@ the IERP® Global Conference, August 2024
The topic of discussion in this session focused on how organisations could manage AI to solve business problems, and develop training and awareness, thus enabling the organisation to earn more revenue, maximise profit, and minimise cost. The moderator was Prof Ts Dato’ Dr Husin bin Jazri, Director of Global Cyber Safety Alliance, Taylor’s University Malaysia; speakers were Lim Chee Gay, Group Chief HR Officer, TDCX, and Khim Tan, Former CHRO/Senior Leader of Banks and MNCs.
Tan said that the move from being knowledge- to skills-based entailed a shift in the way businesses operated. Companies which have embarked on skills-based operations have shown an increase in productivity of about 35%. Of the top 50 innovative companies in 2019, nine of the top ten were tech companies. “Organisations that are focused on digital skills will take the lead,” she said. “The skills which are really important are digital skills. Like it or not, AI and digitalisation are here to stay. Without digitalisation, companies will lag behind.”
While AI and digitalisation may be top of the agenda, data analytics is a close second. “It has been predicted that by 2030, the top skills…will actually be analytical skills and creativity,” she said. “You have the data; you must analyse it and convert it into something that can make a decision. The other thing is human centricity – the human element, the need for an element to actually be able to assess ethics.” With robots in the future possibly imbued with human skills, it will be critical for businesses to transform from being wholly knowledge-based to being skills-based.
Lim confirmed that with hiring, skills over knowledge was emphasised. “Today we are more into hiring skills,” he said. “We are more into skills-based development and skills-based talent management.” There were more models of coaching and mentoring, and training and development. “The learning framework is only 10% of knowledge sharing. But if there is no application learning or action plan, it’s only knowledge. What you take away is the most important. For performance management, the move is towards competency assessment instead of knowledge metrics,” he added.
Even top leadership and C-suite level positions are based on competency today. More companies also preferred project, skill or team-based structures, rather than the traditional functional or knowledge structures. This indicated that organisations were transforming from being knowledge-based to skills-based. However, he cautioned that companies wanting to transform must have the appropriate policies and SOPs in place, for their transformations to be aligned with – and that was another risk to face.
To a query on whether embedding AI in the syllabus for the younger generation was crucial to prepare individuals for what is coming, Tan said that countries in Europe had already implemented AI in their education systems. Also, some companies were already using facial recognition in research and targeted marketing. “If you don’t join the race, you will be out of it,” she said. “You have to learn how to use it.” Responding to a query about why AI is called artificial when it appeared more advanced, Lim said that its ‘intelligence’ was equal to that of humans.
“AI can replace humans when correcting mistakes in manufacturing (for example)…and has taken over some of the technician’s functions,” he said, but added that it was unable to replace humans completely; it takes over jobs so that humans can be more productive. “What makes us more productive is our ability to analyse the results of AI.” Generative AI can give quick answers, analyse and even produce an action plan, thereby making employees more productive; this allows humans to plan better, and take planning to the next level.
Noting that risk management was about how an organisation can anticipate change, Tan used the examples of two local banks in Malaysia to illustrate how AI can both support and be the change that is required. In their efforts to ‘humanise’ their financial services, both banks went to great lengths to implement digital functions but included training at all levels from the top down because they took the approach that an integrated approach could generate growth, safeguard the company, and allow for the management of new trends.
Other areas that need to be considered for risk management include ethics, privacy, data integrity, risk appetite and assessment. She said that Singapore had already established an AI Readiness Index to see how an organisation is ready for growth using AI, and how they are protecting their assets and data. Lim remarked that AI insights were now replacing direct observation, with generative AI capable of detecting overpayment process issues. “Generative AI can detect audit issues,” he said. “With generative AI, users now do not need to have knowledge of a domain to be effective.”
How should AI be managed when it comes to privacy, especially since it is programmed to collect all data? Tan said that this was where the human element should be applied; AI can only mimic human intelligence. “It is up to us to have a policy to say what you can or cannot do,” she said. “Be open to encourage adoption and use, but be wary about what it can do. If you use it for marketing, for example, there should not be bias towards one sector. AI helps, but we need the human brain, intellect and nuances, to decipher challenges, diagnose analytics, see trends and deduce other practices.”
Dr Husin suggested the formation of a regulating body to look into the emergence of new technologies to curb their abuse. “You need an AI commission to tap into AI machines to know if they are breaching privacy laws,” he said. “There will be rapid automation in the years to come, and human interaction may be too slow to address privacy issues. A regulatory body is necessary, maybe under the Ministry of Science, Technology & Innovation, to regulate the emergence of new technologies. Lim noted that the bias was already evident, in hiring processes for example, where AI tended to discriminate between candidates. “Diversity – ‘DI’ – will become key in years to come,” he said. “How do we ensure there is no bias against diversity? AI can go against DI.”
