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ZDNET’s key takeaways

• Measuring productivity means setting KPIs that show value.
• Working harder with AI doesn’t always mean working better.
• Focus on strong partnerships that demonstrate clear benefits.

Proving the value of AI is more challenging than it sounds. A CIO recently explained to me he’d proudly told his CEO that the organization’s Microsoft Copilot implementation had saved the average employee 30 minutes a day. The CEO’s response was curt: “So what? How are staff using that time to produce something valuable for the company?”

The CIO admitted to being somewhat flummoxed. The lesson, he said, was that all professionals who want to exploit AI must demonstrate how their implementation produces real, tangible benefits, not just a reduction in the time it takes to complete a task.

Also: I asked 5 data leaders about how they use AI to automate – and end integration nightmares

So, how can professionals turn a desire for value into actual productivity gains? Here are five ways to create great productivity boosts from your AI projects.

1. Concentrate on business outcomes

Bernhard Seiser, VP of digital, data, and IT at AOP Health, said his organization introduced Copilot and ChatGPT a year ago, and set KPIs to measure success.

“The first one, of course, was adoption. OpenAI told us adoption is high in our organization, so it’s heavily used,” he said.

(Disclosure: Ziff Davis, ZDNET’s parent company, filed an April 2025 lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.)

“But then the usage does not really tell you a lot. I mean, it could be for email writing in the end — success should be tied to the outcome and the impact of what you do to your products and interactions with customers.”

Also: 5 ways to use AI when your budget is tight

Seiser told ZDNET that’s where the second KPI comes in: working with the rest of the business to define a list of challenges and evaluate the benefits that AI brings for each use case. 

“I think that’s a better metric than just purely looking at the adoption rates,” he said.

Now, Seiser said he wants to create a productivity-focused approach for individuals across the organization.

“I think it will become even more important once we analyze the use cases and do a thorough investigation on how beneficial gen AI is for helping out with the specific use cases, because there you will see much better impact on the business,” he said.

2. Determine the operational benefits

John-David Lovelock, distinguished VP analyst at Gartner, said it’s important to be skeptical about suggested AI-enabled productivity benefits.

“I encourage people to use jazz hands when they say productivity, because, for the most part, people say, ‘Hey, productivity is going to go up. Productivity is wonderful.’ Nobody ever defines what productivity is,” he said.

“We actually had a survey result from about two years ago that showed the less able a company was to measure the productivity that came from their AI project, the more likely they were to say that there was great productivity that came from their initiative.”

Also: A chief AI officer is no longer enough – why your business needs a ‘magician’ too

Lovelock told ZDNET that successful professionals determine at the start of the project how the technology will improve operational effectiveness.

“The example that I tend to go to is email,” said Lovelock, referring to the implementation of gen AI tools in administrative areas.

“If someone sends out 100 emails a day, and is seen as a very productive worker, are you more productive if you send out 125 emails, or if you send out 80 emails that don’t confuse people, or 40 emails that don’t cause the whole company to go into an email thread hell?”

3. Cooperate tightly with others

Ewa Zborowska, research director at IDC, said tight cooperation between the IT department and lines of business is crucial to achieving value-generating goals.

“You have to finance AI somehow, and budgets will often be shared,” she said. “There will be a co-ownership over certain solutions, so making sure that you work together, understand each other, and have KPIs in place that help you understand whether you’re smartly spending money is going to be important.”

Until now, Zborowska said companies have often directed AI spending to tech-related areas, such as cybersecurity and software development, where firm processes are in place, and a lot of data is ready for AI projects.

Also: 5 ways you can stop testing AI and start scaling it responsibly

Now, AI is increasingly being applied to operations, customer service, marketing, and back-office functions: “Almost in all areas, customers say that investment often will double over the next year.”

However, her firm’s research with tech giant Lenovo found that as many as 94% of European CIOs expect to see a positive ROI from their AI initiatives, and Zborowska told ZDNET that strong partnerships will be critical to success.

“Our face-to-face in-depth interviews with CIOs confirmed that the approach has changed, and it has had an impact on how digital leaders are perceived within the company, because IT professionals are now viewed as a partner for business, not just people who make sure that servers are working and email is OK.”

4. Let people tell brilliant stories

Richard Corbridge, CIO at property specialist Segro, said his organization evaluates enterprise-grade AI solutions in a matrix, where projects are assessed and prioritized based on likely costs and potential savings in terms of money and time.

Corbridge told ZDNET that an important element of this process is letting people test the tools.

“Let people who want to try AI get their hands on it, so they can start to have a look, and they become the biggest fans out there, who’ve had a crack and can talk to others about their experiences,” he said.

“It’s fascinating when you put a bunch of professionals in a room, and you’ve got the cohort who have tried AI and think it’s great, and the cohort who are still a bit terrified of it, they soon get FOMO because of those who have tried it and got something out of it, rather than the other way around.”

Also: Worried AI agents will replace you? 5 ways you can turn anxiety into action at work

Corbridge said that professionals who benefit from AI can help show its worth to others.

“Once you’ve got AI, and people have seen the value, it’s hard to try to take it off them,” he said. “So, let’s get the brilliant stories out there so that the other people can see what this stuff is going to bring.”

5. Embrace the watercooler chat

Like other industry experts, Gartner’s Lovelock said that AI might give people a bit of extra time back in their day — and that’s not necessarily a bad thing.

“The simplest productivity gains are likely going to be ‘latte productivity,'” he said. “Yes, you’re going to save some time and effort, and the value to the company is you’re going to have the time to go get a latte now.”

While the CIO I mentioned earlier encountered a CEO who required clear, measurable benefits from an AI implementation, Lovelock said executives who don’t see the value of extra downtime could be missing a trick.

Also: 6 ways to stop cleaning up after AI – and keep your productivity gains

“When people are eight hours head-down, you don’t have a corporate culture. You have people approaching burnout. If you give them half an hour, where they can get a latte and enjoy the company of their co-workers, there’s value in that,” he said.

“So maybe you’re saying, ‘How do you measure the success of AI?’ And you can say, ‘Hey, we gave people back half an hour a day.’ That would be the measure: AI reduces pressure and anxiety. In short, the value of that half an hour is different for every organization.”