Survey Reveals Slow Adoption of Generative AI in Business, Despite High Expectations

Survey Reveals Slow Adoption of Generative AI in Business, Despite High Expectations

A global survey shows only 9% of businesses significantly use generative AI, citing data privacy and IT challenges as major adoption barriers.

According to a recent survey, businesses’ adoption rate of generative AI has not kept up with the hype surrounding the technology. Data privacy, regulations, and IT infrastructure are the main obstacles preventing the technology from being widely used.

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Only 9% of more than 300 business leaders worldwide were found to be heavily utilizing AI, according to a survey conducted by Australia-based Telstra and the MIT Technology Review Insights.

The MIT report

Although most leaders were optimistic about AI’s potential and expected to widen its usage, even the early adopters of this technology have deployed it for limited business areas. 

In the survey report, Stela Solar, Inaugural Director at Australia’s National Artificial Intelligence Centre said that there is a misconception about how easy it is to run mature, enterprise-ready, generative AI. She added that its adoption may require companies to improve data quality and capability, privacy measures, AI skilling, and implement safe and responsible AI governance organization-wide. 

She also stated that there are surrounding elements like the app design, connection to data and business processes, corporate policies, and more that are still needed.

However, most business leaders said they anticipate generative AI to be used by more than twice as many business functions or general purposes by 2024. 

According to Chris Levanes, head of South Asia Marketing at Telstra, early adopters in 2023 primarily used the technology for automating repetitive, low-value tasks because they required less human supervision.

Respondents add their voice

By 2024, as many as 85% of the respondents anticipate using generative AI for these low-value tasks; 77% expect to implement it in customer service, and 74% for strategic analysis. 

Other areas for potential deployment include product innovation, supply chain logistics, and sales. 

However, the report noted some obstacles to a widespread rollout of generative AI next year, especially IT resources and capabilities, and labeled these plans as high on “ambition and hubris.

Less than 30% of the respondents said that their company’s IT attributes will allow generative AI to be adopted quickly, and those rolling out generative AI have even less confidence in their IT infrastructure to support the new technology. 

Conversely, 56% of the respondents stated that the implementation of generative AI was limited by their IT investment budgets.

Up to 77% of respondents identified regulation, compliance, and data privacy as the main obstacles to the generative AI ecosystem’s rapid adoption. These issues have been a major concern since the technology gained notoriety at the end of 2022 with the release of OpenAI’s well-liked ChatGPT.

Laurence Liew, director of AI innovation at AI Singapore, stressed to the media during Monday’s launch of the MIT report that establishing clear governance frameworks and security procedures for AI models is necessary to mitigate these risks.

Liew said that companies must ask if they have the appropriate governance in place and if their internal documents are properly segmented or secure.  He noted that businesses will want to avoid having AI models that can be tricked into disclosing private information such as employees’ salaries. 

Image credits: Shutterstock, CC images, Midjourney, Unsplash.

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