The Dallas stop of re:imagine 2025 opened with proof instead of prediction. A customer dialogue with AMD’s Kari Ramseth, HR Service Center Leader, illustrated what disciplined scale looks like in practice.
Her team introduced an HR assistant to handle about 30% of employee inquiries, expanding only after accuracy and trust were confirmed. Within the month it was managing thousands of inquiries a week.
“We went live saying it could answer about 30% of employee questions,” Ramseth said. “Now we’re seeing thousands handled each week—faster, more consistently, and still human where it matters.”
The point wasn’t automation hype or trend-chasing, but dependability through design. This approach and others resonated across a room of more than 200 business and technology leaders gathered at the Astoria Event Venue in Irving, Texas.
In the opening strategy briefing, Michael Kropidlowski, Kore.ai’s Chief Marketing Officer, described how enterprises are moving from pilots to platforms.
He outlined how governance, security, and design converge so intelligent systems operate as extensions of enterprise discipline. Cathal McCarthy, Chief Strategy Officer at Kore.ai, expanded that view.
“After three years of experimentation since GPT-3, it’s emerging that the key to enterprise success lies in single-platform solutions.”
McCarthy noted that agentic tools have driven what he called “off-the-chart velocity.” But the next step is coherence: managing that speed through orchestration and shared standards.
By 2028, about 95 percent of enterprises will run AI in daily operations; the advantage will belong to those that unify it under one backbone rather than scattered tools.
A later analyst segment with Craig Le Clair, Forrester VP and Principal Analyst, added data to that framework. He reported that two-thirds of Forrester’s executive inquiries now center on orchestration and governance. Leaders who have scaled are now asking how to manage dozens of autonomous systems without fragmentation.
Le Clair described that gap as the next competitiveness frontier: companies that build-in governance from the start maintain velocity instead of rebuilding it.
In a technical exploration, Cobus Greyling, Kore.ai’s Chief Evangelist, examined coordination as the defining capability of enterprise AI.
“The challenge isn’t access to AI anymore,” Greyling said. “It’s coordination—getting systems, agents, and humans to work together safely.”
He showed how orchestrated agents can now complete complex, cross-departmental workflows end-to-end while maintaining full audit trails. The insight landed cleanly: autonomy becomes valuable only when every decision is observable and explainable.
The day concluded with a boardroom discussion featuring Nolan Waltman of First Service Credit Union. Their focus: performance, risk, and return.
The topic of enterprises building “AI control towers” to unify oversight and compliance across hundreds of systems was raised to start. Waltman added the financial perspective: measurable outcomes are the only way to prove sustained value. Le Clair closed by emphasizing that innovation is no longer about speed alone but about governance that lasts.
Across the day, one theme reigned supreme: enterprises aren’t building AI skyscrapers anymore. They’re designing cities. Every model, agent, and workflow must fit within an infrastructure that can scale safely, support traffic, and withstand change. The winners will be those who master urban planning, not simply construction.
Dallas demonstrated how large organizations are codifying AI and moving from rapid deployment toward disciplined execution.
The examples, from AMD’s measurable rollout to McCarthy’s single-platform imperative and Greyling’s coordination model, formed a blueprint for the next era of intelligent operations.
AI is becoming infrastructure, governed by the same standards that define finance, supply chain, and customer service.
Leaders left with clear priorities for the months ahead:
As one attendee noted leaving the Astoria Event Venue, the conversation has evolved to a focus on responsibility and how to build AI that performs predictably, safely, and at scale.