Generative AI will Create at Least US$450 Billion in the Enterprise Market Across 12 Verticals Over the Next 7 Years, But Sizeable Commercial Challenges Remain

The democratization and acceleration of generative Artificial Intelligence (AI) originated in the business-to-consumer (B2C) market with the release of popular applications like ChatGPT and Stable Diffusion. But the B2C market will barely scratch the surface of generative AI’s potential economic value. Global technology intelligence firm ABI Research expects that generative AI will add more than US$450 billion to the enterprise market across twelve different verticals over the next seven years.

Generative AI already has hundreds of use cases across these enterprise verticals. But accuracy, performance, and enterprise readiness will mean that use cases will come in three distinct waves. Reece Hayden, Senior Analyst at ABI Research, says, “Content-heavy verticals like marketing and education are already seeing disruption across a range of job roles in the first wave of adoption.” Advertisers are bringing projects to market more quickly, social media managers can deploy content more effectively with greater localization, and teachers are already developing a more personalized curriculum.

“The current wave of adoption will not be revolutionary. Rather, it will have an internal focus by augmenting employee productivity by providing generative tools,” Hayden says. “The second wave will have a larger impact on external services. As gen AI becomes more mature with greater trustworthiness, enterprises will be able to start building products or services around it. Service industries like healthcare and legal will increasingly leverage generative AI to build mission-critical services. For example, healthcare enterprises can leverage generative AI tools to manage patient health trends or build chatbots to answer healthcare questions.”

The third wave of enterprise adoption will be the most significant value creator. “We expect to see verticals like manufacturing and logistics leverage generative AI to automate and optimize processes. This will have a significant impact but also bring additional risks as hallucinations could have potentially dangerous consequences,” cautions Hayden. Although some verticals will not be widely impacted until the market matures, it does not mean that each vertical does not have practical use cases today. Generative AI with sufficient human oversight can be utilized to augment employee productivity across most if not all, business functions.

The outlook of generative AI for the enterprise market is undoubtedly exciting, but most are not in the best position as they lack a clear corporate strategy. Individual business units are currently looking at ways to deploy generative AI to augment operations. These isolated deployments will drive fragmentation between business processes. Avoiding this requires a more careful and measured approach to enterprise deployment with a central corporate strategy on generative AI usage, including employee usage, governance, legal approach, and expected business outcomes.

“Building a framework to support enterprise generative AI deployment is critical. For operational consistency, enterprises should adopt a common platform that includes foundation models, low/no code tools, guardrails, and curated data sets. This framework can then allow different business units to build highly contextualized, use case-specific models and applications,” Hayden recommends.

Generative AI in the enterprise market remains mostly nascent. Some Multinational Corporations (MNCs) have started building solid partnerships with vendors, while startups have quickly leveraged isolated tools to augment content generation processes. But most of the market is still exploring use cases and deployment options. “For this reason, it remains to be seen how the market develops, especially as global regulation comes into force over the next two years. But for now, given the use cases that have already been identified and the potential value on offer, ABI Research expects that generative AI will be ubiquitously deployed across verticals and integrated throughout most business processes over the next seven years,” Hayden concludes.

These findings are from ABI Research’s Generative AI Business Outcomes: Identifying Enterprise Commercial Opportunities application analysis report. This report is part of the company’s AI and Machine Learning research service, which includes research, data, and ABI Insights. Based on extensive primary interviews, Application Analysis reports present an in-depth analysis of key market trends and factors for a specific application, which could focus on an individual market or geography.