The Boston Consulting Group (BCG) has discovered an expanded crack that separates the elite from the majority of companies struggling to generate AI Masters elites from AI investments.
A BCG survey found that only 5% of companies have successfully achieved the ultimate value from large AI. In contrast, 60% report only minimal profit despite failing to achieve material value and investing heavily in technology.
“AI is rebuilding our business environment much faster than the previous technology wave,” says Nicolas de Bellefonds, managing director, senior partner and global leader of BCG’s AI initiatives and co-author of the report.
“Companies that are gaining real value from AI don’t just automate. They’re restructuring and reinventing the way their business works. And they’re pulling away.”
Top-performing organizations that BCG labels “FutureBuilt” aren’t just successful. They are creating a frighteningly widening gap in AI values. They already generate revenue growth of 1.7 times and EBIT margins of 1.6 times the lagging majority. Beyond isolated experiments, the elite group fundamentally reinvents its business and drives shareholder returns through increased revenue and improved measurable workflows. The remaining 35% of companies are striving to scale up, but admitting they are not moving fast enough to keep up the pace.
Future companies have earned early rewards and are now moving further by reinvesting profits. They plan to increase 64% of their IT budget to AI by 64% in 2025. This will make your overall AI investment 120% higher than your slower competitors.
As a result, future companies expect to see double revenue growth from AI applications and cost savings of 1.4 times. For Laguard, who has no basic ability and produces little value, this creates what BCG calls the “vicious cycle of losing the ground.”
The main reason for this disparity is leadership failure. Among companies that are lagging behind, top management often delegates AI strategies to middle management, failing to clearly express a clear vision for value from investment, spreading resources too thinly across disconnected initiatives.
The secret to success lies in proven playbooks, followed by 5% of the major ones. These companies approach AI as a multi-year board and CEO-sponsored multi-year program with ambitious and well-defined targets.
Almost every C-level leader in future organizations is heavily involved in AI, compared to just 8% of companies that are behind. They cultivate a model of shared ownership between business and IT departments. This is a practice that is likely to employ 1.5 times more likely than their peers. A senior retail business officer told BCG: “We will create a room where we can focus on senior sponsorship and ownership of AI benefits, particularly on senior sponsorship and ownership of AI benefits.”
These leaders don’t just automate existing processes. They focus on reshaping and invention of core business workflows with a large portion of their value. The report found that 70% of AI’s potential value is concentrated on core features such as R&D, sales, marketing and manufacturing. Future companies prioritize this reinvention, compared to just 12% of Laguard, compared to 62% of AI initiatives already rolled out.
Value gap accelerators are the emergence and investment in agent AI that combines predictive and generating capabilities, allowing them to “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.
Although little has been discussed in 2024, Agent AI already accounts for 17% of total AI value in 2025, and is projected to double by almost 29% by 2028. These leaders prioritize customer experience use cases for agents, with customer service being the top focus of 50% of the company.
“Agent AI is not a concept for the future. It’s already restructuring workflows and redefine roles. Companies need to view it as the next step in scaling AI, not as a starting point.”
“Agents represent a great opportunity, but it’s not just plug and play. Companies need to deal with the impact of agents on existing processes, roles and skills and urgently redesign work outcomes.”
Talent is another important differentiator. Future businesses are actively skilling their workforce to work with AI rather than focusing on unemployment. They plan to raise more than 50% of their internal staff, invest in a wide range of employee AI enablements, and carve out dedicated time for structured learning. This approach is six times more likely than a company to fall behind. It also involves employees twice as often as they co-design and reshape workflows to incorporate AI agents, ensuring smoother recruitment and building trust.
Major organizations avoid the “genai burden” of siloed, vulnerable concepts by building on a central, integrated AI platform. With three times more likely to operate such a platform, you can build a common security and monitoring feature once and then reuse it to accelerate deployment and ensure enterprise-wide scale. More than half of these companies operate on a single enterprise-wide data model, compared to just 4% of stagnant peers, providing quick access to trusted governance data.
The message is urgent as 95% of businesses are behind. The path to success is clearly portrayed, but requires fundamental changes in mindset and organization. BCG gives advice following the “10-20-70 Rule.” Here, transformation efforts should focus only 70% on people and processes, 20% on technology, and 10% on the algorithm itself.
The biggest obstacle to achieving value from AI investment is organization rather than technical, related to people, strategies, and processes. As technology advances and leaders accelerate, the window to catch up is rapidly closing. Companies that have not taken a decisive step will risk permanently remaining.
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