What does it actually take to make AI work inside the enterprise? I recently sat down with Philip Miller from Progress to talk about the challenges companies are facing as they move AI from experiments into real production environments. We talked about Progress Data Platform, PDP Studio, context layers, AI guardrails, data governance, AI agents, cost optimization and what enterprises need to build AI they can actually trust.
We also discussed a real-world use case where report-writing time was reduced from around 90 minutes to just minutes.
One thing that stood out to me:
AI is not just about the model.
The data, context, governance and infrastructure around the model matter just as much.
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