We’ve all been guilty of blindly following the latest trend at one point or another.
For this writer, as much as it pains me to admit, it was the trademark side-swept fringe and uncomfortably tight jeans of an emo teenager.
For younger readers, it might be the current, inexplicable obsession with Labubus, which one day you’ll look back on with confused nostalgia.
Whatever your vice, the good news is that some mortifyingly embarrassing photos and a small amount of wasted cash are probably all you have to worry about.
Unfortunately, for major enterprises delivering customer experiences that matter, deciding to hitch their wagon to the wrong trend can have far more damaging results.
Right now, there is no bigger CX trend than AI. Be it chatbots, agent-assist tools, or QA, enterprises are experimenting with AI wherever and however they can.
Of course, this isn’t to say that AI should be ignored; the technology’s potential to drastically alter and enhance CX is undeniable. But despite the hype, not every AI deployment delivers the results businesses expect.
For Joseph Kelly, Solutions Architect at Miratech, part of the issue is the ubiquitous nature of the tech, as he explains:
Everything is AI. But is it just AI for AI’s sake?
“Customers really need to hone in on the right strategy to start with. In the CCaaS space, in customer experience and employee experience, first getting strategy right will help cut through a lot of the clutter and get to the heart of how AI can really help.”
Kelly’s point hits at a real challenge: how to separate genuine AI value from marketing spin.
Vendors are quick to slap ‘AI-powered’ on everything, from natural language understanding to speech recognition; the trick is knowing what will actually move the needle.
The Hype vs. Reality
When organizations are hype-driven, they run the risk of deploying technology without a defined goal, which often results in overspending.
Kelly notes that even established tools like NLU IVRs have been ‘AI-powered’ in marketing terms for years, without fundamentally improving the experience.
“It’s about cutting through the marketing and sales speak on what is really AI, and what’s not,” he says.
“Then, you look at where you want to start to make real change. Are you looking to enhance your customer experience with AI? Or your agent experience with AI? That’ll help guide you where you’re trying to get to.”
Enterprises that clarify their objectives – whether it’s reducing call volumes, boosting first-contact resolution, or improving agent workflow – are far more likely to see tangible benefits from their AI deployments.
Start Small, Solve Real Problems
For organizations just starting with AI, Kelly believes the best approach is to take things step-by-step.
For example, he highlights practical pilots like agent-assist, smarter routing, and call deflection as good examples of “seeing how the technology can help agents provide more informed and efficient answers to customer inquiries.”
Small-scale projects reduce risk and can produce immediate wins against clear goals to build on. Routing customers correctly the first time reduces wait times; agent-assist tools speed up complex resolutions. These early wins build momentum and justify wider adoption.
However, in order for these pilots to be successful, he emphasizes the need for “good, accurate data that the AI can access.”
Once pilot projects show value, scaling AI requires alignment with broader business goals. Efficiency, personalization, and agent experience must stay front and center. But again, data is at the heart of it all.
“Where am I going to house all of this information?” Kelly asks.
“Does it have to be in the CCaaS vendor’s platform? Do I need a way to connect these things so a change in one system propagates to another?”
Kelly also cautions that adding AI won’t fix a weak foundation.
If you don’t have a really stellar customer experience today, adding AI is not going to provide the benefits you’re probably thinking it can.
Consolidating data, optimizing knowledge management, and improving processes must come first.
Avoiding AI for AI’s Sake
For Kelly, the major contributors to AI project failures are vanity projects, poor integration, and a lack of adoption by agents and customers.
To combat this, change management is critical.
Agents need confidence in new tools, and customers must feel automation improves – not hinders – the experience. Without this, even advanced AI can underperform.
This is where Miratech can help. By grounding AI projects in business needs and guiding enterprises through data strategy, integration, and adoption, the company turns AI investments into tangible, measurable business outcomes.
This all means AI doesn’t have to be just a buzzword or trend. When used with clear goals, it can truly transform customer experience – improving efficiency, personalization, and agent empowerment.
The key is to have a purpose: and then start small, scale strategically, and let AI serve the business, not the other way around.
You can learn more from Joseph Kelly on how to maximize your CCaaS migration by checking out this article.
You can also discover Miratech’s full suite of solutions and services by visiting the website today.
