ServiceNowAI Maturity Index: A 5-Stage Framework Toward Enterprise AI Transformation

Unlocking the Way forward for Enterprise AI: Insights from the ServiceNow AI Maturity Index

At ServiceNow Information 2025 in Las Vegas, I had the privilege of becoming a member of Chief Innovation Officer Dave Wright, my boss, and Tom Smith, Editor in Chief, analyst, at Cloud Wars, to debate a pivotal growth within the AI panorama: the ServiceNow AI Maturity Index. This complete framework, constructed on insights from over 4,500 international organizations, presents a structured method to evaluating and advancing AI methods inside enterprises.

Accelerating Enterprise AI Success: Introducing the ServiceNow AI Maturity Index

At ServiceNow, we consider the long run isn’t one thing we enter, it’s one thing we architect and affect. I just lately had the chance to hitch Dave Wright and Tom Smith to discover insights from the AI Maturity Index. This isn’t simply one other framework. It’s a residing blueprint, formed by deep analysis throughout greater than 4,500 international organizations, designed to assist firms higher perceive the place they’re of their AI journey—and extra importantly, easy methods to transfer ahead with intention and confidence.

What Is the AI Maturity Index?

The AI Maturity Index categorizes organizations into 5 distinct levels, offering a roadmap for firms to evaluate their present AI capabilities and establish areas for development. This mannequin emphasizes the significance of governance, adoption, and delivering tangible enterprise worth from AI investments

Why This Issues Now

AI is now not a buzzword; it’s a enterprise crucial. However too usually, organizations dive in and not using a clear technique or governance mannequin. That’s the place the AI Maturity Index is available in. It breaks down the trail to AI excellence into 5 distinct levels, serving to leaders establish the place they stand and what steps to take to drive significant outcomes.

In Our Dialog, We Explored:

The origin of the Index and the way this idea got here to life. Spoiler alert: it born out of the necessity for an actual, sensible roadmap to assist leaders operationalize AI.

Stunning insights: Many organizations report a dip in AI maturity as they scale. It’s not at all times a straight line. And understanding why is essential to transferring ahead.

The way forward for governance and worth: We unpacked why maturity isn’t nearly utilizing AI—it’s about aligning it with function, belief, and measurable impression.

In case you’re main digital or AI transformation, or simply attempting to make sense of the place your group matches on this quickly shifting panorama, this dialog is for you.

Watch the video here – and uncover the place you’re on the AI maturity curve.

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

The dialog takes place on the ServiceNow Information 25 occasion in Las Vegas, that includes ServiceNow executives Wright and Solis. Wright explains the creation of the AI Maturity Index, pushed by the necessity for the standard maturity index for purchasers deploying AI. The index was developed by interviewing 4,500 firms and figuring out 5 standards to fee maturity ranges. The index offers a five-stage maturity mannequin, permitting firms to plan and observe their AI journey.

Business and Geographic Insights (01:41)

Smith inquires if the surveyed firms are solely ServiceNow prospects or a broader vary. Wright confirms the survey included ServiceNow prospects and highlights the insights gained on variations primarily based on trade and geography. The index presents a 3-D view of maturity development, contemplating trade and geographic elements. Information governance and AI governance are essential; governance is usually a barrier to AI development.

Counterintuitive Findings on AI Maturity (03:18)

Smith discusses the counterintuitive discovering that AI maturity is down regardless of new know-how and use circumstances. Wright attributes the lower to the overwhelming variety of new applied sciences and use circumstances, resulting in a reevaluation of AI methods. A CIO‘s remark at a gathering highlights the belief that AI’s potential is bigger than initially understood. The dialogue touches on the idea of a “control-delete second,” the place firms rethink their AI methods.

Challenges and Alternatives in AI Deployment (05:59)

Solis and Wright focus on the complexity and velocity of AI evolution, resulting in a necessity for higher understanding and governance. International CIO Rachel Sandel was on the occasion. Her firm, Orica, is talked about for instance of an organization with superior AI governance buildings. Relatively than counting on remoted IT setups, the dialogue factors to centralized AI deployment as key to scaling impression throughout the group. Solis notes that solely 30% of firms deploy AI use circumstances throughout a number of features, reinforcing silos fairly than breaking them down.

Governance and Measurement in AI (08:44)

Wright and Solis focus on the necessity for higher governance and information governance in AI deployment. The dialog shifts to measurement, with conventional IT metrics being reevaluated within the context of AI. New metrics like prevented failures and automatic processes are launched, reflecting the evolving nature of AI measurement. The dialogue touches on measuring the worth extracted from AI investments.

Individuals Concerns and Organizational Impression (11:07)

Smith raises the difficulty of individuals issues and organizational impression in AI deployment. Solis emphasizes the significance of expertise and abilities in AI roadmaps, with a concentrate on expertise and abilities as key pillars. The dialog explores the potential for AI to create new roles and alternatives for human-machine collaboration. Wright talks in regards to the want for organizations to have powerful conversations about AI’s impression on jobs and workforce transformation.

Business Management in AI (16:02)

Smith asks in regards to the prime three industries main in AI maturity: know-how, heavy manufacturing, and banking. Wright attributes the management to those industries’ early adoption of automation, which facilitated speedy AI adoption. The dialogue consists of the stability between automation and innovation, with a warning towards automating to mediocrity. Solis provides that buyer expertise ought to be a key focus in AI deployment, utilizing Amazon for instance of profitable automation and buyer obsession.

Platform Method and Enterprise Transformation (21:46)

Smith inquires about the advantages of a platform method in AI deployment. Wright explains {that a} platform method offers centralized management and visibility, important for managing AI brokers. The AI Management Tower idea is launched, permitting for the administration of brokers from totally different distributors inside a unified platform. Solis talks about how companies should rework for an period of AI, transferring past digital transformation to true enterprise transformation.

Ultimate Ideas and Closing Remarks (24:52)

Wright and Solis focus on dreaming larger in AI deployment. There’s a necessity for organizations to suppose past price financial savings and concentrate on worth creation and enterprise transformation. The dialogue concludes with a name to motion for organizations to discover new prospects with AI and reimagine their enterprise fashions.