AI value gap widens even as enterprise spend doubles

Trailblazers extract 2–3x more value as most firms mistake AI activity for strategy.

Enterprise investment in artificial intelligence (AI) has doubled year on year, yet Boston Consulting Group (BCG) warned the gap between organisations extracting real value and those that are not is widening.

Speaking at the Singapore Business Review Technology Enterprise Summit, BCG Managing Director and Partner Srihari Chakarajan identified a cohort of companies, those the firm classifies as “trailblazers”, that are extracting two to three times more value from AI than their peers. The divergence, he said, comes down to five organisational disciplines, one of which is strategic clarity.

“The companies pulling ahead are realising two to three times more value from AI than those lagging behind,” BCG said in research presented alongside Chakarajan’s remarks. “Strategic clarity starts from the other end. Where does AI change how we compete, and what has to work differently inside the business to get there?”

By BCG’s data, the overwhelming majority of organisations say they will continue AI investments even without a clear payoff this year. AI has also climbed from 30th place to the top 10 in BCG’s survey in just two years. Chakarajan said he would not be surprised to see it enter the top five in the next edition, with a path to the top three shortly after.

Chakarajan illustrated the dangers of unfocused investment with an example from a bank he had advised. What began as a tightly scoped initiative covering three clearly defined AI priorities eventually expanded as individual departments lobbied for their own use cases.

“Eventually, there were 25 programmes that were started,” he said. “You end up doing everything, which means a lack of clarity.”

The result, he argued, is that organisations with strong AI capabilities but poor strategic focus still underperform. The fix is not simply picking fewer projects, but thinking in terms of a structured portfolio: no-regret moves for certain-value applications, flexible options that preserve infrastructure optionality as the technology evolves, and asymmetric bets, meaning high-risk, high-upside initiatives where failure is affordable.

The right mix depends on risk appetite. Conservative organisations should direct 60 to 70% of AI investment toward no-regret moves, with the remainder split between the other two categories.

Trailblazers also spend more in absolute terms, Chakarajan noted, but do so with strategic intent. 
“Despite not having absolute certainty over value realisation, a lot of the ones who are actually delivering value and uptake invest a lot more,” he said. “But they are not putting in money without intention.”

Change management, Chakarajan said, is the most common failure point in enterprise AI programmes. BCG’s research found that 40% of employees say their CEO is not transparent enough about the organisation’s AI intentions. That trust deficit makes programme execution significantly harder.

“If you cannot bring the people through the AI change, then every programme that you try to execute, you’re not going to get the momentum from the people,” he said.

Only around half of organisations are able to explain clearly how AI can be put to work, Chakarajan added, underscoring the case for role-tailored literacy programmes. BCG has implemented this internally, running differentiated AI fluency tracks for consultants, researchers, HR staff and partners. More advanced tools are gated to those who have completed the relevant training tier.

The fifth discipline separating trailblazers from laggards is rigorous tracking and controls. Chakarajan pointed to organisations spending heavily on AI tools with no mechanism to verify the return, as well as those that built capable platforms but failed to put governance structures in place before deployment.

One case involved an insurer that spent $25.6m (US$20m) building a platform enabling business users to configure and deploy AI agents, only to lock access for everyone because the organisation was not confident in its controls. The platform sat unused. Organisations that think about controls from day one, he said, consistently deliver greater value as a result.

Trailblazers, by contrast, measure every metric and use that data to demonstrate, rather than assume, that AI programmes are delivering. For organisations still on the wrong side of the value gap, Chakarajan said the path forward was clear.

“Make AI your big strategic priority,” he said. “Go after these programmes as an investor would. Have a diversified portfolio... and make sure you have all the tracking mechanisms in place to be able to get value out.”

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