The ingenuity of generative AI at scale

Generative AI has seemed almost too good to be true. It cuts coding time from days to minutes, personalizes products down to the tiniest detail, and spots security vulnerabilities almost as soon as they appear. And it’s helped skyrocket AI ROI from 13% to 31% since 2022.

While this largely reflects the success of pilots, sandbox experimentation, and other small-scale investments, these early results have business leaders rethinking what’s possible. Our latest proprietary survey of 5,000 executives across 24 countries and 25 industries reveals that most executives are more optimistic about the generative AI opportunity than they were last year. More than three in four (77%) say gen AI is market ready, up from just 36% in 2023, and nearly two-thirds (62%) now say gen AI is more reality than hype.

From skepticism to confidence: Executives see the true value of generative AI taking shape

More than three-quarters of executives say they need to adopt generative AI quickly to keep up with competitors. And 72% of the highest performing CEOs say competitive advantage depends on who has the most advanced generative AI, according to the IBM Institute for Business Value (IBM IBV) 2024 CEO study.

Already, business leaders have begun to discover how generative AI boosts the bottom line. Operating profit gains directly attributable to AI doubled to nearly 5% from 2022 to 2023—and executives expect that figure to hit 10% by 2025. And embedding generative AI in existing enterprise software workflows also promises to deliver more sustainable ROI, according to forthcoming IBM IBV research.

One in three companies pause an AI use case after the pilot phase—but two in three don’t.

Still, despite these early signals, some analysts are skeptical. They anticipate that this hype-driven adoption spike will be followed by a “trough of disillusionment,” where organizations back away from the complexity involved with deploying generative AI in core business functions. And in some instances, it’s true. One in three companies pause an artificial intelligence use case after the pilot phase—but two in three don’t. In this setting, how can business leaders best translate successful experimentation into enterprise-grade investments that can deliver value at scale? 

Where is generative AI delivering the most value today?   

Generative AI promises to be a powerful catalyst for business transformation—but it’s not a panacea. It must be implemented with careful consideration of cost, data governance, and ethical implications, as well as an eye toward talent and skills. Because generative AI’s biggest strength is to augment human work rather than automate it, culture change is essential to deliver sustained value. In fact, 64% of CEOs say succeeding with generative AI will depend more on people’s adoption than the technology itself.

Instead of applying generative AI as a solution for every problem, leaders need to understand how different tools work together, with traditional AI techniques, generative AI models, and automation each playing their own part. They must break out of the use case mindset and focus on using generative AI to transform how employees work every day. Getting there is a journey—and how much experience an organization has with AI influences where it should start. 

Focusing generative AI adoption in essential business functions helps organizations create transformative, top-line growth.

Organizations are taking two main approaches to drive the systemic change needed to deliver sustained AI ROI.

1. Experimentation: Finding efficiencies in low-risk, non-core functions. Prioritizing generative AI adoption in low-risk areas where traditional AI is already delivering clear business value helps accelerate transformation and can drive incremental profitability. Roughly two-thirds of executives say their organizations are adopting generative AI in customer service (70%), IT (65%), and product development (65%) functions, which is consistent with what we saw in mid-2023.
2. Focus: Augmenting essential business functions to spark broader transformation. The risk of using generative AI in business operations closer to the core may be higher—but this is where the promise of business transformation begins to take shape. Those willing to focus on the previously underexplored areas of sales; information security; and supply chain, logistics, and fulfillment are seeing higher ROI.

But for some organizations, transformative opportunities like these seem out of reach. That’s why some are considering a platform approach to generative AI that pools resources and gains across departments or partner organizations as a lower-cost, simpler-to-implement option. This way, leaders can avoid starting from scratch in each area and embed generative AI quickly and more strategically across functions that have the greatest potential, including finance, supply chain and manufacturing, human resources, and sales and marketing. However, leaders taking this approach also need to consider the unique needs of each function and find ways to fine-tune generative AI applications accordingly.

Productivity gains that provide an advantage today will be table stakes tomorrow.

By providing an AI platform that lets employees experiment safely, organizations can unlock the collective genius of their workforce and enable data-driven decision-making. Leaders will need to foster a growth and innovation mindset—and encourage employees to look beyond what’s worked in the past—to pioneer groundbreaking innovation, outpace the competition, and drive transformative growth at scale with generative AI. 

Download the report to learn where generative AI is currently delivering the highest ROI, how executives can capitalize on its long-term potential and overcome key challenges, and what steps you can take to scale generative AI and transform the business—regardless of where you are on the AI journey.