Unlocking the Future of Enterprise AI: Insights from the ServiceNow AI Maturity Index

At ServiceNow Knowledge 2025 in Las Vegas, I had the privilege of joining Chief Innovation Officer Dave Wright, my boss, and Tom Smith, Editor in Chief, analyst, at Cloud Wars, to discuss a pivotal development in the AI landscape: the ServiceNow AI Maturity Index. This comprehensive framework, built on insights from over 4,500 global organizations, offers a structured approach to evaluating and advancing AI strategies within enterprises.

Accelerating Enterprise AI Success: Introducing the ServiceNow AI Maturity Index

At ServiceNow, we believe the future isn’t something we enter, it’s something we architect and influence. I recently had the opportunity to join Dave Wright and Tom Smith to explore insights from the AI Maturity Index. This isn’t just another framework. It’s a living blueprint, shaped by deep research across more than 4,500 global organizations, designed to help companies better understand where they are in their AI journey—and more importantly, how to move forward with intention and confidence.

What Is the AI Maturity Index?

The AI Maturity Index categorizes organizations into five distinct stages, providing a roadmap for companies to assess their current AI capabilities and identify areas for growth. This model emphasizes the importance of governance, adoption, and delivering tangible business value from AI investments

Why This Matters Now

AI is no longer a buzzword; it’s a business imperative. But too often, organizations dive in without a clear strategy or governance model. That’s where the AI Maturity Index comes in. It breaks down the path to AI excellence into five distinct stages, helping leaders identify where they stand and what steps to take to drive meaningful outcomes.

In Our Conversation, We Explored:

The origin of the Index and how this concept came to life. Spoiler alert: it born out of the need for a real, practical roadmap to help leaders operationalize AI.

Surprising insights: Many organizations report a dip in AI maturity as they scale. It’s not always a straight line. And understanding why is key to moving forward.

The future of governance and value: We unpacked why maturity isn’t just about using AI—it’s about aligning it with purpose, trust, and measurable impact.

If you’re leading digital or AI transformation, or just trying to make sense of where your organization fits in this rapidly shifting landscape, this conversation is for you.

Watch the video here – and discover where you are on the AI maturity curve.

Genesis and Goals of the AI Maturity Index (00:23)

The conversation takes place at the ServiceNow Knowledge 25 event in Las Vegas, featuring ServiceNow executives Wright and Solis. Wright explains the creation of the AI Maturity Index, driven by the need for a standard maturity index for customers deploying AI. The index was developed by interviewing 4,500 companies and identifying five criteria to rate maturity levels. The index provides a five-stage maturity model, allowing companies to plan and track their AI journey.

Industry and Geographic Insights (01:41)

Smith inquires if the surveyed companies are only ServiceNow customers or a broader range. Wright confirms the survey included ServiceNow customers and highlights the insights gained on differences based on industry and geography. The index offers a 3-D view of maturity progression, considering industry and geographic factors. Data governance and AI governance are critical; governance is often a barrier to AI advancement.

Counterintuitive Findings on AI Maturity (03:18)

Smith discusses the counterintuitive finding that AI maturity is down despite new technology and use cases. Wright attributes the decrease to the overwhelming number of new technologies and use cases, leading to a reevaluation of AI strategies. A CIO‘s comment at a meeting highlights the realization that AI’s potential is greater than initially understood. The discussion touches on the concept of a “control-delete moment,” where companies reconsider their AI strategies.

Challenges and Opportunities in AI Deployment (05:59)

Solis and Wright discuss the complexity and speed of AI evolution, leading to a need for better understanding and governance. Global CIO Rachel Sandel was at the event. Her company, Orica, is mentioned as an example of a company with advanced AI governance structures. Rather than relying on isolated IT setups, the discussion points to centralized AI deployment as key to scaling impact across the organization. Solis notes that only 30% of companies deploy AI use cases across multiple functions, reinforcing silos rather than breaking them down.

Governance and Measurement in AI (08:44)

Wright and Solis discuss the need for better governance and data governance in AI deployment. The conversation shifts to measurement, with traditional IT metrics being reevaluated in the context of AI. New metrics like avoided failures and automated processes are introduced, reflecting the evolving nature of AI measurement. The discussion touches on measuring the value extracted from AI investments.

People Considerations and Organizational Impact (11:07)

Smith raises the issue of people considerations and organizational impact in AI deployment. Solis emphasizes the importance of talent and skills in AI roadmaps, with a focus on talent and skills as key pillars. The conversation explores the potential for AI to create new roles and opportunities for human-machine collaboration. Wright talks about the need for organizations to have tough conversations about AI’s impact on jobs and workforce transformation.

Industry Leadership in AI (16:02)

Smith asks about the top three industries leading in AI maturity: technology, heavy manufacturing, and banking. Wright attributes the leadership to these industries’ early adoption of automation, which facilitated rapid AI adoption. The discussion includes the balance between automation and innovation, with a caution against automating to mediocrity. Solis adds that customer experience should be a key focus in AI deployment, using Amazon as an example of successful automation and customer obsession.

Platform Approach and Business Transformation (21:46)

Smith inquires about the benefits of a platform approach in AI deployment. Wright explains that a platform approach provides centralized control and visibility, essential for managing AI agents. The AI Control Tower concept is introduced, allowing for the management of agents from different vendors within a unified platform. Solis talks about how businesses must remodel for an era of AI, moving beyond digital transformation to true business transformation.

Final Thoughts and Closing Remarks (24:52)

Wright and Solis discuss dreaming bigger in AI deployment. There’s a need for organizations to think beyond cost savings and focus on value creation and business transformation. The discussion concludes with a call to action for organizations to explore new possibilities with AI and reimagine their business models.