Part two of a two-part series. Part one covers why your AI architecture may not be fit for regulated environments. I spoke a client a few months ago. A legal dispute had landed, pretty standard for a regulated contact centre, a customer claiming an agent had given them incorrect information. The legal team’s request was…
The risk isn’t that enterprise AI search tools don’t work. It’s that they work exactly as designed, for knowledge workers, not contact centres. When you use discovery infrastructure to do governance work, the permissions get respected. The governance does not.
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.
What my grandfather’s pickaxe, COVID restaurant pivots, and a teenager’s dismissal taught me about every technological shift, and why this one has a shorter timeline.
Why both vendors and buyers underestimate complexity, and how to navigate out.
Six weeks from assessment to working AI pilot. Not perfect. Working.
What my empty dashboard taught me about shared understanding.
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…
Why the invisible infrastructure nobody wants to build is still the foundation of success.