Asia-Pacific Organizations Struggle to Harness AI Benefits, Forrester Predicts
According to research firm Forrester, only a third of organizations in the Asia-Pacific region will be able to fully benefit from artificial intelligence (AI) due to a variety of obstacles. Despite the increasing interest in AI across the business landscape, many organizations in this region are held back by their aversion to risk and subpar data management capabilities.
Forrester’s 2024 predictions highlight that just 30% of organizations in Asia-Pacific have the necessary IT practices to leverage the benefits of AI, which include improved operational resilience, enhanced customer experience, and innovative business models. The remaining organizations are hindered by a risk-averse culture and inadequate data management capabilities.
While many Asia-Pacific firms see generative AI as a tool to boost efficiency, many will encounter obstacles in the form of an overly cautious work culture and gaps in data management capabilities, explained Frederic Giron, Forrester’s Vice President and Senior Research Director.
Giron noted that the most prepared organizations in the region, constituting about 30% of firms, are better equipped to maximize the potential of AI and are focused on using generative AI to evolve their business models. However, he emphasized that this evolution will be a gradual process rather than an overnight success story in Asia-Pacific.
In addition to the challenges associated with AI adoption, Forrester identified two other key forecasts for the region. Firstly, only a quarter of multinational corporations operating in Asia-Pacific will prioritize customer trust. However, only a mere 5% of these companies are expected to have established measurable metrics to measure and uphold this trust, which is currently declining.
Secondly, companies in the region will struggle to operationalize customer trust, with few taking tangible efforts to integrate it into their corporate culture. However, by the end of 2024, Forrester predicts that 25% of large enterprises in Asia-Pacific will advocate their commitment to earning customer trust.
Despite these challenges, Forrester predicts that customer experience will improve as generative AI is adopted in the backend, enabling customer service agents to respond to queries faster and more efficiently. This will result in issues being resolved on the first contact, making customers feel heard.
Forrester also anticipates that advertising agencies will invest in custom AI applications on behalf of organizations. The top 10 advertising agencies in the region are set to collectively spend $50 million in partnerships next year to build these applications, which will allow their clients to scale customized marketing campaigns.
Furthermore, the implementation of AI initiatives in businesses is projected to lead to a 50% improvement in productivity and problem-solving. Generative AI is expected to enhance productivity across all IT roles, including developers. By investing in this technology, organizations can enhance employees’ problem-solving capabilities by up to 50%.
However, the adoption of prompt engineering services by enterprises will be limited. Despite the efforts of cloud hyperscalers to introduce such services, 80% of businesses will add prompt engineering talent internally to drive model grounding and value.
Forrester concludes that Asia-Pacific is entering a year of exploration and potential growth, with generative AI at the focal point. As the promise and potential of generative AI continue to inspire technology and business leaders in the region, there is a growing trend to fuse AI with transformation efforts to drive business outcomes.
In summary, although AI holds significant potential for the Asia-Pacific region, there are substantial hurdles to overcome in terms of risk aversion and data management capabilities. With careful navigation and a focus on building trust with customers, organizations can gradually unlock the benefits of AI and drive successful outcomes in their respective industries.
