How AI mature is your organization? And what are the implications of it?

The last two years have been extremely stressful for anyone working in tech. There’s been a consistent sense that we all need to do more with less. That our jobs are on the line. And now AI is being touted as the cheat code that will unlock productivity and profit gains.

In our latest podcast, Peter Merholz (add him on LinkedIn) doesn’t see AI helping much in the short-term because teams are too over-tasked to believe they have the time to try new models of working. He also believes that most organizations don’t have cultures and leadership that promote experimentation and reward learning.

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What makes matters worse is that simply “using AI” won’t get you the results you need. Simply using ChatGPT or Claude will not give you and your business a significant boost because data is at the heart of AI. The more of your first-party data that you train models on and the more that you craft agents around specific workflows, the closer you’ll get to what AI acolytes are selling.

Accenture calls this AI maturity: Advancing from practice to performance. And this is where Peter Merholz believes that most orgs will be blocked. His experience working in mega-corps has found that most aren’t learning cultures. Introducing new tools, mental models, and ways of working aren’t well-received.

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Valuable lessons

💡 Nearly half of workers are uncomfortable admitting to their manager that they used AI for common workplace tasks

💡 Evaluations —or “Evals”— are the backbone for creating production-ready GenAI applications.

💡 Ten lessons that separate impactful training from mere AI showcases

💡 Even teams actively working with AI are wrestling with fundamental knowledge structuring challenges. The tools are advancing faster than our practices

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