BOARDS ARE PAYING ATTENTION. AI IS FORCING CHANGE, BUT IT IS ALSO GIVING LEADERS AN OPPORTUNITY TO GUIDE THAT CHANGE AND REFRAME THE CONVERSATION.
Even when a problem is deeply damaging to the business, there are too few credible data points to make a compelling case for resource prioritization. And too little understanding of what goes on behind the scenes to link problems to a common cause.
This leaves the contact center stuck as a cost center: the price the business pays for all the messy, broken processes it has not fixed elsewhere.
The contact center leaders know the problems, but they haven’ t been able to solve the root causes.
THE CHALLENGE, REFRAMED
This has always been a challenge, and lately it is getting harder. Interaction volumes rise relentlessly, while budgets do not. Customers expect more, product and policy change is constant, and channel sprawl makes the picture more complex. The net is carrying more weight with fewer stitches.
Here is the good news. The conditions that kept the contact center out of the root cause conversation are shifting. Leaders now have the tools, data, and mandate to do more than“ handle the calls.” They can fix the system that creates the calls.
Customer service and the contact center are now C-suite discussions. Boards are paying attention. AI is forcing change, but it is also giving leaders an opportunity to guide that change and reframe the conversation.
Change is coming. But how the leaders manage it will determine whether the contact center remains a torn safety net.
DATA AVAILABILITY HAS CHANGED
For years, the story from the front lines was compelling but anecdotal. Contact center leaders had transcripts in pockets, flagged calls, sample QA scores, and embedded operators with rich experience.
What they lacked, though, was total visibility across interactions, with enough precision to quantify the impacts and enough currency to survive a budget meeting.
That is now available. The unstructured mass of conversations, messages, and case notes can be captured, searched, clustered, and trended at scale.
• Modern speech and text analytics unlock who said what, where, and why.
• Generative AI tools summarize long interactions into crisp, comparable records.
• Topic detection groups emergent issues that would never have been named in static taxonomies.
• Continuous QA gives a fuller picture than a 1 % sample ever could.
BOARDS ARE PAYING ATTENTION. AI IS FORCING CHANGE, BUT IT IS ALSO GIVING LEADERS AN OPPORTUNITY TO GUIDE THAT CHANGE AND REFRAME THE CONVERSATION.
Beyond this, the visibility outside the contact center is far greater. It’ s not just“ our” systems that can be interrogated and aggregated, it’ s all of them, from the CRM through ticketing, even internal communications.
Data alone, however, does not change minds. It must be presented in such a way that it is clearly understood by others.
Packaged well, data gives leaders what they have lacked: evidence, timing, and a clear“ so what.” It converts“ we think” into“ we know” to justify ongoing and new investments in the contact center. And it makes inaction harder to defend.
CONTACT CENTER ISSUES
The conversation is happening, that C-level mandate is forcing them. Leaders like yourself have the data to guide the conversations: and with the data we have the soft power to drive real change. Other areas of the business can’ t refuse the conversation or label the problem anecdotal.
That gives contact center leaders the mandate to drive change, to fix the net, so they can bring the customers along.
AI MAKES IT ECONOMICALLY FEASIBLE
There is so much buzz, hype, and excitement around AI that leadership teams are predisposed to invest in it. Customer service has become a C-suite priority because of the perceived potential with AI.
Ironically, those who are most ardently calling for AI transformation are often the least familiar with the workflows, constraints, and risks of production operations.
This opens the door to failed implementations that wreak havoc on all departments, not just customer service.
Worse still, it alienates customers and the agents who engage with them. It also wastes investment resources, both time and money. And it squanders the opportunity for positive transformation.
Contact centers are extremely complex, mission-critical operations. AI capabilities are new, powerful, and rapidly evolving. But the two elements don’ t easily mix. Effective deployment requires:
• A workflow‐first view of how service actually gets done, end-to-end.
• Ready access to the right data, governed and reliable.
• Pragmatic, iterative change, where you automate what should be automated, assist where judgment matters, and redesign where the system itself is wrong.
FEBRUARY 2026 35