UpTrajectory Review

Zeus Kerravala's piece on SiliconANGLE zeroes in on a pattern most small-business owners will recognize from their own operations: everyone has jumped on AI for customer experience, but almost nobody can point to a result. The article draws on a Talkdesk-NewtonX survey of 252 director-level and above leaders across customer experience, IT, operations, and AI strategy at midmarket and enterprise organizations in four regions. Kerravala's core argument is that the bottleneck has shifted. Getting AI tools deployed is no longer the challenge. The hard part is orchestrating them, meaning getting multiple AI systems, human agents, and workflow logic to function as one coherent experience rather than as a pile of disconnected pilots.

For a small-business operator, this framing matters because it mirrors what happens when you adopt point solutions one at a time. You add a chatbot here, a sentiment-analysis tool there, maybe an AI-assisted knowledge base, and suddenly your customer experience stack is a patchwork. Kerravala's point, applied to a smaller scale, is that the value of AI in customer experience is not in any single tool but in how the whole system routes, escalates, and hands off between automated and human touchpoints. If you are running lean, a bot that cannot seamlessly transfer context to a human agent is not saving you time. It is creating a second problem your team has to clean up.

What is genuinely useful here is the reframing of the problem as orchestration rather than adoption. That is a more honest diagnosis than most vendor marketing allows, and it aligns with what many operators have experienced firsthand: the technology works, but the workflow around it does not. We are somewhat skeptical of drawing broad conclusions from a single vendor-commissioned survey, since Talkdesk has a direct commercial interest in selling orchestration platforms. Still, the finding that leaders can describe their AI deployments but not their outcomes rings true regardless of who funded the research. The gap between activity and result is real and worth taking seriously.

The second-order effect worth watching is how this reshapes vendor conversations and internal budgeting. If orchestration is the real constraint, then businesses that spent heavily on standalone AI tools may find themselves needing to invest again in integration layers, process redesign, or staff training to make those tools actually pay off. For smaller operators without dedicated IT teams, this could mean leaning more heavily on platforms that bundle orchestration natively rather than assembling a best-of-breed stack. It also raises the bar for what you should demand from any AI vendor: not a demo of the tool in isolation, but a clear picture of how it fits into your existing customer journey without creating new seams.

The practical move is to audit your current AI touchpoints before adding anything new. Map where a customer interacts with automation, where a human steps in, and whether context travels cleanly between those moments. If the handoffs are broken, that is your orchestration problem, and no additional tool will fix it. Watch how the larger market responds to this framing over the next year, because if orchestration becomes the dominant narrative, vendors will start competing on integration depth rather than feature lists, which should eventually benefit buyers at every size.

“Every information technology leader I talk to has an artificial intelligence story about customer experience. Almost none has an outcome story.” — SiliconAngle

Takeaway: Audit your AI customer touchpoints for broken handoffs before buying anything new; orchestration, not adoption, is where the real payoff lives.