Despite the buzz surrounding generative artificial intelligence (AI), its adoption in businesses is not as widespread as one might expect. A recent survey conducted by MIT Technology Review Insights and Telstra, an Australian telecommunications company, reveals that only 9% of over 300 global business leaders are significantly utilizing AI. The main obstacles to its adoption include data privacy, regulation, and IT infrastructure.
Stela Solar, the Inaugural Director at Australia’s National Artificial Intelligence Centre, highlighted in the survey report that there is a common misunderstanding about the ease of implementing mature, enterprise-ready, generative AI. She emphasized that for successful adoption, companies need to enhance data quality and capability, privacy measures, AI skilling, and implement organization-wide safe and responsible AI governance. She also pointed out the necessity of other elements such as app design, connection to data and business processes, and corporate policies.
Future Prospects and Challenges
Despite the current slow adoption, business leaders are optimistic about the future of generative AI. They anticipate that the number of business functions or general purposes for which generative AI will be deployed will more than double by 2024. Chris Levanes, head of South Asia marketing at Telstra, noted that early adopters in 2023 primarily used the technology for automating repetitive, low-value tasks that require less human supervision.
The survey also revealed that as many as 85% of the respondents expect to use generative AI for these low-value tasks by 2024, with 77% planning to implement it in customer service and 74% for strategic analysis. Other potential areas for deployment include product innovation, supply chain logistics, and sales.
However, the survey also identified several challenges to a widespread rollout of generative AI next year, particularly IT resources and capabilities. Less than 30% of the respondents considered the IT attributes at their companies as conducive to a rapid adoption of generative AI. Furthermore, 56% of the respondents identified their IT investment budgets as a limiting factor in rolling out generative AI.
Regulation, Compliance, and Data Privacy Concerns
Regulation, compliance, and data privacy emerged as significant barriers to the rapid deployment of generative AI, with 77% of the respondents citing these as key concerns. These issues have been at the forefront since the technology gained prominence at the end of 2022 following the release of Open AI’s popular ChatGPT. The technology has since led to numerous lawsuits related to the copyrights of AI-generated materials and sensitive information leaks and security issues at major companies.
Laurence Liew, director for AI innovation at AI Singapore, emphasized the need for well-established governance structures and security protocols for AI models to address these risks. He also stressed the importance of robust internal cybersecurity measures, with a slight majority of respondents admitting that their cybersecurity measures are only modestly capable of supporting a generative AI rollout.
Skills Gap and Future Outlook
Another barrier to generative AI adoption is the lack of relevant generative AI skills. Companies are concerned about not having the right talent internally and the unavailability of such talent in the market.
Despite these challenges, the survey reflected overall positive sentiments about the future role of generative AI in business. While 60% of respondents expect generative AI to substantially disrupt their industry in the next five years, 78% see it as a competitive opportunity. Only about 8% see it as a threat.
Geraldine Kor, managing director of South Asia and head of global enterprise at Telstra International, believes that while building generative AI solutions that can responsibly handle large datasets and contextualize them for business is extremely challenging, it will soon be well worth the investment. She stated that successful implementation of generative AI will be a game-changer for most organizations and will distinguish leaders from followers.
According to a report from McKinsey released last year, generative AI is expected to have its biggest impact on sales, marketing, consumer operations, software development, and R&D sectors, potentially adding an estimated $4.4 trillion annually to the global economy.
