Findings from a new report indicate 85 percent of businesses see generative AI as important and plan to explore its applications within the next 24 months, while remaining wary of its risks.

Information Services Group’s “State of Applied Generative AI Market” report indicates that “rather than taking a “blank slate” approach, companies are asking their providers to devise ways that generative AI can be applied to providers’ existing services, such as call center operations.”

“Our research shows a real sense of urgency in the market,” said Prashant Kelker, partner and chief strategy officer with ISG, a global technology research and advisory firm. “However, despite the top-down imperative to embrace generative AI, most enterprises lack the focus to identify the right use cases. Right now, the market is being driven by specialist providers that are actively engaging with enterprises to brainstorm and co-create innovative solutions.”

Enterprises currently lack an AI architecture to support generative AI at scale, Kelker added.

As a result, early generative AI applications have been focused on creating domain-specific models built on proprietary datasets, with the intent to expand the datasets to “improve model training, developing customized adoption platforms, and creating solutions that unite analytics, AI and generative AI.”

“The initial focus for generative AI is on knowledge management, the ability to extract data from vast unstructured data sources for business decision-making, and functional process optimization, in areas such as marketing and sales, finance, HR, IT and DevOps,” said Kelker. “As enterprises grow more comfortable with generative AI, and use cases become more mature, companies will begin to imagine more transformative possibilities leading to new products and service offerings and complete business transformation.”

There are hurdles enterprises will need to overcome, according to the ISG report, namely security, copyright issues, ethical considerations and legal concerns.

“Enterprises are cautious about pushing the capabilities of generative AI too far, too soon – especially in customer-facing interactions,” said Kelker. “The quality of legacy data is an issue, which may be addressed by using synthetic data, as are so-called AI data hallucinations caused by missing or inaccurate data. Enterprise leaders also want to see clear ROI for their investments before proceeding. Then, of course, there are the security, legal and ethical implications. Guardrails will need to be established before generative AI can be adopted at scale.”

Banking and insurance are the leading industry for generative AI adoption, the report noted.

Financial services account for 24 percent of total use cases, followed by manufacturing (14 percent), healthcare and pharma (12 percent) and business services (11 percent).

When it comes to mature use cases, defined by ISG as those already in progress, with well-defined key performance indicators and return on investment, business services leads the way, at 39 percent of mature use cases. This is driven primarily by code-generation use cases, ISG reported, accounting for half the use cases in this sector.

From a functional perspective, the findings indicate that predictive analytics is the top use case, with 57 percent of all mature use cases, followed by code generation or DevOps (50 percent), data extraction and analysis (30 percent) and performance analysis (24 percent).