Most Organisations Still Fail to Capture AI Value Despite Soaring Adoption
Source: Fintech News SG
Despite 88% of organisations now using AI regularly, 60% report no material value from their investments. Only 5% of firms have achieved AI value at scale, generating 1.7x higher revenue growth and 1.6x higher EBIT margins.
A wave of new studies from Bain & Company, BCG, and McKinsey paint a stark picture of the AI adoption landscape: 88% of organisations now use AI regularly, up from 78% in 2024, yet 60% of companies report no material value from their investments. Only 5% of firms — described as "future-built" — have achieved AI value at scale, generating 1.7x more revenue growth and 1.6x higher EBIT margins compared to peers.
The data reveals what analysts are calling a "micro-productivity trap." Most organisations treat AI as a plug-and-play SaaS investment, using it to optimise existing offerings or automate current processes without rethinking the underlying workflows. Gains stall at the firm level due to tacit knowledge, manual handoffs, and legacy systems not designed for AI integration. Bain and OpenAI's joint framework recommends narrowing AI efforts to 4-5 critical domains and, crucially, redesigning workflows end-to-end rather than bolting AI onto existing processes.
The firms that do get it right see substantial returns. Bain's client data shows successful AI transformations delivering 10% to 25% EBITDA gains, with those gains continuing to scale. One Fortune 100 manufacturing client identified 14 discrete AI use cases across sales, engineering, and manufacturing — focused on a small subset — and is on track to realise approximately US$30 million in additional profit. The lesson is consistent across industries: value comes from reimagination, not addition.
Why it matters for Singapore: Singapore's economy, heavily reliant on financial services, logistics, and manufacturing, is particularly vulnerable to the micro-productivity trap. With EnterpriseSG and IMDA pushing aggressive SME digitalisation targets, the risk is that Singaporean businesses adopt AI tools at scale without redesigning the workflows they sit in. The Bain-BCG-McKinsey data offers a roadmap: focus AI investments on a narrow set of high-impact domains, measure outcomes rigorously, and invest in workflow redesign — not just software procurement.