via CIO Online, Dave Wright and Brian Solis

At first glance, the central finding in the newly released ServiceNow and Oxford Economics’ 2025 Enterprise AI Maturity Index study seems surprising: on a 100-point scale, the average AI maturity score dropped nine points from last year. With so much attention, focus and investment in AI, how is it possible that businesses have fallen behind?

The reasons are relatable but telling. The speed of AI is overwhelming and moving faster than most organizations can keep up. In 2022, OpenAI introduced the world to generative AI. By 2024-2025, AI agents took over the spotlight. Now, agentic AI is the new rage. At the same time, AI complexity combined with the uncertainty around unproven pilots and the inherent limitations of basic use cases is holding back companies around the world, and across every industry. Naturally, they’re more reserved and move cautiously.

There are also those leaders who see uncertainty as a catalyst for finding answers and an opportunity for curiosity, exploration and imagination. This group is motivated to speed up, to challenge their assumptions and explore bolder, more ambitious pilots that move the needle. In doing so, they broaden their perspectives and force-function the ability to uncover more impactful AI use cases and outcomes. ServiceNow calls these progressive leaders AI Pacesetters.

AAt first glance, the central finding in the newly released ServiceNow and Oxford Economics’ 2025 Enterprise AI Maturity Index study seems surprising: on a 100-point scale, the average AI maturity score dropped nine points from last year. With so much attention, focus and investment in AI, how is it possible that businesses have fallen behind?

The reasons are relatable but telling. The speed of AI is overwhelming and moving faster than most organizations can keep up. In 2022, OpenAI introduced the world to generative AI. By 2024-2025, AI agents took over the spotlight. Now, agentic AI is the new rage. At the same time, AI complexity combined with the uncertainty around unproven pilots and the inherent limitations of basic use cases is holding back companies around the world, and across every industry. Naturally, they’re more reserved and move cautiously.

There are also those leaders who see uncertainty as a catalyst for finding answers and an opportunity for curiosity, exploration and imagination. This group is motivated to speed up, to challenge their assumptions and explore bolder, more ambitious pilots that move the needle. In doing so, they broaden their perspectives and force-function the ability to uncover more impactful AI use cases and outcomes. ServiceNow calls these progressive leaders AI Pacesetters.

What does it mean to be low or high in AI maturity?

The study measured organizations across five pillars of maturity:

• AI strategy and leadership
• Workflow integration
• Talent and workforce
• AI governance
• Realizing value in AI investment

Early enterprise maturity starts when companies begin to understand AI and explore how it can be used in their company, whereas full maturity involves transformation, when a company’s AI vision is focused on innovation and transformational investment.

The decline in AI maturity found in the 2025 Enterprise AI Maturity Index illustrates that, across the board, companies are struggling to keep up with the pace of change. In further studying the data and speaking with companies, we also know that they’re constrained by the limited use cases and examples of companies bucking the trend and breaking ground. As a result, the vast majority of businesses are in the early stages of AI maturity.

The decline in maturity also speaks to a reality check across companies. The relentless focus and hype around AI pressured everyone to act on the technology and behave as if they knew exactly what they wanted to do with it. But as AI keeps advancing and agentic AI has opened up ever more possibilities, executives are realizing they aren’t fully sure what they want to do with AI.

This all comes with a huge upside: It’s still early and it isn’t too late to make progress.

Learning from an AI Pacesetter

So, if we know AI has the potential to transform lives, work, businesses and markets, but we also recognize how much needs to be done to realize the opportunities, then what are executives to do? Some companies are more advanced in their AI maturity, offering a practical roadmap. These AI Pacesetters scored nine points higher in maturity and were far more likely to report improved experiences, efficiency and faster innovation from their AI solutions.

To learn what pacesetters are doing differently, we spent time with Rachael Sandel, the group chief information officer at Orica. Sandel and her team recently won a ServiceNow 2025 Pacesetter Award for their efforts in leading AI advancements. In our conversation, she identified seven steps that were crucial to Orica’s AI approach:

Embed and align your AI strategy with your existing technology and innovation strategies rather than starting from scratch. Instead of a standalone AI strategy, align your AI strategy to your technology roadmap and focus on incorporating AI into the various technology streams and functions. This alignment supports the delivery of collective objectives, including safety, productivity and sustainability.

Modernize your technology platforms to create a solid foundation for taking advantage of AI.

Form separate AI groups with distinct members so you can ensure key AI responsibilities are handled while concentrating your organization’s AI skills, knowledge, decision-making and oversight. These groups should include:

• A dedicated AI Center of Excellence with cross-business representation that leads AI thought leadership, evaluating and prioritizing ideas.
• An AI Council of senior leaders who are focused holistically and high level on risk, policies, initiatives and decision-making.

Prioritize governance by establishing principles and guidelines in alignment with your core values; implementing a governance framework with a group standard and risk management approach; and establishing three separate lines of governance through the AI Center of Excellence, AI Council and internal audits.

Promote talent in AI by hiring curious and adaptable individuals while providing training and upskilling opportunities; consolidating skills into the AI Center of Excellence; and combining talent change with management change to help adapt to technology changes. People will have to learn to work with this technology differently, as well as adjust to different processes and operating models.

Imagine and plan for the future of work with AI agents by extending pilot projects and integrating AI agents into business systems to boost productivity and demonstrate value today. At the same time, prioritize imagining and planning for a future where there is widespread adoption of AI solutions to transform business processes and AI agents perform tasks alongside humans, orchestrating across platforms and data sources and collaborating with other agents, transforming how we work.

The steps Sandel describes focus on creating a solid foundation in terms of technology, people, governance and leadership. Following these steps can help an organization fully harness AI’s potential while navigating the risks and complexities resulting from a technology revolution accelerating at an unprecedented pace.

From an AI strategy to a transformation strategy

Today, most businesses are focused on familiar strategies, with AI added to the remit. How are we going to implement AI in our work? How can I use AI to automate repetitive tasks, summarize activities and spotlight more relevant results? How can I use it to deflect calls, optimize my supply chain, improve vendor or employee onboarding, etc.? But the questions that Sandel and the Orica team are asking look beyond the status quo and instead seek to solve real problems, drive transformation and achieve business impact. AI should be a tool to achieve an organizational vision rather than deploying AI for its own sake. And that starts with having and articulating a ‘visionary’ vision.

When we imagine this bigger strategy, we should be open to questioning everything and recognizing that the full potential of AI will not happen without true transformation. And that transformation starts from within. There is a significant, measurable difference between “having a vision” and “being visionary.” The latter involves questioning why something should be done, not just how we do it. Where we will end up on this AI maturity journey depends on going beyond the constructs of today with AI to augment work and unlock new levels of innovation.