The 2025 CDO Study: The AI multiplier effect

AI-first enterprises are redefining market mechanics. They’re gaining ground with unprecedented velocity, creating a winner-takes-most dynamic.

It’s not just products or services that set these disruptors apart. It’s data. Organizations that tap into their most valuable data—and have a clear vision of what they want to achieve— deliver better AI-powered business results.

Only 26% of CDOs are confident their data capabilities can support new AI-enabled revenue streams.

 
What does that mean, practically, for enterprises that want to lead the future? To identify best practices, the IBM Institute for Business Value (IBM IBV) conducted in-depth proprietary research in partnership with Oxford Economics, surveying more than 1,700 Chief Data Officers (CDOs) across 19 industries and 27 geographies. We’ve also compared those results with findings from the 2023 CDO Study to paint a picture of how the CDO role has evolved.

Our research has identified five focus areas—strategy, scale, resilience, innovation, and growth—that help organizations deliver greater business value with data. The CDOs that excel in these areas are able to do more with their money—delivering higher ROI on both artificial intelligence and data investments.

They demonstrate that driving more value isn’t about accessing more data. It’s about using the most valuable data to deliver specific business outcomes. That’s what sets leaders apart.
 

1. Strategy 

Don’t just collect data. Deploy it on a mission.

Enterprise data strategy revolves around powering AI. 81% of the CDOs in our study prioritize investments that accelerate AI capabilities and initiatives.

As data becomes more central to business strategy and competitive advantage, organizations are increasingly investing in data strategy to fuel better AI outcomes. Today, 13% of a typical organization’s IT budget is allocated to data strategy, up from just 4% in 2023. But these funds shouldn’t be spent in a vacuum. To point the entire technology estate toward the same purpose, CDOs need to partner closely with other C-suite leaders, including Chief Information Officers (CIOs), Chief Technology Officers (CTOs), and Chief Information Security Officers (CISOs).

What does it take for organizations to deliver better AI-powered business results? CDOs from organizations that see higher ROI on both AI and data initiatives are 25% more likely to say they can clearly articulate how data priorities facilitate key business outcomes—and they have clear measures to determine the business value of data-driven results 18% more often than their peers. Plus, they’re more likely to say they integrate data strategy with the organization’s technology roadmap and infrastructure investments.

“Leading CDOs are not just optimizing functional capabilities, rather enabling their organizations to reimagine their end-to-end workflows powered by data and AI.”

Vikrant Bhan
Global Head of Analytics, Data, and Integration, Nestlé

 
Proprietary data—the structured and unstructured data that an organization intentionally collects and stores for its operational and decision-making processes—can provide a significant strategic advantage. 72% of CEOs go so far as to say that proprietary data is key to unlocking the value of generative AI. 

Yet, many organizations struggle to use their data to power AI. CDOs agree that the top data barriers they face on this front are accessibility, completeness, integrity, accuracy, and consistency. Fortunately, AI agents can help address these challenges—if organizations unleash AI on an optimized data estate.
 

CDOs are focused on outcomes—but many struggle to measure data’s value

2. Scale

Give AI agents a fast track to data.

AI agents can only be effective if they’re given a clear mission—and access to the high-quality data they need to learn and improve. Over the past two years, CDOs have made major strides on this front. In 2023, only 41% of CDOs said they had the right data platform in place to process enterprise data. In 2025, 75% say they have a data platform that allows data integration across silos when needed.

How can better data management expedite AI adoption at scale? With the right platform in place, AI can work with data that exists in multiple systems, formats, and locations across the enterprise. 81% of CDOs now say they bring AI to data rather than centralizing data for AI. This approach lets business leaders avoid the costs and security risks that come with relocating data while also accelerating AI-powered outcomes.

CDOs from organizations that deliver higher ROI on both AI and data investments focus on cultivating this type of dynamic data ecosystem. They’re more likely to use a common data hierarchy that enables the integration of structured and unstructured data. They also invest in automation to extract meaningful information from documents, images, and customer emails and phone calls at scale, ensuring AI has access to the same rich context that would inform a human employee’s decisions.

But transforming data practices for an AI-fueled future may also require a shift in mindset, as CDOs see a focus on short-term performance and resistance to change as their most significant barriers to innovation. Without a cultural shift, disconnected efforts could create more complexity and cost, rather than less.

CDOs say a focus on short-term performance is the top barrier to innovation their organizations face.

3. Resilience

Build unbreakable data pipelines.

AI amplifies both the value of good data and the potential cost of poor data. While human analysts might work around incomplete or inconsistent datasets, AI agents are more likely to perpetuate and scale biases, errors, or gaps in underlying datasets. The effective use of data requires actively managing these risks.

