In the Post-ChatGPT Era, Is AI Actually Making Us More Productive?
In the wake of ChatGPT’s rise, boardrooms around the world are racing to integrate AI into corporate workflows. Generative AI is now being seen as a game-changer for automating service and knowledge-based tasks — from call centers to consulting firms.
But is faster work really the same as more productive work?
Ramine Tinati, head of Accenture’s APAC Center for Advanced AI, raised this question during a panel at the Fortune Brainstorm AI conference in Singapore last week. “If you give employees a tool to do things faster, they do it faster,” he said. “But are they more productive? Probably not, because they do it faster and then go for coffee breaks.”
Tinati argued that true productivity gains only come when organizations rethink the nature of work itself. “If you reinvent the work, then suddenly those coffee breaks don’t become meaningful anymore — because you're doing something else,” he added. He also suggested that some Asian companies are lagging in AI adoption precisely because they’re not approaching it as an opportunity to fundamentally transform workflows.
AI in Practice
AI isn’t new to the workplace. Companies have been using various forms of automation for years, long before ChatGPT came on the scene in late 2022.
At Jabil, a manufacturing solutions provider, Chief Information Officer May Yap described how AI has been used to support their “Golden Eye” program — a team responsible for visually inspecting electronics for defects. The repetitive nature of the work, coupled with long shifts, made human error inevitable. By augmenting this process with AI, Jabil has been able to reduce mistakes and improve inspection quality.
Singapore’s Home Team Science and Technology Agency, which supports national security efforts, has also seen significant benefits from AI. Chief AI Officer Chee Wee Ang reported a 200% improvement in certain information extraction processes, delivering strong returns on investment. More importantly, he noted that AI is enabling capabilities that didn’t exist before — such as handling new types of crime and emergencies across the Home Team’s ten departments, including police, emergency response, and immigration.
Reskilling, Not Replacing
Still, the growing use of AI brings understandable concerns about job displacement. Many employees fear they’re unknowingly training the AI systems that could eventually replace them.
The panelists agreed that reskilling is essential. Rather than replacing workers, AI should shift them into adjacent roles with new responsibilities. Yap emphasized that transformation can be intimidating, but the goal at Jabil is to enhance—not replace—the human workforce. She noted that while some tasks can be automated, core skills and strong leadership can’t be replicated by AI.
Ang shared that finding AI talent in Singapore remains a challenge. His team often hires individuals with related skill sets, even if they lack direct experience in generative AI. Another constraint: the agency must rely on on-premise computing due to the sensitive nature of their work, limiting access to powerful GPUs.
Despite these hurdles, Tinati remains optimistic. “AI is uplifting workers’ skills,” he said. “They’re moving into supervisory roles or learning new capabilities that support higher-order tasks in the development cycle.”