AI is everywhere, but do we really know how to measure its impact? That was the big question tackled by Daryl Plummer, Distinguished VP Analyst and Gartner Fellow, during his keynote at the Gartner Data & Analytics Summit.

And if you’re a CIO, CTO, or CISO wondering how to prove AI’s value beyond just “it saves time,” you’re not alone.

Plummer hit the audience with a staggering stat: 41% of C-level executives say AI’s business value is unclear — but at the same time, 50% of CEOs expect technology leaders like you to figure it out and unlock the value of GenAI. No pressure, right?

The AI Value Problem: Are We Thinking Too Small?

Most organizations start their AI journey by looking for productivity gains — automating tasks, speeding up processes, reducing headcount needs. But Plummer’s message was clear: That’s just the starting point, not the endgame.

He broke it down into three levels of AI-driven value:

• Productivity Gains – AI helping you do things faster and cheaper. (Think: basic automation, chatbots, report generation.)

• Efficiency Optimization – AI improving decision-making and operations. (Think: AI-powered forecasting, customer segmentation, supply chain improvements.)

• Transformational Value – AI fundamentally changing how your business operates. (Think: AI creating new business models, industries, and revenue streams.)

Right now, most companies aren’t even making it past level one. In fact, according to Gartner, only 6% of organizations report that AI has truly transformed their business.

If You’re Not Thinking About AI Transformation, You’re Already Behind

Plummer pushed the audience to think bigger. He compared AI to major infrastructure projects like highways and railroads — the real value isn’t in the project itself but in how it changes industries and economies.

His advice? Shift your AI strategy from cost-cutting to competitive advantage. Instead of just optimizing what you already do, ask how AI can unlock entirely new opportunities.

Plummer pointed to real-world examples of companies already making that leap. In agriculture, AI is optimizing soil conditions, engineering better seeds, and reshaping global food production to improve both yield and sustainability. Meanwhile, healthcare is experiencing a revolution with AI-powered precision medicine, tailoring treatments to individual patients, improving outcomes, and reducing unnecessary medical waste. Even sports are being transformed as AI-driven analytics redefine real-time strategy, changing how teams compete and how fans experience the game.

And here’s the kicker — these aren’t “future visions.” They’re happening right now.

Plummer’s message to technology leaders was blunt: If you’re only using AI to cut costs, you’re already falling behind. The real leaders are using AI to change the game entirely.

So the real question is: Are you keeping up — or are you letting the future pass you by?

The AI Data Dilemma: Opportunity or Liability?

One of the biggest hurdles to reaching AI’s full potential? Data.

Plummer warned that AI is only as good as the data it learns from, and that’s a massive problem for most enterprises. Right now, according to Gartner, over 70% of enterprise data is unstructured and poorly managed—meaning AI systems are often working with incomplete, inconsistent, or even biased information​.

And here’s where it gets risky: Bad data leads to bad AI decisions. Imagine AI approving loans based on outdated customer records, recommending flawed business strategies, or even making critical security errors because of unclean or biased datasets.

One particularly eye-opening example? An AI system at a company accidentally exposed employees’ salaries across the entire organization. The issue? Poor governance over sensitive data.

The takeaway? If you don’t have a rock-solid AI data strategy, you’re not just missing opportunities, you’re creating serious risks. Plummer urged tech leaders to stop treating AI governance as an afterthought and start treating it like a mission-critical function.

AI Is Becoming More Than a Tool — It’s Becoming an Expert

Perhaps the most fascinating part of Plummer’s keynote was his vision for where AI is headed. We’re no longer just talking about automation. AI isn’t just crunching numbers, organizing data, or streamlining workflows. It’s learning, it’s advising, it’s becoming an expert.

Plummer introduced the concept of Agentic AI, where AI doesn’t just process information — it develops expertise over time. Instead of waiting for human input, these AI systems will proactively analyze data, make decisions, and even act autonomously in complex business scenarios​.

Think about it this way: AI won’t just assist a financial analyst—it will become the analyst, spotting market trends before humans do. AI won’t just support legal teams—it will help draft contracts and negotiate deals. And in hiring? AI won’t just scan resumes — it will act as both recruiter and candidate, matching talent to companies in ways that go beyond keywords and job titles.

AI is moving up the knowledge ladder, from just processing raw data to actually developing skills, expertise, and even strategic foresight​. This is a massive shift.

For CIOs, CTOs, and CISOs, this means AI isn’t just a tool to optimize workflows anymore — it’s a partner in decision-making. AI is no longer something you just “use”; it’s something you rely on. And the organizations that recognize this shift early? They’ll be the ones leading the next wave of AI-driven transformation.

The Wrap: AI Success Is About Mindset

Plummer closed with a powerful message: AI transformation isn’t a destination — it’s a journey. Too many organizations treat AI as just another tool for automation, a way to cut costs and improve efficiency. But the real game-changers? They’re the ones who see AI as a strategic enabler of entirely new opportunities.

The difference between incremental improvement and industry disruption lies in how AI is applied. It’s not just about optimizing existing processes — it’s about rethinking how business is done. That’s the mindset shift tech leaders need to make.

For technology leaders, this means taking a step back and asking the tough questions. Are you just using AI to do things faster, or are you using AI to do things differently? Are you leveraging AI to gain insights, make smarter decisions, and drive innovation, or are you simply plugging it into existing workflows?

The answer will define whether AI remains just another tool in your tech stack or the force that reshapes industries, redefines leadership, and propels your business into the future.

The companies that embrace this shift? They’ll be the ones leading the next wave of transformation. The rest? They might find themselves struggling to keep up in a world where AI isn’t just an advantage anymore — it’s the expectation.