Main image of article Chief Cloud Officers and AI: What You Need to Know

Summary

Chief Cloud Officers (CCOs) are tasked with designing and implementing their companies’ respective cloud strategies. It’s a role that touches on everything from cybersecurity and revenue to cutting-edge tech. And as you might imagine, it’s a role heavily influenced by the rise of AI.

Although CIOs have traditionally steered enterprise IT strategy, AI’s integration into cloud infrastructure is creating a unique leadership opportunity for CCOs—positioning them not just as operational leaders, but as enablers of innovation and business transformation.

Today’s CCOs are expected to do far more than manage infrastructure and control cloud costs. They must support Agile development and optimize operations across diverse cloud environments—all while ensuring security, compliance, and scalability.

AI offers CCOs the potential to radically enhance their ability to do so by automating repetitive tasks, identifying inefficiencies, forecasting trends, and enabling smarter, faster decision-making.

To harness that potential, CCOs must not only understand what AI tools can do, but how to integrate them into strategy, workflows, and governance models.

For John Pettit, CTO at Promevo, AI is transforming the CCO from a behind-the-scenes operator into a proactive strategist. “The role of the CCO is evolving from primarily a manager of cloud infrastructure and costs to a strategic leader who leverages AI to drive business value,” he says. “With AI, the CCO is becoming a champion of cloud strategy—identifying new opportunities and ensuring AI is used safely and ethically.”

Shaown Nandi, director of technology at Amazon Web Services (AWS), puts it more bluntly, calling AI tools accelerators for CCOs unlocking massive potential to innovate faster: “It's not just about having more data, it's about having intelligence built into every layer of your cloud operations.”

AI transforms cloud management by bringing all the data to an executive’s fingertips, enabling better decisions and operational efficiency, he adds. This gives CCOs the ability to anticipate needs—not just react to them. Meanwhile, the CCO is moving away from hands-on infrastructure to analyzing the performance of and recommendations from AI agents.

These tools allow CCOs to focus on decisions that maximize outcomes for the least cost—options that wouldn’t be possible without the insights AI provides.

AI’s use cases in the cloud are diverse and rapidly expanding.

For Chris Hesse, vice president of global platform engineering operations at Mondelēz International, code completion and AI-powered development tools are among the most transformative.

“There isn’t a better use of generative AI than code assistants,” he says. “At Mondelēz, we use Amazon Q Developer—it boosts productivity for every developer.”

Hesse emphasizes the CCO’s responsibility to stay hands-on. “I use Amazon Q Developer personally,” he adds. “For example, I’ll ask it to write a Python script that lists AWS account costs by date. Using the tools gives you insights into how to accomplish things that previously seemed out of reach.”

Beyond engineering enablement, AI is driving powerful improvements in cost and performance.

Pettit compares the CCO to the captain of a fleet. “AI tools act like navigation and weather forecasting systems,” he explains. “They can detect anomalies, predict costs, and recommend ways to optimize cloud resource usage—like right-sizing virtual machines.”

Cameron Brunner, senior vice president of HPCWorks at Altair, says he sees immense value in AI for FinOps and SecOps.

“If the value from your cloud seems depressed due to high costs, FinOps tools help. If there’s high risk from security incidents, SecOps AI solutions are critical,” he says. “Predictive autoscalers can even address resource acquisition lags—reducing inefficiencies before they hit production.”

With a deluge of AI solutions flooding the market, CCOs must also determine what’s worth adopting.

Nandi advises to start by working backwards from what issue the CCO is trying to solve. “Where are your teams hitting roadblocks? Where are you missing opportunities to experiment or innovate?” he asks. “Look at the tools that are already available in your cloud platform and test them in limited environments.”

Pettit outlines four key evaluation criteria: alignment with business objectives, data readiness, tool integration, and vendor reliability.

“It’s not about finding the most powerful AI tool—it’s about choosing the right one that integrates smoothly and addresses your most pressing challenges,” he says.

Hesse emphasizes listening to engineering teams, noting CCOs must enable team to use emerging tools while remaining vigilant about security: “You have to ask the hard questions: Where’s our data going, and is it being used to train external models?”

Meanwhile, Brunner recommends a use-case-first approach. “If I’m leading an HPC cloud team, I ask: Where’s the most value at risk? Is it cost, security, or time-to-deploy?” he says. “Then I match the AI solution accordingly.”

Understanding AI is no longer optional for today’s cloud executives—with AI technology evolving literally overnight, the complexity of the cloud ecosystem is changing too.

 “CCOs face challenges CIOs never did—multi-cloud, GPU-as-a-service, evolving threat environments,” Brunner says. “AI-integrated tools are essential to managing this.”

Pettit stresses that while CCOs don’t need to become data scientists, they do need to be fluent in AI concepts. “It’s about strategic understanding,” he says. “Enough to make decisions, evaluate tools, and guide adoption.”

Nandi adds that CCOs must understand how to enable responsible AI adoption: providing guardrails, enabling creativity, and ensuring performance and cost are balanced.

At Mondelēz, Hesse believes using the tools firsthand is part of the job. “I’m always developing something myself,” he says. “It keeps me sharp, keeps the strategy grounded, and ensures that when my team needs a solution, we’ve already prototyped the foundation.”

As AI reshapes cloud operations, CCOs also take on a critical governance role—ensuring that innovation doesn’t outpace ethics or security. “Enabling your teams to deliver outcomes fast is important,” Nandi says. “But it must happen within the right guardrails—security, privacy, and cost-awareness must be built in.”

Brunner believes this dual mandate—enable innovation while managing risk—is now central to the CCO role, adding it’s a shift that’s long overdue. “AI gives you tools to optimize, but the responsibility for deployment, oversight, and outcome alignment still rests with you,” he says. “Cloud operations have always been about enabling scale and speed. AI just gives us sharper tools and deeper insights.”