Boston Consulting Group (BCG) says a growing gap is separating a small group of AI leaders from the majority of companies that struggle to convert AI spending into measurable business results. A BCG study found that a mere five percent of companies are successfully achieving bottom-line value from AI at scale, while 60 percent report only minimal gains despite large investments.
“AI is reshaping the business landscape far faster than previous technology waves,” said Nicolas de Bellefonds, a managing director and senior partner and global leader of BCG’s AI efforts, and a coauthor of the report. He and other authors argue that the difference between winners and the rest is widening quickly.
BCG labels the top performers “future-built.” These organizations already post 1.7 times more revenue growth and 1.6 times higher EBIT margins than the lagging majority. They have moved well past isolated pilots and are changing core ways of working, using AI to lift revenue and improve workflows in ways that drive shareholder returns. The remaining 35 percent of companies are trying to scale AI but admit they are not moving fast enough to keep up.
Future-built firms, having seen early results, are plowing gains back into tech and talent. They plan to spend 26 percent more on IT and to devote 64 percent more of their IT budgets to AI in 2025. The combined effect is an overall AI investment that is 120 percent higher than that of slower competitors. Those investing more expect to capture double the revenue increases and 1.4 times greater cost reductions from AI applications. For the laggards, which often lack core capabilities and generate almost no value, BCG warns of a “vicious cycle of losing ground.”
Leadership behavior lies at the heart of the gap. In many lagging firms, senior executives delegate AI strategy to middle or lower management, offer no clear vision for value from AI, and scatter resources across disconnected initiatives. The firms that succeed treat AI as a board- and CEO-sponsored, multiyear program with ambitious, clearly stated targets.
Nearly all C-level leaders in future-built organizations are deeply engaged with AI, compared with only eight percent in lagging companies. These leaders push a model of shared ownership between business and IT, a practice they are 1.5 times more likely to adopt than their peers. One senior retail executive told BCG they “concentrate in particular on senior sponsorship and ownership of AI benefits by the businesses, which creates the room to invest.”
Top performers do more than automate existing tasks. They concentrate on remaking core workflows where most of AI’s value sits. BCG’s analysis finds that 70 percent of AI’s potential value is concentrated in functions such as R&D, sales, marketing, and manufacturing. Future-built companies prioritize these areas, and 62 percent of their AI initiatives are already deployed, versus just 12 percent among laggards.
A fast-growing factor widening the gap is agentic AI, which combines predictive and generative capabilities and can “reason, learn, and act autonomously” with minimal human input. These agentic systems act like digital workers capable of handling complex workflows across supply chain, customer service, and other domains. Agentic AI accounted for 17 percent of total AI value in 2025 and is projected to almost double to 29 percent by 2028. About a third of top firms are already using agents, compared with almost none of the lagging group. Customer experience use cases get priority, with customer service the top focus for 50 percent of companies adopting agents.
“Agentic AI isn’t a future concept—it’s already reshaping workflows and redefining roles. Companies should view it as the next step in scaling AI, not as the starting point,” said Amanda Luther, a managing director and senior partner at BCG and a coauthor of the report. “Agents represent a huge opportunity but aren’t simply plug-and-play: companies urgently need to redesign how work gets done, addressing the impact of agents on existing processes, roles, and skills.”
Talent strategy marks another dividing line. Rather than emphasizing job cuts, future-built firms invest heavily in upskilling so employees can work with AI. They plan to upskill more than 50 percent of internal staff through broad-based programs and structured learning time. That approach is six times more likely in top companies than in laggards. Leading firms also bring employees into co-design workstreams twice as often, which helps projects land faster and builds trust in new workflows that include AI agents.
Leading companies avoid the “GenAI burden” of siloed, unscalable proofs-of-concept by building on a central, integrated AI platform. They are three times more likely to operate such a platform, allowing teams to build common capabilities for security and monitoring once and then reuse them across projects, which speeds deployment and supports enterprise-wide scale. More than half of future-built firms run on a single, enterprise-wide data model, compared with just four percent of their stagnating peers, giving teams quicker access to reliable, governed data.
BCG lays out practical steps for companies that want to catch up. It recommends a “10-20-70 rule,” where transformation efforts allocate 70 percent of focus and resources to people and processes, 20 percent to technology, and 10 percent to the algorithms themselves. The consulting firm stresses that the main obstacles to realizing value from AI are organizational — relating to leadership, talent, and ways of working — rather than purely technical.
With technology advancing and leading firms accelerating their programs, the window for catching up is shrinking. Firms that do not move decisively risk losing market position as investments by the top cohort translate into sustained revenue and cost advantages.