For years, conversations about artificial intelligence in boardrooms have followed a familiar pattern. Leaders acknowledge AI’s potential, agree it would add value, promise to move once budgets and plans are finalized—and then delay. Months pass, priorities shift, and momentum stalls. Meanwhile, competitors move ahead, costs rise, and inefficiencies deepen. By the time action feels unavoidable, the price of delay has already been paid.
That dynamic is now visible in hard data.
A new Build for the Future 2025 report from Boston Consulting Group (BCG) reveals a stark reality: only 5% of companies are capturing substantial, measurable value from AI. But those firms are not merely ahead—they are pulling away at speed. According to the report, these AI leaders are achieving twice the revenue growth and 40% greater cost reductions compared with companies that have not meaningfully invested in AI capabilities.
Meanwhile, nearly 60% of the 1,200 companies studied have little or nothing concrete to show for their AI investments. What was once a manageable gap between early adopters and cautious followers has become, as the report describes, a widening chasm.
From Caution to Costly Delay
“Leaders tend to distance themselves from the rest of the pack more and more,” said Nicolas de Bellefonds, Global Leader of AI at BCG and a co-author of the report. “The time for passive observation has sailed.”
The issue, BCG’s researchers argue, is not a lack of awareness or even ambition. It is a widespread confusion between being cautious and moving slowly. In fast-moving technological cycles, hesitation compounds. AI systems improve with scale, data, and iteration—meaning early movers benefit from accelerating returns while laggards fall further behind.
BCG refers to this top-performing 5% as “future-built companies.” These firms are not experimenting at the margins; they are embedding AI deeply into how their businesses function. As a result, they are widening the value gap and placing slow movers into what the report calls a “deeper value hole.”
Where the Real Value Comes From
One of the report’s clearest findings is that AI value does not come from pilots, proofs of concept, or isolated chatbots. Instead, it comes from reengineering the core of the business.
“Big value comes not from AI pilots or isolated use cases,” the report notes, “but from reshaping and reinventing core business workflows end-to-end.”
Future-built companies are applying AI across sales, manufacturing, supply chains, research and development, and IT—areas that directly affect revenue, cost structure, and competitive differentiation.
Amanda Luther, Global Leader of AI and Digital Transformation at BCG and a co-author of the study, said companies see the strongest returns when they make a small number of bold, focused bets.
“If you’re a consumer-goods company, pick marketing or R&D and go for material lift,” Luther explained. “If you’re industrial, it might be manufacturing and supply chain. It’s about identifying the areas that truly matter for competitive advantage—and then driving transformation across the entire value chain.”
Proof, Not Post-Mortem
Importantly, the report is not positioned as a retrospective analysis of how winners emerged. Instead, it serves as a roadmap for companies that have yet to move decisively.
“I think the positive news for organizations that haven’t moved yet is that there is proof at scale of where value delivery really happens,” Luther said. “That allows companies to be fast followers—if they act now.”
But fast following still requires urgency. According to the study, AI leaders have already fixed their data foundations, built internal capabilities, and created organizational muscle for adopting change. Those advantages compound over time.
“The gap is widening largely because early adopters have built the ability to absorb and deploy AI faster,” Luther added. “That capability only gets stronger.”
Investment Is Accelerating—Unevenly
The financial divide is also growing. Companies in the study that are already extracting value from AI plan to spend twice as much on IT this year, with a larger share of that budget directed specifically toward AI.
Catching up, de Bellefonds cautioned, is not about deploying the highest number of use cases. “Leaders are seeing returns—and reinvesting those returns,” he said. “That’s what makes the gap hard to close.”
Agentic AI as a Force Multiplier
One of the fastest accelerators identified in the report is agentic AI—systems capable of reasoning, learning, and acting autonomously across workflows. Once dismissed as a buzzword, agentic AI is now delivering measurable impact.
BCG estimates that agentic AI will account for 17% of total AI-generated value in 2025, rising to 29% by 2028. The strongest results emerge when these systems are deeply integrated into the business functions most critical to competitive advantage, such as marketing optimization or supply-chain orchestration.
No Magic Wand—Only Hard Work
Despite AI’s promise, the report pushes back against the idea that transformation is easy.
“There’s a misconception that AI is a magic wand—that you just plug it in and everything works,” de Bellefonds said. “That belief is sometimes pushed by AI providers themselves. The reality is, real transformation requires hard work.”
BCG found that AI failures are rarely about the models being used. Instead, the biggest barriers are human and organizational: unclear strategy, insufficient training, resistance to change, weak data foundations, and lack of governance.
Companies that skip the groundwork—operating models, skills development, and guardrails—struggle to scale, regardless of technical sophistication.
The Human Core of AI Performance
One of the report’s most enduring insights is what Luther refers to as the “10–20–70 rule.” Success with AI depends roughly 10% on algorithms, 20% on technology, and 70% on people.
“This study actually proves it out,” Luther said. “AI success is really about people.”
When deployed effectively, AI reduces repetitive work and frees employees to focus on judgment, creativity, and decision-making. “Done right,” she added, “AI takes the toil out of day-to-day work and creates more joy in the job.”
A Closing Warning
The report’s message is blunt: AI transformation is no longer optional, and delay is no longer neutral. Each week spent observing rather than acting makes catching up harder.
The widening AI gap is not just a technology issue—it is a leadership, organizational, and cultural one. Companies that act now may still position themselves as fast followers. Those that wait risk becoming permanent laggards in an economy increasingly defined by intelligent systems.
As BCG’s findings make clear, the performance case for AI is also a human case—and the cost of inaction is rising fast.
