Familiarisation with AI and digital innovation in practice, hands-on exploration of AI/LLM tools, ideation workshops around business cases, and awareness of environmental impact
This course lays down the fundamentals of AI: ethics, data governance, prompting and intelligent agents. It helps you identify the most relevant use cases and translate them into new operating models that distinguish work of high human value from processes that can be automated.
Familiarise teams with AI in practice, to improve how they perform.
Get hands-on with AI/LLM tools and set the boundaries for their use.
Identify and prioritise the business use cases that matter most.
Raise awareness of impacts, ethics and the environmental footprint of digital.
An overview of AI (ML, deep learning, generative AI) and its current limits. AI maturity assessment. Mapping use cases by business line. Prioritising by impact × feasibility × risk.
Workshop: problem → AI opportunity → assumptions. Decision matrix & Go/No-Go criteria. User-journey storyboards.
Responsible prompting & reusable patterns. Automation (no/low-code). Rapid prototype & test protocol.
Risks, bias, security & compliance. Frugal usage and responsible technical choices.
A 30–60–90 day roadmap: responsibilities, success criteria, scaling up.
Familiarise business teams with generative AI through concrete cases.
Define a usage charter and its guardrails (security, compliance, ethics).
Frame an AI proof of concept ready to measure impact and value.
Standardise rituals & indicators to industrialise two or three proofs of concept.
This course helps you prioritise, govern and equip AI initiatives that improve operational performance and human value.
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