Energized by the hype around generative AI, enterprises are aggressively pursuing practical applications of this new technology while remaining cautious about the risks, a new research report from Information Services Group, a leading global technology research and advisory firm, has found.
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“Enterprises are cautious about pushing the capabilities of generative AI too far, too soon – especially in customer-facing interactions”
ISG presented the findings of its ISG State of Applied Generative AI Market report here today at the 2023 ISG Sourcing Industry Conference (SIC), the industry’s premier annual event for service and technology providers. The first-ever report details generative AI trends, use cases, solutions and challenges, and offers data-driven insights and actionable recommendations for adopting generative AI at scale.
ISG research shows 85 percent of companies surveyed believe investments in generative AI within the next 24 months are important or critical. However, 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. “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.”
Kelker said enterprises currently lack an AI architecture to support generative AI at scale. Early efforts to apply generative AI are focused on creating domain-specific models built on proprietary datasets, further expanding those datasets to improve model training, developing customized adoption platforms, and creating solutions that unite analytics, AI and generative AI.
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“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.”
Before they make that leap, the ISG report notes the hurdles enterprises need to overcome – include 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.”
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