Post-Knowledge 2025: What manufacturers need to know about ServiceNow’s AI leap

Now that the dust has settled from Knowledge 2025, one takeaway stands out: ServiceNow is fully committed to enterprise AI transformation. For manufacturers, this is a pivotal development.

The CoreX road crew spent the week meeting with customers, showcasing solutions, and digging into the most impactful announcements. The message to manufacturers was evident: AI is enterprise-ready, but only if your data foundation is equally prepared.

A week later, here’s what stood out, and how it maps to the challenges manufacturers are facing right now.

The Big Shift: From AI demos to AI at work

We’ve all seen AI headlines before. But we won’t lie, this year felt different.

Announcements like the acquisition of Data.world and the expansion of the Workflow Data Network weren’t about future promises, but rather about immediate execution. These are tools designed to work in production environments, not just in proof-of-concepts.

That’s a significant change for manufacturers grappling with aging systems, siloed data, and the growing pressure to increase uptime and reduce cost. The AI conversation is no longer theoretical. It’s operational. And it couldn’t come at a better time.

Foundation First: The CMDB still rules

One theme that echoed across every manufacturing session: without clean, connected data, AI can’t help you.

ServiceNow’s AI agents are impressive, generating incident summaries, accelerating root-cause analysis, and even making proactive recommendations. But every one of those capabilities depends on a clean, connected, and actively maintained CMDB.

At CoreX, we’ve emphasized this for years, and now, with the addition of metadata intelligence from Data.world, ServiceNow is reinforcing that message. If you’re still treating your CMDB as an afterthought, you're already behind.

Real Manufacturing Wins: What we saw (and showed)

One of our favorite moments came from demoing our work with a global auto manufacturer. We’ve integrated 100+ shop-floor devices directly into ServiceNow, so when a robot goes down, the system doesn’t just log a ticket. It identifies the device, pulls repair steps using GenAI, and delivers a fix in plain language.

That’s not hypothetical. That’s happening now.

We’re building toward true orchestration: AI agents across IT, supply chain, and finance working together to identify issues, coordinate responses, and prevent downtime before it happens. Some clients, like Stellantis, are already seeing results: resolution cycles reduced from 26 days to just five.

ServiceNow’s AI Stack Just Got Deeper

Another key takeaway: ServiceNow is assembling an AI stack built for the enterprise, not just isolated AI features. Here’s why that matters:

• The Workflow Data Network, now supporting over 100 pre-built integrations across MES, ERP, and maintenance platforms, is finally creating connective tissue between traditionally siloed systems.
• A smarter GenAI Assistant, now context-aware and trained on your real business data—helping guide action, not just provide answers.
• Domain-specific agents that operate across roles and processes, signaling a move from isolated AI features to end-to-end orchestration.

This is the kind of layered, operational AI we’ve long advocated for and are actively implementing.

What Should Manufacturing Leaders Do Next?

After Knowledge 2025, it’s no longer a question of whether AI can support manufacturing, but whether or not your organization is positioned to take advantage. ServiceNow’s AI capabilities are built for real-world complexity, but they require strategic groundwork. Here’s where to start:

1. Audit your CMDB. If your configuration management database isn’t accurate, current, and fully connected across systems, your AI initiatives will stall. Treat your CMDB not as a project, but as critical infrastructure.
2. Target your biggest inefficiencies where your teams lose the most time, money, or visibility, and begin your AI journey there. Fast wins in areas like incident response, asset repair, or procurement delays can validate your investment and build momentum.
3. Design for orchestration, not isolation. Orchestration via connecting data and decisions across departments creates lasting operational value. Look for opportunities to weave AI into end-to-end workflows, not just one-off use cases.
4. Invest in cross-functional alignment across operations, engineering, finance, and leadership. Establish a shared vision and governance model early.
5. Act with urgency. Every quarter you delay is a quarter your competitors are gaining ground.

AI is a present-day performance driver. What separates leaders from laggards now is no longer vision, but execution. The tools are here. The roadmaps are proven. If you’re waiting for the “perfect moment” to start, you’re already behind. Now is the time to lead.

Final Thought: We’re just getting started

AI in manufacturing doesn’t look like job displacement. It looks like systems that finally match the speed, complexity, and intelligence of your operations.

At CoreX, we’re proud to be helping manufacturing teams turn ServiceNow’s innovations into real-world results. If you experienced Knowledge 2025 like we did, you know the moment is now.