The AI Performance Triangle: Why Every Company’s Results Look Different
Understanding the Quality-Speed-Cost trade-offs that make AI “success” impossible to standardise.
Understanding the Quality-Speed-Cost trade-offs that make AI “success” impossible to standardise.
You pointed your AI at SharePoint and now it’s confidently wrong. Why? Because you don’t have a knowledge base. You have a filing cabinet. And until you understand the difference between a document repository and a KMS, your AI project is retrieving the wrong things, faster, at scale, with confidence.
I attended a Genesys partner conference recently. The presentation deck and speakers were impressive. They talked about their platform evolution, moving beyond CCaaS to become a full orchestration platform. They dropped every AI buzzword: A2A (agent-to-agent), MCP (Model Context Protocol), agentic workflows, AI Agents, multi-modal AI experiences. Then they shared some real-world use cases. Transcription…
Why AI adoption has nothing to do with access, and everything to do with the one experience that changes everything.
Six weeks from assessment to working AI pilot. Not perfect. Working.
Your AI pilot is probably going to stall or fail. Not because the technology doesn’t work. Not because your team isn’t capable. But because you chose 50 SME power users as your pilot group. Here’s what actually happens: The fix is counterintuitive: Pilot with your typical mainstream users. The ones asking the same 20 questions…