Can AI agents deliver reliable business outcomes? Today, 83% of CDOs say the potential benefits of deploying AI agents in their organization outweigh the risks—and 77% say they’re comfortable with their organization relying on outcomes from AI agents. This is a big shift from 2023, when CDOs were still struggling with data quality. At that time, only 44% said their leadership trusted the data the organization collected.

Still, there are operational lapses. While 80% of CDOs say they’ve started to develop a diverse range of datasets to train AI agents, 79% of CDOs say they’re still early in the process of defining how to scale and govern them.

One option is an agent marketplace, which helps organizations scale productivity gains while avoiding the expensive and risky proliferation of agents that could duplicate work, diverge from data governance guidelines, or share sensitive information beyond its intended scope.

The centralized screening process involved with populating this type of marketplace checks AI agents for data security vulnerabilities and other potential issues before releasing them for widespread use. This type of centralized management of AI also drives better performance: CAIOs spearheading hub-and-spoke or centralized AI operating models see 36% higher AI ROI than those managing decentralized operating models. 

CDOs from organizations that deliver higher ROI on both AI and data investments are 20% more likely to say they understand the increased data access requirements of agentic AI and that they're developing policies for secure and controlled data sharing within their organization. As a result, these leading CDOs are more comfortable with their organization relying on outcomes from AI agents—and they have more clarity on the risks introduced by AI agents accessing enterprise data.

82% of CDOs say they’re wasting data if employees can't access it for data-driven decision-making.

4. Innovation

Deliver data to every desk.

If employees can’t access data—via data platforms or AI agents—its value is limited. And CDOs know they need to stop the data chase.

In fact, 82% of CDOs go so far as to say they’re wasting data if their organization isn’t letting employees access it for data-driven decision-making. Data democratization can also expedite AI efforts: 80% of CDOs say it helps their organization move faster. This speed will come, in part, from connecting employees, AI agents, and data products. In a separate survey of operations executives, 90% said AI agents will enable employees to drill deeper into analytics to support real-time analysis and optimization by 2027.

CDOs from organizations that deliver higher ROI on both AI and data investments are ahead of the game. They’re 20% more likely to say the risk of limiting employee access to enterprise data is greater than the risk of giving employees broad access. They are also 15% more likely to allow employees to access relevant data assets through a unified interface, while maintaining security and governance around it. These approaches can include role-based access controls, multilayered security architecture, self-service with guardrails, and an empowering data culture.

Do organizations have the talent and skills they need to get more value from their data? Increasing talent scarcity is currently a barrier to building broader data literacy: 47% of CDOs now say attracting, developing, and retaining talent with advanced data skills is a top strategic challenge, up from 32% in 2023. This may be due to how quickly team composition is evolving: 82% of CDOs say they’re hiring for data roles that didn’t exist last year related to gen AI, up from 60% in 2024. 
 

Data roles are shifting—and getting harder to fill

5. Growth

Spot breakthroughs waiting to happen.

Proprietary data contains the organization’s secret sauce—special ingredients that can’t be replicated by the competition and that keep customers coming back for more.

78% of CDOs say leveraging proprietary data is a top strategic business objective to differentiate their organization in the market. What's more, 84% of CDOs say their unique data products, which can include customer 360 views, real-time operational dashboards, or financial forecasting datasets, have already provided significant competitive advantages.

As general AI capabilities become more commoditized, distilling value from proprietary data will become mission critical. That’s in part because AI can reveal patterns and possibilities that were previously invisible. Transforming proprietary data into data products helps organizations quickly identify market gaps or productivity plays they can capitalize on—opportunities for business growth that other organizations using different datasets wouldn’t be able to see.

Only 26% of CDOs are confident their organization can use unstructured data in a way that delivers business value.

 
CDOs also see immense value in ecosystem data, with 83% saying strategic partnerships enhance their organization’s data capabilities and promote innovation. 82% also say partnerships help accelerate AI and data-driven initiatives.

How can organizations get more value from proprietary and ecosystem data? It requires advanced data analytics and AI capabilities, high data quality, and a strong governance framework that connects enterprise-wide digital transformation. CDOs in organizations that deliver higher ROI on both AI and data investments are able to cut through this complexity. They incorporate clear mechanisms for creating value and turning it into revenue for their organization in their data strategies—and these leaders are 25% more likely to say AI has changed how they measure the ROI of data.

Download the full report for even more data and insights that will help your organization move faster, make better decisions, and capitalize on market changes.