Richard Foster-Fletcher is an experienced speaker, consultant and independent AI researcher. As founder and Chair of MAKI, an independent AI research organization, he examines what artificial intelligence does to organization and how it changes the institutional architecture for judgement, governance, reporting and senior decision-making. He is a LinkedIn Top Voice and was ranked by Favikon as one of the Top 20 AI researchers in the UK. He is based in Milton Keynes, UK.

• Chapter - 00: Introduction;Section - ONE: What happens when AI is treated like software;Chapter - 01: What AI was supposed to be – how the corporate AI promise became smaller as the technology became stronger;Chapter - 02: The enterprise playbook and why it fails with AI;Chapter - 03: What the enclosure is – how safety, compliance, audit and retrieval controls narrow AI before it reaches the user;Section - TWO: How intelligence gets subtracted;Chapter - 04: What gets lost – how safer AI output becomes less useful for senior judgement;Chapter - 05: When AI is only the interface – why useful enterprise tools can fall short of the intelligence claim;Chapter - 06: When AI becomes mandatory – how performance expectations attach to tools whose real capability remain unclear;Section - THREE: Beyond the approved tool;Chapter - 07: The distant frontier and the single-model trap – how leaders can whether approved AI is delivering;Chapter - 08: Where the routes lead – how the institution’s own architecture decides which paths to AI capability open and which close;Chapter - 09: The shifting ground – why the conditions that made the current configuration work are changing, and what the institution that moves now can do about it;Chapter - 10: Conclusion

Richard Foster-Fletcher is an experienced speaker, consultant and independent AI researcher. As founder and Chair of MAKI, an independent AI research organization, he examines what artificial intelligence does to organization and how it changes the institutional architecture for judgement, governance, reporting and senior decision-making. He is a LinkedIn Top Voice and was ranked by Favikon as one of the Top 20 AI researchers in the UK. He is based in Milton Keynes, UK.

• Chapter - 00: Introduction;Section - ONE: What happens when AI is treated like software;Chapter - 01: What AI was supposed to be – how the corporate AI promise became smaller as the technology became stronger;Chapter - 02: The enterprise playbook and why it fails with AI;Chapter - 03: What the enclosure is – how safety, compliance, audit and retrieval controls narrow AI before it reaches the user;Section - TWO: How intelligence gets subtracted;Chapter - 04: What gets lost – how safer AI output becomes less useful for senior judgement;Chapter - 05: When AI is only the interface – why useful enterprise tools can fall short of the intelligence claim;Chapter - 06: When AI becomes mandatory – how performance expectations attach to tools whose real capability remain unclear;Section - THREE: Beyond the approved tool;Chapter - 07: The distant frontier and the single-model trap – how leaders can whether approved AI is delivering;Chapter - 08: Where the routes lead – how the institution’s own architecture decides which paths to AI capability open and which close;Chapter - 09: The shifting ground – why the conditions that made the current configuration work are changing, and what the institution that moves now can do about it;Chapter - 10: Conclusion

Richard Foster-Fletcher is an experienced speaker, consultant and independent AI researcher. As founder and Chair of MAKI, an independent AI research organization, he examines what artificial intelligence does to organization and how it changes the institutional architecture for judgement, governance, reporting and senior decision-making. He is a LinkedIn Top Voice and was ranked by Favikon as one of the Top 20 AI researchers in the UK. He is based in Milton Keynes, UK.

• Chapter - 00: Introduction;Section - ONE: What happens when AI is treated like software;Chapter - 01: What AI was supposed to be – how the corporate AI promise became smaller as the technology became stronger;Chapter - 02: The enterprise playbook and why it fails with AI;Chapter - 03: What the enclosure is – how safety, compliance, audit and retrieval controls narrow AI before it reaches the user;Section - TWO: How intelligence gets subtracted;Chapter - 04: What gets lost – how safer AI output becomes less useful for senior judgement;Chapter - 05: When AI is only the interface – why useful enterprise tools can fall short of the intelligence claim;Chapter - 06: When AI becomes mandatory – how performance expectations attach to tools whose real capability remain unclear;Section - THREE: Beyond the approved tool;Chapter - 07: The distant frontier and the single-model trap – how leaders can whether approved AI is delivering;Chapter - 08: Where the routes lead – how the institution’s own architecture decides which paths to AI capability open and which close;Chapter - 09: The shifting ground – why the conditions that made the current configuration work are changing, and what the institution that moves now can do about it;Chapter - 10: Conclusion