The democratization and acceleration of generative Artificial Intelligence (AI) began in the business-to-consumer (B2C) domain with the introduction of popular applications such as ChatGPT and Stable Diffusion. However, the potential economic impact of generative AI goes far beyond the B2C market. According to ABI Research, a global technology intelligence firm, generative AI is expected to contribute over US$450 billion to the enterprise market across twelve different verticals in the next seven years.
Numerous use cases for generative AI already exist within these enterprise verticals, and they can be categorized into three distinct waves of adoption based on accuracy, performance, and enterprise readiness. 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 getting initiatives to market faster, social media managers are more successfully deploying material with more localisation, and schools are already crafting a more tailored 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 most significant value creation, however, will come with the third wave of enterprise adoption. “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 certain verticals may not be significantly impacted until the market matures, this does not imply that no sector has viable use cases now. With enough human oversight, generative AI may be used to boost staff productivity across most, if not all, company operations.
Despite the exciting prospects of generative AI in the enterprise market, many businesses lack a clear corporate strategy for its implementation. Currently, individual business units are independently exploring ways to deploy generative AI, leading to potential fragmentation of business processes. To avoid this, a more deliberate and measured approach to enterprise deployment is necessary. This involves formulating a central corporate strategy for generative AI usage, including employee guidelines, governance policies, legal considerations, 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.
Although some multinational corporations (MNCs) have already established strong partnerships with vendors, and startups have quickly utilized isolated tools for content generation, the majority of the market is still in the early stages of exploring various use cases and deployment options for generative AI in the enterprise setting.
“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.
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