Why AI Maturity Is Declining And Why CEOs Need To Reinvent Their Businesses

A goldfish jumping into the next business model
CEOs selected one word to describe their companies' focus in an era of generative and agentic AI. The word that rose above the rest was 'innovation' according to IDC, a word that underscored the bold vision CEOs will need to achieve their goal of reinventing company business models in the next three-to-five years. To do so, organizations will need to invest in AI vision, fluency, and maturity at unprecedented speed and scale.
Driving AI-powered growth will require existential corporate transformation, and historically, companies have a poor track record here. Axios reported that a staggering 94% of c-suite executives say they're not satisfied with their current AI solutions. So how are companies progressing in their AI maturity? According to new ServiceNow research, AI maturity regressed by 25.5% between 2024 to 2025.
As AI technologies evolve, how is it possible for organizational AI maturity to regress? ServiceNow published its second annual AI Index report, which measures overall AI maturity based on a score between 0 and 100. Oxford Economics and ServiceNow surveyed just under 4,500 executives worldwide and measured organizational AI performance across five pillars of AI maturity: 1) AI strategy and leadership, 2) workflow integration, 3) talent and workforce, 4) AI governance, and 5) realizing value in AI investment. Last year's maturity scores were low across the board. This year's scores are lower still. In 2024, the average AI maturity score was 44 out of 100. In 2025, the average score is 35.
It might sound counterintuitive, but perhaps the decline in maturity is actually what CEOs need to achieve their goals of business model transformation. Richard Murphy, Head of Global Thought Leadership Research at ServiceNow, shared his thoughts on the slip back.
'These sharp drops suggest that AI innovation is outpacing organizations' capacity to deploy AI effectively at scale,' he observed.
The Agents are Coming, The Agents are Coming
2025 has been called the 'year of AI agents' and early adoption of AI agents did in fact play into ServiceNow's research. But the rise of AI agents, as yet another wave of complex software, forced executives to distinguish between signal from hype, adding to their sense of overwhelm.
Since the debut of ChatGPT in November 2022, companies around the world had to respond without having a generative AI plan at the ready. Then the ecosystem exploded with infrastructure providers, foundation models, cloud service providers, app developers, open-source communities driving the expansion of services and solutions at break-neck speed. Then came waves of AI reasoning, AI agents, and agentic AI. All the while, headlines were overwhelming with stories about superintelligence and AGI (artificial general intelligence), and the rise of AI native startups who were seemingly employing AI-first approaches to new org designs. Added up, Murphy's assessment of why companies moved backwards makes sense.
The Big Three Areas Inhibiting AI Forward Initiatives
ServiceNow's research showed that despite maturity falling year-over-year, 82% of companies expect to increase AI investment next year. But to make progress after a year of reversal, it helps to understand the challenges companies face in gaining headway.
Governance: Many enterprises are pushing to drive AI adoption, but in doing so, governance must be in place to protect the organization, employees, and stakeholders while empowering and enabling their experimentation. But only 44% of companies have made significant progress formalizing data governance, privacy, and compliance. This means a majority of enterprises do not have a designated team that drafts AI policies, mitigates AI risks, and focuses on responsible AI use.
AI Skills: AI requires not only new skills but also new mindsets. The goal is to help employees (and customers) learn what they can do with AI as a tool to optimize, enhance, and scale their existing work, while eliminating repetition, complexity, and the mundane. Additionally, the opportunity to help people explore how to collaborate with AI, not as a tool, but as a superpower, to do what they couldn't do yesterday, and unlock or create new value, is also necessary to drive AI innovation.
However, organizations are still struggling to articulate the necessary skills and identify the right talent to get the job done (let alone reimagine the jobs to be done). Of the companies surveyed, 64% are still in the process of identifying skills needed to implement their AI strategy.
Measurement: One of the main reasons for AI maturity declining YoY is that AI is changing faster that executives can develop strategies to experiment and evolve with it. Leaders find it elusive to connect business strategy to AI strategy. As a result, pilots tend to focus on discreet areas where impact and ROI are impossible to measure. For instance, 55% of companies have rolled out more than 100 AI use cases. But only 19% say those efforts are driving meaningful business outcomes. And just 29% have defined a set of metrics to measure return on AI transformation.
Governance, AI skills, and measurement are instrumental in scaling and AI. But the research also highlights a delta between most companies operating without a strategic AI vision and defined state for what success looks like. Of course this affects scores around governance, AI skills, and measurement. It also highlights an opportunity to grow toward the CEO aspiration of achieving business model transformation.
ServiceNow's Murphy observed, 'There's a vision gap at the top, as leaders struggle to set audacious AI goals while also driving measurable results.'
The AI Pacesetter Roadmap Offers a Path Forward
Though companies took steps backward this year in overall AI maturity, an elite cohort of companies, ServiceNow calls AI Pacesetters, are moving backward and forward differently. This group represents just 18% of all companies in the study but lead with an average score nine points higher than their peers (44 out of 100).
While still early in their developments, a Pacesetter roadmap is taking shape, which can help other companies close the emerging gap. Leading enterprises aren't just using AI as smarter tools, they're retooling their business starting with leadership. Leaders are building cultures of trust, enablement, experimentation, and empowered decision-making.
