Telstra International, in conjunction with MIT Technology Review Insights (MITTR), has today released a joint report entitled "Generative AI: Differentiating Disruptors from the Disrupted". The study offers a comprehensive vision into the perspective of top executives spanning Asia Pacific, the Americas, and Europe regarding adoption, use, and barriers to Generative AI within diverse industries including IT, logistics, and financial services.
According to the report, a substantial 78% of surveyed businesses perceive generative AI as a competitive opportunity, while 65% are actively considering creative ways to utilise this AI technology to reveal unseen prospects from data. Interestingly though, less than 30% believe they have the adequate level of technology, funding, culture, and skills to facilitate its swift adoption. Furthermore, those with greater experience in the deployment of generative AI express lesser confidence in the readiness of their IT capabilities.
Geraldine Kor, Managing Director of South Asia and Head of Global Enterprise at Telstra International, commented on this paradox and stressed the crucial role of data in decision-making processes. She noted, "being able to process data to drive informed real-time or near real-time business decisions is paramount." Notwithstanding its potential, per Kor, the path to effective adoption is fraught with complexities, particularly in handling large datasets, contextualising data for business value, and ensuring responsible and ethical AI application.
Within the report, several salient findings stand out. A significant 60% of executives anticipated a substantial disruption in their industry over the next five years due to generative AI technology. Despite these expectations, many companies (20%) have merely experimented with or restrictedly adopted generative AI in 2023. However, companies plan to double down on their commitment to this technology next year, appreciating its potential benefits across areas including customer experience, strategic analysis, and product innovation.
Yet, the reasons preventing rapid adoption of this recognisably disruptive technology extends beyond IT capabilities. A significant 77% of respondents reported that their regulatory, compliance, and data privacy environment potentially hindered swift AI adoption. For 56%, IT investment budgets presented another obstacle. In contrast, early generative AI adopters doubled down on the competitive environment enabling accelerated adoption, along with openness to innovation and better awareness of the talent limitations.
Laurence Liew, Director of AI Innovation at AI Singapore, provided additional context on the state of generative AI in Singapore, underscoring the constraints companies face in obtaining necessary hardware. Along with these issues of hardware, data quality and talent shortages remain major bottlenecks to productive deployment. He reassured, however, that "at AI Singapore, we try to address the issues of AI talent with programmes such as the AI Apprenticeship Programme (AIAP) and the LLM Application Developer Programme (LADP)," which are both designed to address immediate business problems using AI while also helping to build a pipeline of AI talents.