Front pagesponsored · Intermedia
Productivity AI8h · 13:31 GMT · 5 min read
Why Your AI Strategy Needs a Partner Who Knows Your Industry
For many mid-market businesses, adopting AI isn’t simply a technology decision. It’s a question of knowing where to start, which solutions make sense, and how to turn an investment into measurable results. That’s where the right technology partner can make all the difference
Most mid-market businesses don’t have a dedicated AI team. They don’t have the internal resources to evaluate every platform, run a proof of concept, and manage a deployment. What they have is a technology partner – and increasingly, the quality of that partner relationship determines whether an AI investment delivers or disappoints.
Rob Oscanyan, VP of Product Marketing atIntermedia, has watched this play out across the market. “There’s certainly interest in AI,” he says. “But there’s a large group that, while they’re hesitant, they’ve heard the value of it and are now looking for practical applications.”
“There’s a lot of ambition there, and that ambition needs to meet somebody who can guide them through it.”
For businesses navigating AI adoption, the right technology partner can help turn that ambition into action. Here’s what to look for.
The First Question Every Good Partner Will Ask You
One of the most common patterns in early AI adoption was a customer telling their partner “I need AI” – and the partner going out and finding something. Oscanyan is direct about the problem with that approach. “When a customer says ‘I need AI,’ you have to ask: what are you trying to do?” he says. “What does the 30-60-90 look like? What are the results that you want?”
Without that conversation, an AI deployment has no clear direction. A good partner will challenge assumptions, help define the desired outcomes, and establish what success looks like before recommending a solution. It’s the difference between deploying technology for its own sake versus solving a real business problem.
Understanding Your Call Flow Matters More Than the AI
AI that isn’t configured to work with how your business handles calls can create a poor experience for your customers. It doesn’t matter how capable the underlying model is – if the AI agent doesn’t understand your call routing rules, escalation triggers, or how different queues should behave, it’s more likely to fall short when it matters most.
Oscanyan draws a direct parallel to what the UC industry has already been through. “We’ve seen this story before,” he says. “Back in the day with communications, people were just going out and buying a patchwork of solutions – a video conferencing solution from here, a chat solution from there. The downsides were more things to manage, communications siloed. We’re seeing the exact same story play out again with AI <a href="https://bitcomme.com/crowdstrike-announces-kill-switch-for-ai-<a href="https://bitcomme.com/boldtrails-streams-app-tells-agents-who-to-call-today/” title=”BoldTrail's Streams App Tells Agents Who to Call Today”>agents-that-go-rogue/” title=”CrowdStrike announces 'kill switch' for AI agents that go rogue”>agents.” A standalone AI solution that operates separately from the core communications platform may not automatically account for existing call routing rules, escalation procedures, or other established workflows.
“When a call needs to be escalated, many standalone solutions just throw it over the fence and say, ‘Well, we’re going to set it to this number and hope everything works out,'” he says.
Oscanyan also makes clear that sector-specific understanding isn’t always about the AI model itself. “It’s more that the partner who’s there to help influence that decision. You really want someone that understands what the business is trying to do, and also has an understanding of their current communication workflow. That’s actually ground zero.”
A partner who understands this will ask about your workflows before recommending anything. How are calls currently handled? What are the edge cases? Where do things break down today? Those answers help ensure AI works with the business’s existing processes rather than introducing new complications.
Deploying AI Is the Easy Part – Measuring It Isn’t
A successful AI strategy doesn’t end at deployment. Businesses also need visibility into how AI is performing and whether it’s delivering the results they expected. Oscanyan is emphatic on this point. “It’s one thing to deploy the AI; it’s another thing to see if it’s actually working,” he says. “Do you have the tools to determine whether it’s being effective?”
Before committing to any AI-powered communications platform, businesses should understand what they can measure. Can they see how many calls AI handles versus those requiring escalation? Can they review transcripts or recaps to assess quality? Can they identify which workflows are performing well and where improvements are needed? These insights help businesses evaluate results, refine their approach, and get more value from their investment. “Can you have some sort of analytics backend that allows us to see how many of these calls are being fully captured?” says Oscanyan. “Are you able to find out how many are getting escalated, and under what queues?”
Without that visibility, businesses are left guessing about what’s working, what isn’t, and where to improve.
Build on a Platform That Will Still Be Here in Three Years
The AI market is moving quickly, and with new solutions entering the market almost daily. For mid-market businesses, that makes the long-term stability of their technology providers an important consideration. The last thing a business wants is to invest in a solution today only to face another costly transition tomorrow. Oscanyan makes the point plainly. “Many of these standalone AI solutions may not be around for a while,” he says.
“We’re here to stay. That’s why we’re taking this to another level – this is going to be embedded within our platform.”
For many mid-market businesses, a more durable strategy is to prioritize AI that’s native to, or deeply integrated with, an established communications platform – backed by a provider committed to ongoing innovation and solutions tailored to the needs of different industries. “Our goal is to continue to work and deliver more verticalized solutions in the future,” says Oscanyan, “that allow businesses to work within an intelligent communications platform – always aligned to the way in which that vertical operates from their workflows.”
The right partner does more than recommend AI technology. They understand how a business operates, help identify where AI can make a meaningful difference, ensure it works with existing communications workflows, and provide the insight needed to measure and improve results.
For mid-market businesses without a dedicated AI team, the partner relationship isn’t a nice-to-have. It’s an essential part of the strategy.
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