Explore findings from the Deloitte AI Institute's report tracking generative AI trends, business impacts, and challenges throughout 2024.

The term “unprecedented” is often thrown around when talking about business and technology, to the point of being cliché. However, in describing the pace of generative AI’s emergence and advancement—and its massive potential impact on business (and humanity as a whole)—unprecedented could be an understatement.

Generative AI is already widely available to the public and has a running start toward critical mass. Also, similar to smartphones, it’s easy for an average person to use without much training—and can help with activities they already engage in every day—so the barriers to adoption are low. What’s more, generative AI has the strong potential to assist with its own future development, which could trigger a cycle of exponential improvement at exponential speed.

For our initial pulse on generative AI, we surveyed more than 2,800 leaders from AI-fueled organizations that are currently piloting or implementing generative AI. Findings show that 2024 is likely to be a defining year for generative AI worldwide, with global respondents planning significant investment and showing optimism about the technology’s potential.

Excitement about generative AI remains high, and transformative impacts are expected in the next three years.

Nearly two-thirds (62%) of the business and technology leaders surveyed reported excitement as a top sentiment with regard to generative AI; however, that excitement was tinged with uncertainty (30%). The vast majority of respondents (79%) said they expect generative AI to drive substantial transformation within their organization and industry over the next three years—with nearly a third expecting substantial transformation to occur now (14%) or in less than one year (17%).

The survey results suggest that many AI-fueled organizations are on the verge of scaling up their efforts and embracing generative AI in a more substantial way. This aligns with what we’re seeing in the marketplace, where organizations around the world are racing to move from experimentation and proofs-of-concept to larger-scale deployments across a variety of use cases and data types—pursuing both speed and value capture while managing potential downside risks and societal impacts.

Many leaders are confident about their organization’s generative AI expertise.

A large percentage of our survey respondents (44%) said they believe their organizations currently have high (35%) or very high (9%) levels of expertise with generative AI. This result is somewhat surprising given how rapidly generative AI is evolving. But within the specific context of our survey, high levels of confidence seem entirely reasonable since we deliberately chose experienced leaders with direct involvement in AI initiatives at large organizations already piloting or implementing generative AI solutions.

Organizations that report very high expertise in generative AI tend to feel more positive about it—but also more pressured and threatened.

Relative to other respondents, leaders who rated their organization’s overall generative AI expertise as “very high” tended to feel much more positive about the technology; however, they also feel more pressure to adopt it—and see it as more of a threat to their business and operating models. Analysis showed this group using more modalities, deploying generative AI across more enterprise functions, and pursuing more use cases.

Current generative AI efforts remain more focused on efficiency, productivity and cost reduction than on innovation and growth.

The majority of organizations surveyed are currently targeting tactical benefits such as improving efficiency / productivity (56%) and/or reducing costs (35%). Also, 91% said they expect generative AI to improve their organization’s productivity, and 27% expect productivity to increase significantly. A smaller percentage of organizations reported targeting strategic benefits such as innovation and growth (29%).

This is consistent with past technology adoption patterns. Initially, most organizations logically focus on incrementally improving their existing processes and capabilities—capturing value from low-hanging fruit while building knowledge, experience and confidence with the new technology. Later, they expand or shift their focus to improvements that are more innovative, strategic and transformational—using the new technology to drive growth and competitive differentiation and advantage through capabilities that simply weren’t possible before.

Most organizations are primarily relying on off-the-shelf generative AI solutions.

In line with their current emphasis on tactical benefits from generative AI, the vast majority of respondents were currently relying on off-the-shelf solutions. These included productivity applications with integrated generative AI (71%); enterprise platforms with integrated generative AI (61%); standard generative AI applications (68%); and publicly available large language models (LLMs) (56%), such as ChatGPT.

Reliance on standard, off-the-shelf solutions is consistent with the current early phase of generative AI adoption, which is primarily focused on improving the efficiency and productivity of existing activities. However, as use cases for generative AI become more specialized, differentiated and strategic, the associated development approaches and technology infrastructure will likely follow suit.

How can my organization build generative AI expertise when things are moving so quickly?

In the race to deploy generative AI solutions, organizational attributes such as adaptation, experimentation and agility will be critical as new models, capabilities and use cases emerge. The key is to maintain a beginner’s mindset—the belief that no matter how expert you think you are, there will always be much more to learn— even as your experience grows. Careful coordination across your organization will be needed to successfully shepherd generative AI transformation in the face of rapid change. Work to improve generative AI literacy throughout your organization, and lead using a cross-disciplinary approach.

Full report is available here: State of Generative AI in the Enterprise 2024 | Deloitte US