Pressure to adopt AI isn't coming from one source. It's coming from boards, competitors, customers who have already experienced AI-powered service elsewhere, and employees who increasingly expect AI to make their work easier. But pressure and clarity are two different things. For many mid-market organisations, the reality is that they're navigating a landscape that's moving faster than their ability to evaluate it thoughtfully. The risk of moving too quickly is real. So is the cost of waiting too long. Mark Sher, SVP of Product Marketing at Intermedia, sees this tension every day. His view is that AI adoption in business communications isn't happening all at once. Organisations are moving at different speeds and for different reasons. "Some say, 'I've got to have it right now. I don't care,'" he says.
"Others are more pragmatic - they want to understand the ROI, they want to understand what they're going to get in return. And there are others still crossing their arms and saying, 'I'm not ready.'"
The pragmatists, Sher believes, are asking the right questions. The organisations seeing the strongest early results are typically those that begin with practical, well-defined use cases before expanding into more advanced automation.
Not All AI Is the Same – and the Distinction Matters
One of the most useful frameworks Sher offers is a simple distinction between two types of AI. Understanding the difference, he says, helps organisations avoid many of the pitfalls that accompany early AI adoption. The first category is what he describes as out-of-the-box AI - technology that delivers value almost immediately with little configuration or training. Meeting transcription is a good example. The meeting ends, a summary is generated, action items are captured and a record is immediately available. These capabilities require minimal setup, produce immediate productivity gains and are among the lowest-risk, highest-return AI capabilities organisations can adopt. Call summaries follow the same pattern. In a contact centre, an agent finishes an interaction and AI automatically summarises the conversation and updates the CRM. "I don't think there's a ton of risk with that," says Sher. "And there's a lot of upside - around productivity, efficiency, a better employee experience and a better experience for the customer." The second category is knowledge-dependent AI - and this is where both the opportunity and the complexity increase. An AI voice agent that can answer calls, hold natural conversations, schedule appointments and intelligently route enquiries is a compelling capability. Its effectiveness, however, depends entirely on the quality of the information it's given. "To make that work right, you have to invest in infusing it with the right kind of business data," says Sher.
