Generative AI (GenAI) is moving rapidly from buzzword to business enabler. Few roles have embraced this revolutionary shift as much as chief product officers (CPOs), who spearhead all aspects of a company’s product strategy and development while focusing on innovation and growth. But while GenAI technology has reached near-universal adoption among corporate product leaders, how they use it is still evolving. In goods and technology sectors, users value the technology for its ability to accelerate early-stage creativity — supporting concept development, prototyping and visual design. By contrast, in the data-driven services sector, the technology shines in generating reports, summarizing insights and assessing the competitive landscape.
This adaptation reflects GenAI’s versatility. But it also signals that companies are still exploring where the technology fits best and how to use it most productively. Use of fully autonomous AI remains rare. Ultimately, expectations are high for GenAI to drive speed to market, enhance user experience (UX) and contribute to leaner teams.
These are just some of the findings in “From Spark to Strategy: How Product Leaders Are Using GenAI to Gain a Competitive Edge,” a PYMNTS Intelligence exclusive report. This edition examines the opportunities and challenges for CPOs utilizing the technology to support and get the best out of their product development strategies. It draws on insights from a survey of 60 product leaders working at U.S. firms, each generating at least $1 billion in revenue last year. The survey was conducted from March 14, 2025, to March 27, 2025.
GenAI Fuels Innovation, Not Oversight
Nearly all product leaders use GenAI, mostly to drive product innovation, especially in the goods and technology sectors.
Nearly every CPO surveyed uses GenAI — but not all use cases are equal. Product leaders are nearly twice as likely to use the technology for innovation and ideation than for production monitoring. Nearly 2 in 3 product leaders use GenAI to innovate products and services, while 38% use it to generate feedback on the production process. The information helps workers make adjustments that improve quality and process.
This signals a clear perception of GenAI as a creative partner in the idea phase, and not (yet) as a go-to for quality control or operational oversight. Rather than spending weeks aligning cross-functional teams on a concept, CPOs can use GenAI to jumpstart collaboration and surface multiple design directions in just a single meeting. By contrast, the use of GenAI for monitoring production remains limited, as product leaders still don’t fully trust the technology in roles where mistakes can carry significant operational, financial and legal risks. For now, GenAI is helping product leaders move from idea to concept faster than ever — but it’s not yet ready to run the shop floor.
Creativity in goods, strategy in services
Within that careful usage, users are tailoring GenAI to meet the strategic imperatives of different sectors. Among surveyed product leaders, those in the goods and technology industries are far more likely to use the technology to drive product design and idea generation. One in three goods providers makes product design the technology’s most important job, while 31% of technology companies do the same.
By contrast, services companies use GenAI for entirely different purposes: to draft reports, synthesize research and scan the competitive landscape. While 32% cite competitive analysis as GenAI’s most important task, 27% say the same about report writing. For this sector, the technology’s value lies in its ability to generate insights faster and craft better strategic positioning, not in visual creativity. This distinction highlights GenAI’s adaptability as a tool that evolves to meet core sector needs, not as a fixed solution.
Leaders Trust GenAI, But Humans Still Run the Show
CPOs remain overwhelmingly positive about the effectiveness of their GenAI tools, but they still rely heavily on human oversight.
Despite its promise, GenAI is rarely fully autonomous now. Most product leaders report that even high-automation tasks like fraud detection or workflow management still require human oversight. In fact, for more complex use cases — such as cybersecurity or strategic planning — AI almost always requires the human touch to input prompts and review results.
This finding reinforces a recurring theme in GenAI adoption: Usefulness does not mean independence. Among CPOs using GenAI for cybersecurity-related tasks, 77% acknowledge that it still needs a human touch. Whether for auditing AI output, feeding prompts or catching errors, people remain a crucial part of the equation.
Even in workflow automation — arguably one of the simpler, more structured use cases — fewer than half of CPOs say their systems operate without human input. For example, nearly half of CPOs use GenAI for fraud and error detection in a mostly but still partially automated way. This hybrid model points to a future where AI augments, rather than replaces, human decision-making, at least for now.
Is confidence just optimism in disguise?
One of the most intriguing findings concerns the strong confidence that CPOs have in GenAI’s effectiveness — despite the fact that the technology still requires human oversight. Every single CPO using GenAI says it is effective for the following functions and tasks: chatbots, code generation, inconsistency detection, text summaries, information retrieval, production monitoring and cybersecurity. This raises an important question: Are leaders embracing GenAI based on its transformative potential, or assessing it on its actual performance today?
What emerges in the data is a mismatch between perception and reality. While most corporate executives rate GenAI highly in terms of its effectiveness at completing specific jobs, the technology still requires extensive human oversight. In other words, the enthusiasm might reflect how quickly adopters have started to find GenAI useful in precise ways, rather than how ready they view it as actually being. Or perhaps effectiveness is judged not by extent of full automation, but by how much better they are than having nothing at all. If it allows teams to deliver faster, work smarter or test bolder ideas, that’s a win — even if it still needs a human touch.
GenAI Trims Teams, Boosts Speed and Sharpens User Experiences. It Doesn’t Trim Costs
CPOs see GenAI driving speed to market, UX and efficiency while not necessarily slashing production (labor) costs, suggesting a growing demand for analytical skills.
GenAI is reshaping workforce dynamics — and the impact isn’t evenly distributed. Nearly all CPOs agree that their need for more analytically skilled workers has increased. At the same time, headcount reductions depend on the level of automation. While all CPOs using GenAI in highly automated ways report a reduced need for lower-skilled staff, just 79% of those using the technology in less automated ways say the same. This signals that adopting GenAI does not necessarily result in a loss of all types of jobs.
In other words, GenAI’s current status is as a tool that empowers workers who can use it well. GenAI tasks require judgment, critical thinking and domain expertise, not just basic task execution. Meanwhile, companies are increasingly offloading tasks that involve routine execution — like compiling data, formatting documents or performing low-level research — to GenAI. In other words, high-performing teams use GenAI to do more with fewer employees.
What product leaders expect from GenAI in the years ahead
Speed to market, user experience (UX) and staffing costs top the list of expected industry impacts over the next three years, with all or nearly all CPOs across the goods, technology and services industries citing these expectations. Surprisingly, GenAI is less likely to impact production costs and resource allocation, with significantly fewer product leaders expecting a positive impact of GenAI.
Services and technology product leaders are especially optimistic, likely because the former are less tied to physical supply chains and the latter more amenable to digital transformation. In contrast, CPOs in goods and retail are more cautious, likely due to the fixed costs and logistical constraints inherent in their sectors.
These findings suggest that companies are not using GenAI as a cost-cutting tool but rather as a growth and efficiency enabler. The ability to shorten development cycles, refine UX through iterative design and reduce staff requirements by augmenting team capacity drives GenAI adoption.
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Methodology
“From Spark to Strategy: How Product Leaders Are Using GenAI to Gain a Competitive Edge,” a PYMNTS Intelligence exclusive report, examines the opportunities and challenges for CPOs using AI to support and optimize their product development strategies. It draws on insights from a survey of 60 product leaders working at U.S. firms that provide goods, technology or services, and that generated at least $1 billion in revenues last year. The survey was conducted from March 14, 2025, to March 27. 2025.
