Fragmented Contact Center Stacks Are Blocking Enterprise AI Strategy

Most enterprises have spent decades building contact center infrastructure optimized for humans. As AI becomes central to customer engagement strategy, that architecture is becoming a liability — not because of bad decisions, but because of accumulated ones.

Alpana Bajaj, Partner Group Product Manager for Dynamics 365 Contact Centre at Microsoft, describes the core problem: telephony came from one vendor, CCaaS from another, CRM from a third, and AI bots were layered on top. The cumulative result is a stack where customer context, interaction history, and workflow data all live in different silos.

The Cost of Fragmentation

Bajaj recounts a customer with AI running across five different contact center systems. When each system was asked the same question about a customer, none of their answers agreed. The data was too fragmented to produce a coherent picture.

"What should have been a two-minute resolution turns into a 20-minute apology tour," she says. "Customers may not know your architecture, but they absolutely can experience it."

Key Takeaways

• Integration drag is the real cost: Adding more AI tools to a fragmented stack makes the problem worse, not better. Every new workflow requires coordinating across multiple vendors and integration layers.
• UCaaS and CCaaS convergence is accelerating: Complex customer issues increasingly draw in agents, product specialists, and operations staff simultaneously. Siloed tools mean the customer bears the cost of that fragmentation.
• Architecture decisions made now will compound: Organizations that consolidate onto connected platforms will be able to iterate on AI workflows faster than those managing multi-vendor stacks.

Note: This article is sponsored by Microsoft, which offers Dynamics 365 Contact Centre as a unified alternative.

Read the full article on UC Today