
Welcome to this Cloud Wars Agent and Copilot minute. In these discussions, I’ll be analyzing opportunities, impact, and outcomes possible with AI. Today, I address the shift in AI focus from experimentation to achieving consistency and stability in production deployments and the cost implications of that shift.
Highlights
0:15 — As customers and partners look to move AI into production, it becomes clear that the costs of AI extend beyond licenses to API calls, data storage, security controls, and actual usage.
2:16 — The key question is: At what level of usage can the organization reliably forecast costs? Costs include licenses, API calls, tokens, computing capacity, data storage, and usage levels.
3:55 — The cost of the model itself may be smaller than the surrounding application, data, identity, permission, monitoring, and security infrastructure. This is where human beings and experts with experience become very important.
4:24 — If you need data that’s accessible, it needs to be governed. If you need identity and permission, it needs to be governed. Every security expert in the channel I’ve spoken to has said they’re kind of shocked that people aren’t asking some of these questions. Customers and partners must consider how usage will change the bill if adoption expands across the organization. It’s no longer a change management question but it’s also a financial question and one we should all be asking.
More of my AI insights:
- Amid Rapidly Expanding AI Usage, Policies Are Key To Maintaining Customer Trust
- Microsoft Partners Must Address Buyers’ Specific Business Problems
- 3 Ways Microsoft Partners Can Address Growing AI Backlash
- AI’s Impact on the Customer Journey Drives Need for Deep, Differentiated Content
- Leaders Require Cognitive Capacity to Unlock Transformative Power of AI

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