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


  • Data privacy, regulations, and IT capabilities hinder widespread generative AI adoption in businesses.
  • Despite high expectations, only 9% of businesses significantly use generative AI.  
  • IT resources, investment budgets, and governance frameworks pose obstacles to rapid generative AI deployment.

A recent global survey conducted by Telstra and the MIT Technology Review Insights has shed light on the slow adoption of generative AI in businesses, despite the technology’s widespread hype and expectations. Surprisingly, only 9% of more than 300 business leaders worldwide were found to be heavily utilizing generative AI, a stark contrast to the optimism surrounding its potential.

The survey report identified several key obstacles preventing the widespread adoption of generative AI across various industries. Data privacy, regulations, and IT infrastructure emerged as the primary barriers, highlighting the challenges businesses face in implementing this cutting-edge technology.

Stela Solar, Inaugural Director at Australia’s National Artificial Intelligence Centre, emphasized the misconception about the ease of running mature, enterprise-ready, generative AI. She emphasized the need for companies to improve data quality, privacy measures, AI skilling, and implement safe and responsible AI governance organization-wide.

Regulatory challenges and data privacy concerns

One of the significant hurdles identified in the survey is the need for robust governance frameworks and security procedures to mitigate risks associated with generative AI. Laurence Liew, director of AI innovation at AI Singapore, stressed the importance of establishing clear governance frameworks and security procedures for AI models during the launch of the MIT report.

Liew highlighted the necessity for businesses to ensure appropriate governance is in place and that internal documents are properly segmented or secure. He emphasized the need to avoid scenarios where AI models could be tricked into disclosing private information, such as employees’ salaries.

IT infrastructure and investment hurdles in Adoption

The survey also revealed that IT resources and capabilities, as well as investment budgets, posed significant obstacles to the rapid deployment of generative AI. Less than 30% of the respondents expressed confidence in their company’s IT attributes to support the quick adoption of generative AI. Furthermore, 56% of the respondents stated that their IT investment budgets limited the implementation of generative AI.

Despite the slow adoption rate, the survey findings indicated that most business leaders anticipate generative AI to be used by more than twice as many business functions or general purposes by 2024. Early adopters in 2023 primarily used the technology for automating repetitive, low-value tasks, as they required less human supervision.

By 2024, respondents expect to implement generative AI in various areas, including customer service (77%), strategic analysis (74%), product innovation, supply chain logistics, and sales. However, the report noted that these plans might be high on “ambition and hubris” due to the obstacles mentioned earlier.

As the generative AI ecosystem continues to evolve, businesses must navigate the challenges of data privacy, regulatory compliance, and IT infrastructure limitations. Addressing these issues will be crucial for the widespread adoption and successful integration of this transformative technology into various business operations.

The survey highlights the need for businesses to prioritize investments in IT resources, data quality, and AI governance frameworks to unlock the full potential of generative AI. By overcoming these barriers, companies can harness the power of this technology to drive innovation, enhance customer experiences, and gain a competitive edge in an increasingly digital landscape.

Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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John Palmer

John Palmer is an enthusiastic crypto writer with an interest in Bitcoin, Blockchain, and technical analysis. With a focus on daily market analysis, his research helps traders and investors alike. His particular interest in digital wallets and blockchain aids his audience.

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