ServiceNow's research identified five categories where AI Pacesetters were gaining traction. This forms a roadmap to guide other companies in their strategy development and decision-making.
AI Pacesetters:
Pacesetters operate with a clear, shared vision in where AI can deliver practical and transformational impact. They look beyond the digitization that largely modernized yesterday's processes to explore AI-first capabilities, outcomes, business models, products, services, and experiences.
AI Vision
AI Pacesetters use AI as a strategic flywheel. Nearly 60% use AI to collaborate on leadership insights compared to 23% of others. They consider outcomes as they weigh investments. For instance, 49% of AI Pacesetters operate with a defined set of metrics vs. 25% of their peers. And 53% of AI Pacesetters are establishing AI innovation centers to evaluate AI solutions against business vision and goals and to explore opportunities that deliver practical and transformation outcomes.
Going back to the days of digital transformation, ambitious companies explored how to rewire the organization digitally to break down silos, integrate data, and connect people and work across the enterprise. Yet according to Gartner, just 35% of board directors reported achieving or that they were on track to achieving their digital transformation goals.
A similar pattern is playing out in an era of AI business transformation. ServiceNow found that only 30% of organizations have integrated workflows across business functions. This means most companies are exploring AI within confined use cases, which limits impact, prevents data and workflow integration, and confines AI to one part of the business.
Take a Platform Approach
Over half of AI Pacesetters (56%) have made significant progress toward connecting data and operational silos, compared to 41% of others. ServiceNow research found that 25% AI Pacesetters vs 11% have even invented new workflows across business functions to improve collaboration between humans and AI.
Becoming an AI-first business means rethinking workflows across the enterprise so that AI, data, processes, and people connect and optimize work across every operation
Focusing on the future means that you'll need the right talent and skills as AI evolves. Half of all Pacesetters (50%) say they have the right mix of talent to execute on their AI strategy, compared to 29% of others.
Focus on Talent
Seventy percent of Pacesetters say they promote cross-functional alignment across the enterprise. Seventy-one percent empower teams to make their own decisions about how AI can improve their work. Training and upskilling is critical, not just today, but with every wave of AI, which is why 80% of AI Pacesetters are actively investing in their people vs. 54% of others.
Organizations need guardrails, processes, and leadership around AI experimentation. AI (and data) governance mitigates risk while enabling employees to explore AI-enabled approaches to their work. Here, AI Pacesetters are leading the way. They take a more proactive stance on governance.
Prioritize AI Governance
A majority (72%) have already assessed AI applications for risk and worked to understand data privacy requirements, compared to under half of others. Sixty-three percent have made significant progress addressing data governance and security issues with AI- specific policies, compared to just 42% of others. And 57% have implemented policies for data governance, privacy, lawfulness, and compliance.
I had an opportunity to meet with a company recently that emphasized the importance of establishing a cross-functional center of excellence to accelerate and expand governance efforts. For extra credit, the company also stood-up an AI Advisory Council consisting of senior leaders and experts. These groups ensured the balance of guardrails, risk mitigation, and innovation with the responsible, safe and ethical use of emerging technologies and standards foundational to scaling AI investments.
AI agents and Agentic AI is the latest trend that is both overwhelming AI decision makers but also offering unimagined opportunities for efficiency, scale, and also to completely reinvent work to accelerate AI business transformation.
Taking a platform approach can enable organizations to integrate workflows and manage data, oversee their AI strategy from a single control tower, and identify and optimize quick wins. Doing so allows companies to deploy agentic AI, learn, and scale faster than competitors.
Embrace Agentic AI
For example, AI Pacesetters prioritized agentic AI pilots to improve experiences, increasing operational efficiency and productivity, and innovation. As a result, these ambitious companies reported big gains in improved customer experiences (58% Pacesetters vs 36% Others), increases in efficiency and productivity (57% vs 30%), and the ability to innovate faster (52% vs 32%). Eighty-three percent of AI Pacesetters also reported increases in gross margins compared with 64% of others.
AI Pacesetters are Already Breaking Away from the Status Quo
The rapid evolution of AI technology and headlines has been relentless since the launch of OpenAI's ChatGPT in 2022. And there are no signs of slowing down. It's understandable to see AI maturity step back. Legendary basketball coach John Wooden once asked, 'If you don't have time to do it right, when will you have time to do it over?' It's a reminder that amid the rush to adopt AI, slowing down to build the right foundations may be the most strategic move a company can make.
The drop in AI maturity isn't a setback. It's a reset. As AI advances faster than organizations can adapt, leaders have a critical window to step back, refocus, and rebuild with purpose. The companies pulling ahead aren't chasing every new tool—they're aligning strategy, talent, governance, and operations to unlock real value.
To move accelerate AI business transformation, organizations must define a clear AI vision, invest in skills and governance, integrate AI across workflows, and focus on measurable outcomes. This is the moment to shift from experimentation to transformation. The future will belong to leaders who treat AI not as a side project but as the foundation of their next business model.

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