Key takeaways

• Contact centers are shifting from cost-focused call hubs to strategic experience platforms that drive loyalty, revenue and brand differentiation
• Success metrics are moving from speed and cost to value
• AI is used fluidly across full automation and assisted copilots, with seamless human handoffs and humans in the loop by design
• Voice remains critical, modernization must pair AI with zero-trust security and rigorous governance and Responsible AI practices are vital
• HCLTech and Microsoft are partnering to deliver AI-led, cloud-based contact center solutions
• Journey design is becoming dynamic and AI-orchestrated, replacing static sticky note mapping with real-time, personalized experiences
• Winning organizations invest in new skills, continuous learning and an entrepreneurial culture that is willing to disrupt its own models

For Carol Criner, SVP, Strategic Accounts at HCLTech, the transformation of contact centers is personal as well as professional. She still remembers her early days in the telecom industry, when “when things got busy, we would all jump on the phones” and success was defined in the simplest possible terms: answering the calls.

In that world, metrics like speed of answer, handle time and cost per call dominated thinking. “That cost per call metric is something we’ve all known about for so long and managed to,” she reflects. The contact center was fundamentally a cost-control operation or a voice-only utility that turned queues into answered calls. The transition of contact centers being recognized as a brand extension and drivers of brand loyalty and growth has accelerated in the last fifteen years. Today, the focus on personalization has intensified. Contact centers are investing in AI-driven, omnichannel experience platforms that personalize at scale and create measurable business value. And that shift requires leaders to rethink not only technology, but success metrics, operating models and even culture.

From cost control to value creation

The first big difference Criner sees between “then” and “now” is the way success is measured. Where traditional metrics focused heavily on efficiency, “success metrics are really moving from what used to be…speed of answer, handle time, cost per call…to more of a value generation.”

First call resolution has been an important step, but it’s no longer enough on its own. Organizations are now looking at performance sentiment, loyalty and revenue impact. As Criner puts it, new measures are “really driving loyalty, and driving revenue,” shifting contact centers from cost centres to growth engines.

Leaders often underestimate the implications of this change in measurement. It can’t be treated as a reporting tweak at the end of a transformation program. Criner suggests that leaders must embrace “the evolution of measurements” as a core pillar of the strategy, because what organizations choose to measure will shape how they design journeys, train agents, deploy AI and justify ongoing investment.

The second major shift is organizational. The transformation of the contact center “is much more than an IT-led transformation,” says Criner. “It’s very much a business-led transformation.” That means complex cross-functional work, “breaking down silos that have been in place for decades” and prioritizing change management.

She highlights the importance of cultural change, leadership buy-in, dealing with employee resistance and creating confidence: “Point number one in our AI strategy is that we have confidence that we will disrupt our own model.” For Criner, that mindset is essential for leaders who want to succeed in this new age of AI.

Blurring the line between copilots and full automation

With the rise of Generative AI and intelligent copilots, enterprises are grappling with where to “draw the line” between assistive AI and fully agentic automation in the contact center. Criner’s advice is deliberately counterintuitive: “I would recommend that line not be firmly managed.”

There are obvious use cases for full automation, including password resets, order status checks and FAQs, where customers expect instant, self-service resolution. At the other end of the spectrum, emotional or sensitive issues are better served through “human-led within an assisted copilot environment,” where AI suggests next best actions, surfaces knowledge and orchestrates across channels, but the human remains in control.

The real differentiator, however, is not where the line is drawn, but how fluidly customers can move across it. Criner emphasises that “the key...[to] progression is ensuring that there is a path to humans,” that “humans are in the loop,” and that organizations have “very well-designed handoffs.”

Above all, this evolution must be governed thoughtfully. Criner urges leaders to define “good governance around risk and risk tolerance,” so they can iterate and expand automation safely over time without eroding trust.

Modernizing voice without sacrificing trust

Even as digital channels grow, voice remains a critical part of the contact center and a high-stakes one, given the sensitivity of the interactions. The challenge is modernizing voice with AI across authentication, real-time guidance, smarter routing and analytics, without increasing security exposure or damaging trust.

“Everything that we know and have been paying attention to related to security still applies,” says Criner. That means skilled, trained employees, zero-trust as a guiding principle and rigorous testing and monitoring. AI doesn’t replace these fundamentals; it sits on top of them.

HCLTech’s partnership with Microsoft’s Responsible AI initiative is one-way Criner sees the industry strengthening its security posture. She values the transparency in these collaborations: “When technology communities join together…the sharing of learnings, sharing what’s going well, sharing best practices, aligning on perspectives is valued.” This kind of collective learning helps organizations “keep that AI security strengthening as a top priority.”

A strategic partnership to transform contact centers with generative AI

HCLTech and Microsoft recently announced an expansion of its strategic partnership to transform customer service experiences with general AI and cloud-based contact center solutions. Criner describes this as “very much around growth of Dynamics 365 Contact Center and Copilot,” and is clear in her view: “We think Microsoft is the right answer. We believe Microsoft brings it all together: platform, productivity and AI.”

