For true AI transformation, go beyond deployment and using tools
Roundtable panellists say implementation must be accompanied by job redesign, training and complementary skills
While businesses are deploying artificial intelligence and increasingly utilizing AI tools, true transformation remains elusive, according to participants at a recent roundtable discussion in Singapore. The event, titled "Singapore’s AI Future: Built on tech, won on people," was organized by The Business Times in partnership with Accenture.
Speakers emphasized the need for employers to create an environment that enables the scaling of AI technology, as well as for employees to combine AI use with domain knowledge and core skills.
According to an Accenture report, 90% of organizations have begun implementing AI, yet nearly half (46%) of technology leaders claim their company has yet to redesign any role. Additionally, 48% of entry-level workers express AI confidence, but most acknowledge a beginner-level understanding of the skills employers require.
A survey conducted by the Singapore Business Federation (SBF) on approximately 500 companies revealed that only 30% of participants have adopted AI. Adoption rates vary significantly among company sizes, with large companies at 76%, medium-sized at 62%, and small companies at just 24%, according to SBF CEO Kok Ping Soon.
Kok highlighted that even among companies that have implemented AI, many rely on off-the-shelf tools, with only about 4% deeply integrating the technology into their processes. Mark Tham, country managing director at Accenture Singapore, provided several examples of successful AI transformation. For instance, a major port operator utilized AI to automate cranes, subsequently redesigning crane operators to specialize in controlling fleets.
Accenture collaborated with Singapore's National Library Board on the "Albatross File" exhibition, which employed AI to create an interactive "chatbook" allowing visitors to ask questions and learn history beyond traditional classroom settings.
Tham identified several reasons why organizations struggle to scale AI effectively. These include the lack of a robust data foundation, technical debt, inorganisation, and the need to address the "joints" between people, data, workflows, and models. He also noted that a company's ability to manage data is a key factor in scaling AI, citing a local third-party logistics company that redesigned core processes and integrated a digital system, resulting in a 20% revenue increase, 30% profit boost, and a 15-minute reduction in route planning time.
To achieve successful AI transformation, Kok emphasized the importance of focusing on workforce transformation alongside investment in AI. He pointed out that many companies begin AI adoption with their IT departments but require business owners and human resource leaders to understand the necessary process changes and workforce capabilities. Moreover, Tham stressed the need for a long-term commitment, as productivity and profit improvements typically take four years or more to materialize after AI adoption.
Written by urgent.news from The Business Times - Singapore's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
