Upcoming Sessions
Session starting on
Location
Fontainebleau
Duration
5 days
Fees
€
11,600
Content Overview
AI for Business uses video case studies, cutting-edge technologies and vibrant debate to illustrate how established companies can use strategy, leadership and innovation to adapt to digital transformation.
What can AI do for your industry
Participants will be given a thorough, non-technical introduction to different kinds of AI.
Topics covered include:
- From perception (traditional statistics) to prediction (machine learning)
- The key idea: How machines (algorithms) learn from experience (data)
- Applications across functional areas (marketing, finance, operations and HR/organisational development)
- Using AI to create: LLM’s, ChatGPT and generative AI
- The strategic disruption that AI is bringing to various industries
- The fundamental question for the design of tomorrow’s organisations: what should humans keep doing even when machines can do it better?
- What (if anything) will tomorrow’s managers do?
- From predictive AI to generative AI → and now to agentic AI: moving from systems that inform decisions to systems that can act within workflows
Getting the most out of your in-house AI experts
- Equip yourself with the skills to engage in a rigorous conversation with data scientists, be it your direct reports, or from a centralised pool of talent
- Improve your ability to communicate business needs and apply the insights generated
- What agent orchestration skills look like, and why they might remain important even as models become more competent
- A shift from model-level to system-level thinking: the model is just one component; real value comes from integrating data (RAG), tools, memory, and orchestration into end-to-end systems
Next practice: AI Adoption, governance and risks
- Discuss some of the logistical, legal and ethical challenges associated with deploying AI in management
- Discover some of the core weaknesses of machine learning-based decision-making (e.g., using past data to derive insights for future use)
- Learn how to conduct randomisation-based pilot testing, also known as A/B testing or randomised control trials (RCT) – essential before committing to major changes in management practices.
- Study innovative applications that use machine intelligence either directly or indirectly, such as using computer models to forecast how a management intervention will unfold
- Three perspectives on human capital in the age of AI: policy maker, employer and employee
- How to evaluate AI systems beyond accuracy, incorporating dimensions such as trust, compliance, and alignment with company values
- What are the next impactful innovations in AI?
- How to develop and implement your AI strategy
- What are the key challenges organisations face when adopting AI?
- What are some key business questions to ask about AI?
Practical application and building AI systems
- What it takes to build a real AI product (not just a demo): introducing components such as RAG, multi-agent architectures, memory, guardrails, and human escalation
- A hands-on agent-building workshop, where participants design and evaluate their own AI systems.
