Remember when software-as-a-service (SaaS) was the Next Big Thing? In the event, it took more than four years for SaaS to reach a 2 percent market share in the global enterprise software market. The current Big Thing, generative artificial intelligence (gen AI) reached that level in about a year. Looking ahead, gen AI is primed for 10 percent of related spending by 2028, or three times as fast as SaaS. McKinsey estimates gen AI will reach $175 billion to $250 billion by 2027 (up from $15 billion in 2023).
Gen AI: Opportunity or Challenge?
In short, disruption is coming for the enterprise software sector—a conclusion confirmed by a recent survey of 250 chief information officers (CIOs) and technology buyers. That disruption is likely to unleash a wealth of opportunities—and more than a few challenges.
For example, customers will look much harder at where they buy their software. As a result, we expect a significant increase in vendor switching, on the order of 5 to 10 percentage points—or double the current rate. A cohort of upstarts, familiar with the technology and emboldened by the lower costs of data migration, integration development, and user training, will be in position to challenge existing suppliers. Moreover, faster software development will allow competitors to replicate offerings quickly and inexpensively.
Every software category will be affected, although the degree and pace of change will differ. For example, gen AI-enabled automation is already up-ending customer service, as increasingly sophisticated gen AI chatbots become adept at answering queries. Ditto for enterprise automation categories, which will likely shift from legacy robotic process automation to hyper-automation platforms. For enterprise resource management (ERM), the potential to automate user workflows and leverage proprietary assets and insights is a little more remote. As for “expert software,” such as advanced engineering and design tools, gen AI could expand the user base. Finally, there could be a wave of business workflow automation enabled by “agentic AI”—meaning capabilities that go beyond existing foundation models and come closer to the way people think.
That is the reasoning behind the prediction of disruption. How should industry leaders react?
Plan for Disruption
First, don’t delay. While developing a long-term, comprehensive strategy is ultimately a good idea, it is not a reason not to dive right in. In a disruptive era, first movers put themselves in position to capture a disproportionate share of value. Caution, on the other hand, could leave some previously established leaders behind.
Second, deploy gen AI for software development. This may sound obvious; getting it right, however, is not. When it comes to complex tasks, for example, the gen AI time premium is small, about 10 percent, due in large part to lack of familiarity with the programming framework. In terms of expediting repetitive work and writing the first draft of a new code, on the other hand, it excels. Indeed, some routine coding tasks can be done twice as fast with gen AI. Getting the best out of gen AI is not a matter of a tweak here and there; software companies will need to rethink everything from training and coaching to use case selection and risk controls.
Third, be imaginative. By that, we mean canvassing the evolving landscape from 10,000 feet up. If gen AI is going to reshape every software category—and it is—it’s important to consider the broad, long-term implications in terms of customer needs, new business opportunities, and investment. With gen AI-related revenues rising so fast, as well as the number of use cases, it’s important to ensure that this potential is supported through research and development.
Conclusion
Finally, remember that gen AI is a team sport. Capturing its value could mean new pricing and hiring norms; it will certainly require figuring out how to use proprietary data and how to meet new customer demands. In other words, the whole organization will need to be involved, from the CEO down.
Software is not the only sector that gen AI will change; already it is at work in areas ranging from fashion to finance. When McKinsey analyzed a range of industries last year, it estimated that gen AI could generate as much as $4.4 trillion a year in added value globally. Since then, uptake has surged—in more markets, more industries, and in more ways.
In the enterprise software sector, gen AI could boost overall growth rates six percentage points in the next couple of years. But potential and activity is all well and good: for gen AI to create value means patient, systematic—and fast—effort.
Want to learn how to value your AI business? See this complete guide. Read more about the Artificial Intelligence industry outlook in the 2024 Market Reports published by FE International.
Jeremy Schneider is a senior partner in McKinsey & Company’s New York office and global co-head of the software practice. Tejas Shah is a partner in New York.
