Organisations in Asia-Pacific are moving beyond measuring artificial intelligence (AI) by time saved and are increasingly seeking differentiated insights and competitive advantages generated by AI.

Jin Kim, Co-founder and Head of Forward Deployed Engineering at New York-based financial AI company LinqAlpha, said to TNGlobal regarding the World AI Day (July 16).

Kim said the next wave of enterprise AI will shift from productivity gains toward augmenting each individual’s specific strengths. Unlike earlier technologies that primarily benefited specialized teams, generative AI has the potential to improve the output of every knowledge worker, Kim said. The future path is AI acting as a “second brain” that helps individuals think more deeply and connect information more effectively.

Kim said the greatest business value from AI in the region is currently being generated through content generation and workflow automation, particularly for front-office roles in sales, trading, research, and wealth management. Rather than replacing professional expertise, AI can accelerate knowledge-intensive tasks, including synthesizing research, preparing client materials, and processing large volumes of market data, with some workflows reduced to roughly one-seventh of their previous time.

Regarding advantages for organizations to move beyond experimentation, Kim said successful adoption requires abandoning assumptions from the traditional machine learning era. With generative AI, the most effective implementations come from rapid experimentation and continuous iteration rather than attempting to perfect solutions upfront.

Dedicated internal champions who drive adoption, educate colleagues, and identify high-impact use cases are also critical, he added. Organizations that give business users room to experiment can move from proof-of-concept to production more quickly.

On governance, Kim said it has emerged as the defining challenge as AI adoption scales, extending beyond compliance to include model selection, AI budget allocation, guardrails, model quality evaluation, and responsible use across the organization. Many organizations remain in the early stages of identifying the most valuable use cases, and that the best ideas often come from end users rather than top-down planning.

Creating safe experimentation environments is more valuable at this stage than prioritizing cost optimization or restricting usage, Kim said.

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