Boston Consulting Group (BCG) has found a widening chasm separating an elite of AI masters from the majority of firms struggling to generate any value from their AI investments.
A study from BCG found that a mere five percent of companies are successfully achieving bottom-line value from AI at scale. In sharp contrast, 60 percent are failing to achieve any material value, reporting only minimal gains despite making substantial investments in the technology.
“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.
“The companies that are capturing real value from AI aren’t just automating—they’re reshaping and reinventing how their businesses work. And they’re pulling away.”
Top-performing organisations, which BCG labels “future-built,” aren’t just succeeding; they are creating a formidable and widening AI value gap. They already generate 1.7 times more revenue growth and 1.6 times higher EBIT margins than the lagging majority. This elite group has moved beyond isolated experiments to fundamentally reinvent their operations, driving shareholder returns through revenue increases and measurable workflow improvements. The remaining 35 percent of companies are making efforts to scale up but admit they are not moving fast enough to keep pace.
Future-built companies, having reaped early rewards, are now reinvesting their gains to pull even further ahead. They plan to spend 26 percent more on IT and dedicate 64 percent more of their IT budget to AI in 2025. This results in an overall AI investment that is 120 percent higher than their slower competitors.
As a consequence, future-built companies expect to see double the revenue increases and 1.4 times greater cost reductions from their AI applications. For the laggards, who lack foundational capabilities and generate almost no value, this creates what BCG calls a “vicious cycle of losing ground.”
A key reason for this disparity is a failure of leadership. Among lagging firms, top management often delegates AI strategy to middle or lower management, fails to articulate a clear vision for value from investments, and spreads resources too thinly across disconnected initiatives.
The secret to success lies in a proven playbook followed by the leading five percent. These firms approach AI as a board and CEO-sponsored multiyear programme with ambitious, clearly defined targets.
Nearly all C-level leaders in future-built organisations are deeply engaged with AI, compared to only eight percent in lagging companies. They foster a model of shared ownership between business and IT departments, 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.”
These leaders are not merely automating existing processes. They focus on reshaping and inventing core business workflows where the majority of value lies. The report found that 70 percent of AI’s potential value is concentrated in core functions such as R&D, sales, marketing, and manufacturing. Future-built companies prioritise this reinvention, resulting in 62 percent of their AI initiatives already being deployed, compared to just 12 percent for the laggards.
An accelerator of the value gap is the emergence and investment in agentic AI – which combines predictive and generative capabilities – allowing it to “reason, learn, and act autonomously” with minimal human input. These AI agents can be seen as digital workers, capable of handling complex workflows from supply chain management to customer service.
While hardly discussed in 2024, agentic AI already accounts for 17 percent of total AI value in 2025 and is projected to almost double to 29 percent by 2028. The top firms are moving quickly, with a third already using agents, compared to almost none of the laggards. These leaders are prioritising customer experience use cases for agents, with customer service being the top focus for 50 percent of companies.
“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 is another key differentiator. Rather than focusing on job losses, future-built companies are aggressively upskilling their workforce to collaborate with AI. They plan to upskill more than 50 percent of their internal staff, making investments in broad-based employee AI enablement and carving out dedicated time for structured learning. This approach is six times more likely than in lagging companies. They also involve employees twice as often in the process of co-designing and reshaping workflows to incorporate AI agents, ensuring smoother adoption and building trust.
Leading organisations 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 them to build common capabilities for security and monitoring just once and then reuse them, accelerating deployment and ensuring enterprise-wide scale. More than half of these firms operate on a single, enterprise-wide data model, compared to just four percent of their stagnating peers, giving teams quick access to reliable and governed data.
For the 95 percent of companies falling behind, the message is urgent. The path to success is clearly delineated, but it requires a fundamental shift in mindset and organisation. BCG advises following a “10-20-70 rule,” where transformation efforts should focus 70 percent on people and processes, 20 percent on technology, and only 10 percent on the algorithms themselves.
The biggest roadblocks to achieving value from AI investments are not technical but organisational, relating to people, strategy, and processes. As the technology advances and the leaders accelerate, the window for catching up is closing fast. Firms that fail to act decisively now risk being permanently left behind.
See also: Samsung benchmarks real productivity of enterprise AI models
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