The 5-10-85 Reality of Enterprise AI
The Cloudcast
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Aaron invites listener feedback, shares contact info, and closes the episode with final thanks and show details.
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Three years since the launch of ChatGPT, what does the landscape of Enterprise AI look like today? What’s working, what’s struggling and what’s still unknown?
SHOW: 966
SHOW TRANSCRIPT: The Cloudcast #966 Transcript
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SHOW NOTES:
HOW ARE ENTERPRISES USING AI IN LATE 2025?
- 5% have a clear vision of how to apply Predictive and Generative AI to a set of use-cases that drive differentiation, productivity improvements and cost reductions. They are keeping the details close to the vest.
- 10% have allocated about 3-5% of their IT budgets to AI, typically from a C-level mandate, and have given it to Microsoft or Google. They have checked “the business is AI-enabled” and signaled to the market that they have fully embraced AI. The market is rewarding these companies at higher multiples.
- 85% aren’t sure what use-cases to focus on, have unrealistic expectations during POCs, and are focused on the “no” areas instead of their own learning curves.
- Enterprises don’t have great visibility into AI costs, and limited baselines of what AI should cost - pay for outcomes, pay for seats, pay for tokens, or pay for GPUs?
- Enterprises don’t have easy access to GPUs outside of via SaaS services - makes it challenging for Private or Sovereign AI demand to be met
- Right now, there is no simple way for Enterprises to build AI Agents
- Right now, there is no simple way for Enterprises to share AI experience / learning curve - AI is a very individualized experience
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