Real-World AI

Nearly two years after the widespread adoption of generative AI with the launch of ChatGPT, the technology is shifting from experimental phases to real-world implementation.

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A recent survey by TechTarget’s Enterprise Strategy Group highlights this growing trend, revealing that generative AI adoption has significantly increased over the past year. The firm surveyed 832 professionals globally and found that the use of generative AI is expanding across sectors like software development, research, IT operations, and customer service.

“We’re in the acceleration phase,” noted Mark Beccue, an analyst at Enterprise Strategy Group and author of the survey, during an appearance on the Targeting AI podcast.

According to the survey, there is no singular use case driving the adoption of generative AI. Instead, organizations are exploring multiple applications while facing challenges, such as the need for enhanced infrastructure.

“Organizations feel infrastructure changes are necessary before fully proceeding with generative AI,” Beccue said. This may involve investing in enterprise-level platforms or new development tools, all aimed at facilitating AI application development.

Additionally, there’s no clear consensus on which AI models—open or closed source—best suit organizational needs. “It’s likely a combination of both,” Beccue explained. “Companies are realizing no one model meets all their needs, so they’re evaluating what works best in specific scenarios.”

Companies that have seen early success with generative AI are those that invested in AI technologies well before ChatGPT made waves. Beccue pointed to companies like Adobe, ServiceNow, and Zoom, which had already been leveraging machine learning, natural language understanding, and process automation for years.

“They recognized the potential for AI to enhance their operations and were well-prepared when generative AI gained mainstream attention,” Beccue added.

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