5 strategic shifts for real AI value, not just productivity
▼ Summary
– A CIO learned that demonstrating AI value requires showing tangible business benefits, not just time savings like 30 minutes per employee.
– Bernhard Seiser of AOP Health recommends measuring AI success through business outcomes and use case impact, not just adoption rates.
– Gartner’s John-David Lovelock warns that productivity is often poorly defined, and successful projects start by defining how AI improves operational effectiveness.
– IDC’s Ewa Zborowska emphasizes that tight cooperation between IT and business lines, with shared budgets and KPIs, is critical for achieving AI ROI.
– Richard Corbridge of Segro advocates letting employees test AI tools to generate positive stories and enthusiasm, which helps spread adoption through FOMO.
Measuring productivity through AI means setting KPIs that demonstrate tangible value, not just time saved. A CIO recently recounted telling his CEO that Microsoft Copilot had saved each employee 30 minutes daily. The CEO’s blunt response? “So what? How are staff using that time to produce something valuable for the company?” The CIO admitted he was caught off guard. The lesson is clear: any professional leveraging AI must show how the technology delivers real, measurable benefits, not merely a reduction in task completion time.
So, how can professionals turn a desire for value into actual productivity gains? Here are five strategic shifts to create substantial boosts from your AI initiatives.
1. Focus on business outcomes, not just usage rates
Bernhard Seiser, VP of digital, data, and IT at AOP Health, introduced Copilot and ChatGPT a year ago with specific KPIs. “The first one, of course, was adoption. OpenAI told us adoption is high in our organization, so it’s heavily used,” he said. But he quickly realized that usage alone doesn’t reveal much. “It could be for email writing in the end. Success should be tied to the outcome and the impact on your products and interactions with customers.” Seiser now emphasizes a second KPI: collaborating with the business to define challenges and evaluate AI’s benefits for each use case. “I think that’s a better metric than just purely looking at adoption rates,” he noted. His next step is creating a productivity-focused approach for individuals, analyzing use cases thoroughly to see where gen AI truly impacts the business.
2. Define operational benefits clearly
John-David Lovelock, distinguished VP analyst at Gartner, urges skepticism about AI-driven productivity claims. “I encourage people to use jazz hands when they say productivity, because nobody ever defines what it is,” he said. He cited a survey showing that the less able a company was to measure AI productivity, the more likely they were to claim great results. Successful professionals, he argues, determine upfront how technology will improve operational effectiveness. His example: email. “If someone sends out 100 emails a day and is seen as productive, are you more productive if you send out 125 emails, or 80 that don’t confuse people, or 40 that don’t cause email thread hell?”
3. Cooperate tightly across departments
Ewa Zborowska, research director at IDC, stresses that close collaboration between IT and business lines is critical. “You have to finance AI somehow, and budgets will often be shared. There will be co-ownership over solutions,” she said. Historically, AI spending went to tech areas like cybersecurity and software development, where processes are firm and data is ready. Now, AI is expanding into operations, customer service, marketing, and back-office functions, with investments often doubling year over year. Her firm’s research with Lenovo found that 94% of European CIOs expect positive ROI from AI, but strong partnerships are key. “IT professionals are now viewed as a partner for business, not just people who make sure servers are working and email is OK,” Zborowska said.
4. Let people share brilliant stories
Richard Corbridge, CIO at property specialist Segro, evaluates enterprise AI solutions through a matrix that assesses projects based on costs and potential savings in money and time. He encourages letting people test the tools. “Let people who want to try AI get their hands on it, so they become the biggest fans out there, who’ve had a crack and can talk to others about their experiences,” he said. He noted that when you put professionals in a room, those who have tried AI and think it’s great create FOMO among those still terrified of it. “Once you’ve got AI, and people have seen the value, it’s hard to try to take it off them,” Corbridge added. “So, let’s get the brilliant stories out there so others can see what this stuff brings.”
5. Embrace the watercooler chat
Gartner’s Lovelock points out that AI might give people extra time, and that’s not necessarily bad. “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’s CEO demanded clear benefits, Lovelock argues that executives who dismiss extra downtime are missing the point. “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 to enjoy the company of co-workers, there’s value in that.” He concludes, “The value of that half an hour is different for every organization.”
(Source: ZDNet)
