AI is already part of everyday work in every organization: generative AI is within reach of every employee, and agentic solutions handle entire workflows. Yet in most organizations AI work is scattered across individual pilots and enthusiastic experiments that nobody connects back to business goals.

Strategy work too often produces a list of technologies, or a document with no owner and no effect on daily work.

This webinar turns the perspective around: a good data and AI strategy is above all about making choices. It says where the organization points its skills, its time and its investments — what gets done first, what comes later, and what is not done yet.

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AI creates business value only once individual use cases are prioritized, connected to core processes, and steered as a portfolio within normal decision-making.

Participants get a clear overall picture of what machine learning, generative AI and agentic AI mean from a business point of view, why so many data strategies end up without impact, and what an operating model looks like when AI ideas are collected, prioritized and delivered in a managed way. The session includes a concrete customer example of how dozens of needs and opportunities were turned into a prioritized portfolio and a data governance model.

Agenda

Where we stand: what AI is today — machine learning, generative AI and agentic AI through a business lens
Why so many data and AI strategies fail to land — the most common pitfalls
Strategy as choices: from use cases to a prioritized AI portfolio and value paths
The governance model in brief: roles, responsibilities and the decision rhythm that connect strategy to management
Customer example: how dozens of needs became a prioritized portfolio
First steps in your own organization
Q&A: questions from participants
Closing: an introduction to the Datastrategia tekoälyaikaan training day for those who want to go deeper