01
AI strategy, industry dynamics and competitive positioning
Executive management pathway
EMBA Applied AI
Lead AI transformation with boardroom confidence. Select the right AI opportunities, allocate resources, manage risk and turn innovation into performance.
- Duration
- 12 months, part-time executive mode
- Focus
- Enterprise-wide AI transformation
- Final output
- Investment-backed AI roadmap
- Pilot
- Not required
With The Thames International University, Paris, France.
Overview
About the programme
The EMBA (Applied AI) combines management disciplines with the strategic use of AI. It is intended for leaders who make investment, operational and people decisions, govern adoption across functions and turn promising use cases into practical enterprise programmes.
Who should enrol
Senior managers, department heads, business owners, public-sector executives, finance and operations leaders, transformation directors and experienced professionals preparing for broader management responsibility. Indicative profile: a bachelor’s qualification or recognised equivalent plus relevant managerial or professional experience.
Study journey
Indicative 12 months journey
Months 1–3
Understand
Applied AI literacy, industry cases, competitive strategy and leadership.
Months 4–6
Integrate
Finance, operations, data, workforce redesign and operating models.
Months 7–9
Govern
AI governance, change management, implementation risk and benefits tracking.
Months 10–12
Recommend
Capstone: enterprise AI strategy, investment case and delivery roadmap.
Six leadership capabilities
Six leadership capabilities
02
AI-enabled financial analysis, investment and value creation
03
Operations, customer experience and new business models
04
Leadership, change management and workforce transition
05
Governance, cybersecurity, ethical use and oversight
06
Executive communication and AI transformation roadmap
Curriculum
Detailed coverage
- 01
AI for leaders & decision-makers
AI foundations, practical tool fluency, generative and predictive AI, strengths, limitations and evaluation.
- 02
Strategy, competition & foresight
Market shifts, industry disruption, portfolio prioritisation and value-pool analysis.
- 03
Finance, ROI & capital allocation
Cost-to-serve, productivity economics, business cases, payback, NPV, risk and budgeting.
- 04
Data-led management & operations
Metrics, dashboards, supply chain, customer processes, operating-model redesign and controls.
- 05
Innovation & business models
Customer discovery, design thinking, service innovation, subscriptions and AI-enhanced offerings.
- 06
Organisational change & talent
Workforce adoption, capability planning, leadership communication and redesign of roles.
- 07
Responsible AI & cyber risk
Privacy, security, bias, model procurement, third-party diligence, human accountability and policy.
- 08
Executive transformation capstone
Transformation thesis, ranked use cases, investment case, roadmap, KPIs and board presentation.
Evidence of learning
What you submit and take forward
- Case analysis
- Financial and operational assignment
- Functional AI implementation plan
- Final executive capstone
A board-ready AI transformation plan covering strategic priorities, investment logic, operating impact, risk controls, milestones and measurable outcomes.
Award title, credit value, admission requirements and recognition are confirmed by the awarding institution.
Talk to CEAI
Enquire about EMBA (Applied AI)
Ask about entry requirements, the next intake and fees.