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InterviewContact Center2h · 12:06 BST · 5 min read
Why Contact Center Buyers Must Rethink CX for 2026
ISG’s Research Director, Keith Dawson, says the contact center is becoming a customer engagement hub, forcing buyers to weigh AI governance, context, quality automation, and IT alignment alongside vendor rankings. The practical test is whether platforms now fit the operating model the business needs
Contact center buying in 2026 is becoming less about picking the highest-ranked platform and more about deciding what role the contact center should play inside the enterprise.
Keith Dawson, Research Director at ISG, told CX Today that buyers now face a market shaped by AI, automation, analytics, governance, and deeper enterprise technology integration. That changes the evaluation process for service leaders who previously focused on routing, efficiency, and operational cost.
Dawson says the contact center is no longer an isolated function built mainly to process interactions at scale. Instead, it is becoming a broader customer engagement environment that must connect customer data, agent workflows, self-service, AI tools, and enterprise systems.
That shift raises the stakes for buyers. A platform decision now affects risk, data governance, customer context, agent experience, and how different departments act on customer intelligence.
Contact Center Buying Now Starts With Operating Model Fit
For many CX leaders, the buying process has traditionally started with vendor comparisons, feature checklists, and analyst rankings. Those still matter, but Dawson argues they are no longer enough.
The first question is now strategic: what does the organization need the contact center to become? Dawson told CX Today:
“The contact center isn’t necessarily being asked to be primarily just a routing and efficiency engine, right? It’s not just the interaction machine that we tend to think about it as over decades of time. It’s become something more fluid, more negotiable within companies.”
That has practical consequences for enterprise buyers. A platform that works well for a high-volume service operation may not fit a business trying to use the contact center as actional orchestration
Recent CX Today guidance on purchasing contact center software in 2026 makes a similar point, emphasizing AI, omnichannel routing, integration depth, agent experience, security, scalability, and total cost of ownership as core evaluation criteria.
Dawson’s argument adds another layer. Buyers have to map those capabilities against their own future operating model, not just their current technology gaps.
AI Governance Pushes IT Deeper Into CX Decisions
AI is also changing who needs to sit at the buying table.
Dawson noted that contact center technology now has to connect more fluently with the wider enterprise stack, especially around data, AI, and integrations. That is pulling core IT teams more directly into decisions that may previously have sat largely with contact center specialists.
The reason is risk. AI tools need access to customer data, historical interactions, knowledge sources, workflow systems, and sometimes transaction systems. As those dependencies grow, the buying decision becomes a governance decision as much as a CX decision. As Dawson went on to explain:
“When you add AI to the existing structures, you add the need to have governance in place, right? AI governance, model governance, data use, security, compliance. Every one of these words now matters a lot more than it used to.”
For service leaders, that means vendor evaluations need to cover more than productivity gains. They need to test how a platform handles model oversight, data access, security controls, compliance requirements, and escalation between automated and human-led workflows.
The operational risk is not only that AI performs poorly. It is that AI performs inside a poorly governed system, with weak context, unclear accountability, or disconnected enterprise data.
Context Becomes the Foundation for AI-Led Service
Dawson also identified context preservation as a critical capability as contact centers move deeper into AI, automation, and asynchronous customer journeys.
The issue is familiar to many CX teams. Customers move between channels, pause conversations, return later, speak to different agents, or shift from self-service to assisted service. If the platform loses the thread, customers have to repeat themselves and agents lose time rebuilding the history.
AI raises that bar further. Automated workflows need to understand not only what a customer said, but where the interaction started, what has already happened, which systems have been touched, and what the next appropriate action should be.
Dawson said context now has to persist “within the interaction,” “between interactions,” and “between systems” as workflows become more automated and less linear.
For buyers, that makes context a procurement issue. Omnichannel support on its own is not enough if the experience still resets when a customer changes channel or when an AI workflow hands off to an agent.
Quality Automation Moves From Efficiency to Coaching
Some AI use cases are easier to justify because they produce measurable time savings. Dawson pointed to transcription and summarization as early examples, where reducing after-call work by seconds per interaction can quickly translate into cost and productivity gains.
Yet the more significant shift may be in quality management.
Historically, supervisors sampled a small percentage of interactions, often reviewing them days or weeks after they happened. Automated quality management changes that model by allowing every interaction to be captured, evaluated, and calibrated consistently.
Dawson described the change as “utterly transformative,” adding that 100% evaluation creates a faster path from insight to coaching.
The implications go beyond supervisor efficiency. If contact centers can identify coaching needs from interactions that happened today, yesterday, or within the last hour, quality management becomes a live operational system rather than a retrospective compliance task.
That creates a new buying question. CX leaders need to assess whether AI capabilities simply automate existing tasks or help the organization change how it develops agents, manages risk, and improves customer outcomes.
Vendor Rankings Are Only a Starting Point
Dawson closed with a warning for buyers who treat rankings as the final answer.
“Rankings are a snapshot in time and a snapshot of one set of evaluative criteria.”
For enterprise CX teams, the stronger use of analyst research is to understand the range of capabilities available, identify vendors that may not have been part of the last buying cycle, and isolate the criteria that matter most to the organization’s own operating model.
The 2026 contact center market now includes providers from different legacy origins, including hyperscalers, CRM vendors, MarTech providers, and established CCaaS players. That gives buyers more choice, but it also makes the procurement process more multidimensional.
The practical question now is whether the platform can support the customer journeys, governance model, data architecture, agent workflows, and business outcomes the enterprise is actually trying to build.
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