A key accelerator has been HCLTech’s acquisition of Microsoft’s Nuance professional services team. “What they have brought to our overall AI strategy…expertise in conversational AI,” explains Criner. That experience “has amplified our own Agentic AI capabilities” in the contact center space.

In practice, many clients are investing in developing AI-led customer experiences and moving to Microsoft from other platform. Criner highlights three pillars of value: long-developed tools and capabilities, “expert-led engagements” from conversational AI specialists and deep “knowledge and commitment to the Microsoft Dynamics 365 Contact Center and Copilot.”

For Criner, this is “an exciting time,” with “interesting businesses committed to taking giant steps in how they rethink customer experience.”

Proving that AI is working for customers and agents

As AI reshapes workforce optimization, leaders naturally ask: how do we know it’s improving the experience and delivering business value beyond simple productivity gains?

Criner points to movement in traditional metrics such as decreased call abandonment rates but also emphasizes new indicators. One example is tracking where there is “an AI-led personalized recommendation and how that is being accepted by customers.” Another is monitoring the rapid evolution of commercial models, including “dynamic pricing…aligning with cost and outcomes,” and the new market opportunities that appear when you take experience to the next level.

On a personal level, she sees tangible change in everyday interactions. “There was a moment in time where you would be placed on hold,” she says. “Now…while you’re on hold, there is an opportunity to have AI still engage with you and ask you questions…and potentially resolve your question while you’re on hold.”

That kind of design “opens up a whole new avenue of how to think about customer experience.” Measuring how often AI resolves the issue, how smooth the handoff back to humans is and “how frequently that is needed in the process” are all signals of whether your new, AI-enabled customer experience is on track.

Designing dynamic journeys for 2026 and beyond

Looking ahead to 2026, Criner expects the biggest change to be how journeys are designed and orchestrated. For years, customer journey design meant being “in a conference room and there’s a bunch of yellow sticky notes on the wall,” mapping ideal paths by hand.

Now, leading organizations are shifting to “more online, dynamic, real-time development of customer journeys.” The next 24 months, she says, are “very much around AI orchestration,” dynamic journey mapping and “moving away from those sticky notes and getting closer to that personalized customer experience.”

This transformation represents the foundation for new business models. Criner anticipates “new ways that we think about the role of humans in our customer experience,” leveraging AI for unmet needs that “create new revenue opportunities and other new markets.” Commercial models themselves will be “disruptive,” as contact centers become engines for experimentation and growth.

To prepare, she offers two pieces of advice. First, invest in the “evolution of skill sets,” ensuring people are continuously trained and certified, with learning treated as an ongoing effort, not a one-off program. Second, foster a culture that is “willing to test and try and pilot and really be open-minded” – what she calls an “entrepreneurial culture” around evolving customer experience.

Market momentum will reinforce this shift. Criner notes that the CCaaS industry is expected to exceed $17 billion by 2030, with North America leading initially but “further acceleration of growth in the APAC region” on the horizon.

Building a strategic experience platform

The contact center of the future will not be a siloed call hub or a bolt-on service channel. It will function as a strategic experience platform that orchestrates human and AI capabilities across channels, personalizing in real time, creating new revenue models and measuring value in terms of loyalty, outcomes and growth.

To get there, leaders will need to embrace business-led transformation and invest in AI skillset development.

The organizations that thrive will be those that are willing to disrupt their own models, evolve their culture and treat the contact center as a strategic capability to be continually reimagined.

FAQs

1. Why are contact centers shifting from cost control to value creation?
Contact centers are shifting from efficiency-only metrics to measures like loyalty, sentiment and revenue impact. AI and omnichannel platforms turn every interaction into a chance to personalize, solve issues faster and identify growth opportunities, so the contact center becomes a strategic driver of value, not just a cost.

2. How is AI changing the role of agents in the contact center?
Generative AI supports agents with real-time guidance, suggested next best actions and automated routine tasks like FAQs or status checks. The goal isn’t to replace humans but to blend automation and human empathy, with seamless handoffs and clear paths to a person whenever issues become complex or emotional.

3. What governance is needed to safely scale AI in contact centers?
Leaders should define clear guardrails for where AI is used, how decisions are audited and when humans must stay in the loop. Zero Trust security, Responsible AI frameworks, continuous monitoring and cross-functional governance help manage risk while allowing experimentation and iterative expansion of automation.

4. What is unique about the HCLTech–Microsoft approach to AI contact centers?
HCLTech and Microsoft are combining Dynamics 365 Contact Center, Copilot and Nuance’s conversational AI expertise to modernize customer service. Together, they provide a unified platform, AI copilots for agents and deep domain specialists who can design, implement and scale personalized, AI-led experiences across channels for enterprise clients.

5. How should organizations prepare their people and journeys for 2026 and beyond?
Organizations should invest in continuous reskilling, certifications and AI literacy for contact center teams while encouraging experimentation with new journeys and operating models. Moving from whiteboard journeys to dynamic, AI-orchestrated journeys helps them personalize at scale, unlock new revenue models and redefine the role of humans in service.