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Implementing AI in operations is not a technological problem; it is a process problem. Many initiatives fail not because of a lack of models or tools, but because business metrics have not been agreed upon, information systems have been poorly analyzed, or data is not available when it is needed.
In this talk, we review the practical framework that structures any successful operational AI project: from alignment with the end user to technology selection, including data governance and communication between business and IT. A straightforward perspective, without marketing hype, for teams that want to move from proof of concept to real impact.

Programa

1.Introduction – Where most AI projects fail
2. Context – The current state of AI in operations: where we are and where we are heading
3. Practical framework – The 6 keys to successfully implementing AI
4. Review of real-world cases
5. Conclusions
6. Q&A

In collaboration with:

Taught by:

Martí Palou
Martí Palou Vidal
Director at Infini

Director with more than 10 years of experience, the last 5 of which have been spent leading AI implementation and process automation projects at Infini. Prior to Infini, he worked in KPMG’s Strategy department on strategy and operational transformation projects. Educated at ESADE and IESE, he combines a strong business perspective with technical execution capabilities. At Infini, together with a team of more than 20 professionals, they deliver over 50 automation and AI projects each year across sectors such as healthcare, education, and retail.

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