The next phase of AI in unified communications will not be won by the flashiest demo. It will be won by tools that remove work, extend service coverage, and prove value before users lose patience.
Speaking to UC Today at UCX Manchester, Philippe du Fou, EMEA Sales Director at Intermedia, described a market that has moved into a more practical phase. Buyers still want better engagement and faster service. But the sharper question now is not whether AI can impress in a demo. It is whether AI can absorb the low-value work teams no longer have capacity to handle.
“People don’t like technology for the sake of it. They’re scared of change. Our job is to show the art of the possible and give them some new ideas to make life easier.”
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AI in UC Is Entering a Practical Operations Phase
That is the useful takeaway for UC Today readers. In 2026, AI inside unified communications is becoming less about novelty and more about operational coverage. Teams want real-time help during calls, quicker access to answers, and support when staff are stretched. They also want communications tools that keep working after 5pm, when customers still expect a response.
For many organisations, the pressure point is not whether AI exists. It is whether AI can reduce workload without making the workflow more complicated. In that sense, AI in UC is increasingly an operations question as much as a product question.
The 24/7 Gap Is Becoming a Bigger Buyer Problem
Du Fou pointed to a simple but important shift in behaviour: customers now expect immediate answers, even when human staff are unavailable. That creates a wider gap between office-hours service models and digital expectations.
“These days people are more digital. They’ll go online later on, they expect an immediate answer. This is why our AI receptionist can help.”
That makes tools like Intermedia’s AI Agent Receptionist more strategically relevant than they might first appear. For buyers, the point is not just call handling. It is whether AI can extend service coverage, schedule appointments, answer routine questions, and reduce the amount of demand that still lands on human teams the next morning.
A simple scenario makes the value clearer. A small service team may not have staff available overnight, but customers still call, ask routine questions, and request appointments. An AI receptionist that handles basic queries, books callbacks, and flags urgent issues before the team arrives can remove real work rather than just add another tool to manage.
ROI Comes from Workflow Relief, Not AI Branding
Du Fou was also direct on the ROI question. In his view, the industry has already crossed the point where AI needs to prove it can help in principle. The harder task now is linking AI to time savings, workflow support, and visible business outcomes.
“AI needs to be less about the technology, but more about how you deploy it, how you make it easy. If it’s not easy to deploy and to use, nobody’s going to use it.”
That is where his examples became more concrete: live sentiment visibility for supervisors, real-time guidance for agents, and knowledge surfaced during the interaction rather than after it. Intermedia’s AI Supervisor Assist and broader Intermedia AI portfolio reflect that thinking. The value is not the model itself. It is whether a busy supervisor can spot a negative call early, or whether an agent can get the right answer without putting the customer on hold.
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