Front pagesponsored · Intermedia
Productivity AI6h · 13:31 GMT · 6 min read
What AI in Communications Looks Like for Your Business
Every mid-market business is being told it needs an AI strategy. But the question that matters isn’t what AI can do – it’s what AI can do for a business like yours, operating in your sector, with the specific workflows and customer interactions you recognise
For most mid-market businesses, the challenge isn’t deciding whether AI has a role to play. It’s identifying where it can make a meaningful difference – and how to put it to work.
The challenge with AI as it’s typically presented is that it’s almost always framed as a horizontal capability. Something that improves everything at once. Rob Oscanyan, VP of Product Marketing atIntermedia, sees this problem constantly.
“When we say it can improve everything at once, I think it’s just a really broad term,” he says. “You can’t necessarily say it’s going to do everything for you. We’ve had partners, customers come to us and say, ‘Hey, I need some AI,’ and we’re like, ‘Okay, what are you trying to do?’ And they say, ‘I don’t know. I just know I need it.'”
But broad promises don’t help a practice manager at an optometry group, a service coordinator at an automotive dealership, or an operations lead at a professional services firm solve the challenges in front of them. The businesses getting the most traction with AI in communications aren’t the ones chasing the broadest possible implementation. They’re the ones identifying a specific operational problem, deploying AI to solve it, and measuring what changes.
Oscanyan is clear on what good implementation looks like.
“You should create a specific use case where there’s one AI assistant assigned to every single queue that handles a specific topic,” he says. “That way, you ensure that there’s very little drift.”
Here’s what that looks like across three sectors.
Healthcare: Front Desk Consistency and After-Hours Cover
For healthcare practices – whether that’s a multi-location optometry group, a dental practice, or a specialist clinic – the communications challenge is often the same: front office staff are fielding a high volume of repetitive, time-sensitive calls while simultaneously trying to deliver a consistent patient experience regardless of who picks up the phone.
AI is being deployed here in two distinct ways.
The first is as an AI assistant working alongside employees in real time. When a patient calls asking about insurance coverage, copayment requirements, or what to bring to an appointment, the AI assistant can help employees quickly retrieve information during the call from the practice’s own business-specific knowledge base – allowing them to respond confidently without putting the caller on hold. Oscanyan points to a large optometry practice running multiple locations as a telling example.
“They’re hiring front office folks all the time,” he says. “They get calls in from potential patients who ask questions about insurance coverage and copayments, preparation for the appointment, what they need to bring.”
“That AI assistant is able to listen in on the conversation and, when that employee needs information, with a click of a button it can dive into their own personal knowledge database and provide that employee with the right answer for that patient.”
The second is as an AI receptionist handling overflow and after-hours calls. Oscanyan describes an oncology group that made a deliberate decision to keep human staff answering calls wherever possible. “They said that look, they need to have a human being answering those calls,” he says. “But we recognise that there are times when there are spikes in call volume, so we want that AI to be a fallback, an overflow.”
For a patient calling an oncology clinic, reaching voicemail or waiting for a callback can add unnecessary frustration to an already stressful situation. An AI receptionist can help by answering approved business questions, capturing caller intent, and routing calls appropriately when staff are unavailable – helping the practice remain responsive even during its busiest periods.
Automotive: Scheduling That Understands the Business
In automotive – whether it’s a dealership group or an independent service centre – the communications workload is significant and the margin for error is low. Customers calling to book a service need to know the right technician is available for the job. Customers enquiring about a vehicle need to know whether the specific model they want is at the right location.
Oscanyan spells out what that requires in practice. “With automotive, it’s do you have the right mechanics involved for scheduling a repair service? Or if it’s a sales conversation and you’re scheduling time to go see and test drive a vehicle, that there are the actual vehicles at the right location – especially if they have multiple locations.”
An AI agent handling inbound scheduling calls needs access to the right business information – from technician availability and vehicle inventory by location to appointment slots by service category. Without that context, AI can do little more than take a message. With it, AI can route callers accurately, provide relevant information, and help move the booking process forward – or complete the booking when the appropriate integrations are in place.
Professional Services: Turning the Trade-Off Around
Mid-market professional services businesses – accountants, law firms, consultancies – have historically faced a familiar trade-off. Oscanyan frames it plainly. “Most businesses want to achieve three things,” he says. “They want to grow more, or sell more, or serve more. They want to stand out – to deliver a really unique experience to their customer to keep them coming back. And third, they want to do this while being mindful of their budget. But oftentimes those came at odds with each other. There was always this ‘or’ conversation – I could either do this or this, but I can never do three at once.”
AI in communications is shifting that calculation. “What businesses are seeing, especially with AI, is that you can actually achieve all three,” says Oscanyan. “Now I don’t have to have a compromise between these three outcomes.” An AI assistant can help client-facing staff respond and more consistently. An AI receptionist can handle routine inquiries, freeing experienced staff to focus on work that requires their expertise. Businesses can serve more customers, deliver a better experience, and make better use of their resources. The ‘or’ conversation becomes an ‘and’ conversation.
Start With the Problem, Not the Technology
Across industries, the businesses making the most of AI in communications share a common approach: they’re not starting with a broad mandate to adopt AI, they’re starting with a specific challenge – missed calls, repetitive questions, scheduling bottlenecks, or employees spending too much time searching for information.
From there, the focus shifts to what matters: improving responsiveness, creating better experiences, giving employees more time for meaningful work, and measuring the results.
The question isn’t simply, “what can AI do?” It’s “what is AI doing for my business, my employees, and my customers.”
That’s where AI stops being a technology initiative and starts delivering real business value.
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