Singapore firms spend on AI but miss productivity gains
Weak use-case selection and low employee trust are limiting productivity despite rising artificial intelligence investment.
Singapore companies are investing heavily in artificial intelligence, but many are failing to convert adoption into meaningful productivity gains as employees remain unprepared to use the technology for higher-value work.
Only 20% of organisations consider their workforce artificial intelligence-ready. Swagatam Basu, Senior Director Analyst, HR Practice at Gartner, said executive expectations have outpaced actual results, with leaders initially expecting productivity improvements of around 18%.
“Employees who are frequently using AI are only seeing a 3% increase in productivity right now,” Basu added.
He attributed the gap to organisations prioritising adoption over effective use. Employees are often required to use artificial intelligence before recognising its value, resulting in limited productivity gains and weaker employee engagement. Basu also warned that widespread use of personal artificial intelligence tools alongside enterprise platforms increases data privacy and intellectual property risks.
Adrian Choo, CEO and Founder of Career Agility International, said many organisations are introducing artificial intelligence without first identifying operational problems the technology is expected to solve.
“What we actually recommend is you have to look at the workflows. What are the bottlenecks? What are the challenges?” Choo said.
Rather than purchasing new platforms, he urged companies to evaluate existing workflows before deciding whether to use embedded artificial intelligence features, develop in-house solutions or acquire new products.
Both interviewees also highlighted employee trust as a barrier to adoption. Choo said some workers continue using personal tools because they have already trained them, whilst others avoid corporate systems for sensitive tasks because they fear their activity is being monitored.
Basu said organisations should shift their focus from measuring artificial intelligence adoption to applying it to critical business tasks. He also called for stronger governance, regular reviews of enterprise tools and greater psychological safety to encourage responsible use of approved systems.
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