The industry has moved decisively past AI proof-of-concept. Eighteen months ago, vendor conversations centred on isolated pilots—chatbots, agent assist, point solutions. Today, those same conversations have shifted to operational integration: how AI fits into end-to-end workflows, who owns accountability when automation fails, and critically, how much this actually costs. Levelpath's survey of enterprise software buyers reveals the governance gap has caught procurement teams off guard, with 57% experiencing AI spending overruns in the past six months. The pattern is consistent: invoices arriving higher than budgeted, teams hitting usage caps, and organisations redirecting funds from other priorities to cover unexpected costs. This isn't a procurement problem alone—it's a CX problem, because the same governance questions that plague procurement leaders will surface in your contact centre operations.
What's revealing is how organisations are responding. Rather than imposing hard spending caps, buyers are negotiating for transparency: 32% demanded detailed usage reporting versus only 16% implementing spending limits. Thirty-nine percent added exit clauses to contracts, and 36% shortened terms. These moves signal deep uncertainty about vendor lock-in and pricing stability in an immature market. For CX teams already running Agentforce, Zendesk's AI suite, or similar platforms, this creates immediate pressure. You need visibility into how your AI is performing against cost, which workflows it's actually completing versus creating rework, and whether your vendor's pricing model will remain predictable. NiCE's observation that leading customers have moved toward orchestration—linking customer intent, workflows, and resolution in a single system—underscores the real work ahead. Fabletics didn't deploy AI to add a chatbot; they deployed it to authenticate customers, manage orders, and resolve issues without handoffs. That requires process redesign, not just technology implementation.
The implication is stark: your pilot's success proves nothing about operational viability. The harder work—building governance, defining accountability, measuring outcomes, and managing costs—happens after the contract is signed. Support team leads and CX consultants must treat AI deployment as a process transformation, not a technology insertion. This means auditing your existing workflows before implementation, establishing clear ownership of AI-driven decisions, and building cost visibility into your operational metrics from day one. The organisations getting this right aren't those with the most advanced AI; they're those treating the pilot as a proof of concept for the operating model itself.
AI pilots are done. Now, the focus is on processes and pricing. No Jitter