategy, digital transformation, organisational objectives, and stakeholder priorities.
2. Identifying, assessing, prioritising, and selecting high-value AI use cases using business value, feasibility, data availability, implementation complexity, risk, and strategic importance.
3. Applying Artificial Intelligence to executive decision-making, scenario analysis, strategic planning, forecasting, market intelligence, performance management, and organisational analytics.
4. Developing AI business cases covering expected benefits, implementation costs, productivity improvements, risk reduction, revenue opportunities, return on investment, and performance indicators.
5. Designing an AI implementation roadmap covering quick wins, strategic initiatives, organisational capabilities, governance, technology, data, workforce, and change management.
6. Executive Case Study: Prioritising competing AI investment opportunities and developing a phased executive AI transformation roadmap for a growing organisation.
1. Understanding Generative AI, Large Language Models, multimodal AI, conversational AI, AI copilots, AI assistants, and autonomous or semi-autonomous AI agents.
2. Applying Generative AI to executive research, strategic analysis, communication, report preparation, knowledge management, brainstorming, summarisation, presentations, and decision support.
3. Understanding executive prompt design, context management, output evaluation, verification, human review, and techniques for improving the quality and reliability of AI-assisted work.
4. Exploring AI-powered automation of business workflows, administrative processes, knowledge-intensive tasks, customer interactions, document management, and organisational reporting.
5. Managing Generative AI limitations and risks including inaccurate outputs, confidential information, data leakage, intellectual property, bias, security, over-reliance, and inadequate human oversight.
6. Executive Case Study: Designing a responsible Generative AI and AI assistant programme to improve executive productivity, organisational knowledge management, reporting, and service delivery.
1. Applying AI in finance, budgeting, forecasting, fraud detection, auditing, procurement, supply chain management, operations, and enterprise risk management.
2. Using AI in human resource management, talent acquisition, workforce planning, employee development, skills analysis, organisational learning, and performance management.
3. Applying Artificial Intelligence in marketing, sales, customer segmentation, customer experience, communication, service delivery, market intelligence, and stakeholder engagement.
4. Exploring predictive analytics, intelligent automation, business intelligence, AI-powered dashboards, forecasting systems, decision-support systems, and process optimisation.
5. Integrating AI with enterprise digital transformation, cloud technologies, data platforms, Internet of Things, business systems, automation technologies, and organisational innovation programmes.
6. Executive Case Study: Developing an enterprise-wide AI transformation portfolio that balances quick productivity gains with long-term strategic transformation.
1. Understanding responsible AI principles including fairness, accountability, transparency, explainability, privacy, safety, reliability, human oversight, and ethical technology use.
2. Establishing executive AI governance structures covering leadership accountability, policies, approval processes, risk classification, monitoring, reporting, and oversight responsibilities.
3. Managing AI-related cybersecurity, privacy, confidential information, data protection, third-party technology risks, intellectual property, regulatory requirements, and compliance considerations.
4. Understanding algorithmic bias, inaccurate outputs, model limitations, AI hallucinations, discrimination risks, reputational risks, operational risks, and unintended organisational consequences.
5. Developing organisational AI policies, acceptable-use standards, risk management procedures, vendor governance, incident management processes, and responsible AI controls.
6. Executive Case Study: Responding to an organisational AI governance incident involving inaccurate AI-generated information, confidential data, reputational risk, and executive accountability.
1. Assessing organisational AI readiness across leadership, strategy, data, technology, people, processes, governance, culture, cybersecurity, and change management capabilities.
2. Leading AI-enabled organisational change through executive sponsorship, stakeholder engagement, communication, workforce participation, skills development, and resistance management.
3. Developing AI talent and workforce strategies covering AI literacy, reskilling, upskilling, human-AI collaboration, new roles, leadership competencies, and future workforce requirements.
4. Evaluating AI technology vendors, platforms, implementation partners, cloud services, procurement options, build-versus-buy decisions, contracts, scalability, integration, and total cost considerations.
5. Establishing AI performance indicators and measuring business value, productivity, adoption, service quality, innovation, risk, return on investment, and continuous improvement.
6. Executive Case Study and Capstone Exercise: Developing and presenting an executive AI strategy, governance framework, implementation roadmap, priority use cases, performance measures, and 90-day organisational action plan.
1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, flight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
14. Website: Visit our website at www.fdc-k.org for more information.