We're a week removed from the start of Knowledge 26. (Yes, it's only been a week.) But there's just so much more to discuss. So, let's keep the momentum going.
The session Activate Your AI Control Tower with Customer Success spent considerable time discussing governance, orchestration, and operational oversight -- wait, let me guess. You've heard a lot about that already this past week.
Alright, fair statement. That said, underneath all of it was a simpler message that implementation partners should heed: AI projects are increasingly being judged by customer success outcomes, not technical completion.
That changes the role of partners like CoreX in meaningful ways. For years, enterprise implementations were largely measured through delivery milestones. Was the platform configured properly? Were workflows operational? Did the integrations work? Was the go-live successful?
Those questions still matter (perhaps more than ever). But as we've learned at K26, AI introduces a different layer of accountability. Customers now expect platforms to continuously improve operational efficiency, employee experience, and decision-making after launch.
The AI Control Tower Centers on Coordination
ServiceNow framed the session around the concept of an enterprise AI control tower, describing a centralized operational layer capable of coordinating AI workflows, governance, recommendations, and autonomous actions across the business.
From a CoreX perspective, the more important takeaway is that clients are actually asking for help coordinating complexity.
As we know, many organizations are already overwhelmed by overlapping systems, siloed processes, disconnected workflows, and competing priorities. And, in untrained hands, AI can often accelerate those problems before it solves them.
That is where implementation partners become critical. The real opportunity is helping customers build operational frameworks that allow AI to function responsibly and effectively at scale.
For CoreX, that means customer success increasingly starts long before deployment, when our team works to understand process maturity, workflow alignment, governance, and where operational value lies.
Customer Success Teams Are Becoming Transformation Teams
During the session, ServiceNow introduced “Integrated Success,” combining advisory services, implementation guidance, expert support, and platform health monitoring into a unified customer success approach.
In short, customer success is becoming part of the transformation delivery itself. For implementation partners, that creates an important strategic opportunity.
Many customers still approach AI with understandable uncertainty. They want efficiency gains, but they also worry about governance, adoption resistance, process disruption, and long-term operational sustainability.
(Read: "How are we going to manage all this?")
The most valuable partners moving forward will be the ones capable of helping customers navigate organizational change around AI most effectively, which requires a much more consultative relationship. Customers increasingly need partners who can:
- Align AI initiatives with operational realities
- Create governance structures that scale
- Help leadership measure outcomes
- Identify workflow friction before automation magnifies it
- Continuously refine processes after launch
That work looks far more like operational partnership than traditional implementation support.
Hitachi Energy’s Story Highlights What Drives Adoption
The strongest operational lesson from the session may have come from Hitachi Energy’s experience implementing AI-driven workflows.
Jaime Pulido, Global IT Service Integration Manager, Hitachi, discussed how the organization reduced ticket volume by 25% while improving efficiency through AI-powered capabilities such as incident summarization and workflow integration. But the operational details surrounding that success were far more important than the metric itself.
Pulido emphasized early planning, governance, employee enablement, and embedding AI into tools employees already used, including Microsoft Teams.
That approach reflects something many organizations are beginning to realize: AI adoption succeeds when it feels operationally natural. Employees rarely embrace new technology because they are told to. They adopt tools that reduce friction inside the workflows they already trust.
This creates a very actionable standpoint. Instead of positioning AI as a dramatic organizational overhaul, implementation teams can focus on identifying moments where AI removes operational drag from existing processes. This might mean:
- Reducing repetitive HR case handling
- Accelerating incident triage
- Improving procurement visibility
- Streamlining employee onboarding
- Enhancing knowledge delivery
- Summarizing operational data faster for support teams
Small operational wins often build organizational trust faster than massive transformation promises.
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For most, the AI journey is really just beginning. Don't go it alone! Reach out for an AI consultation call, to ensure your AI readiness matches your ambition, so those first steps matter!
