The value gap related to investments in artificial intelligence is becoming alarming within companies. Data reveals that only five percent of firms derive tangible benefits from these technologies. A striking contrast emerges as the majority, sixty percent, settles for insignificant gains. High-performing companies are reinventing their operations, while others stagnate in a downward spiral. Succeeding in this area requires total commitment from leaders, accompanied by a clear and bold vision. Time is running out to act, or many companies risk relegation.
The Value Gap Related to Investments in Artificial Intelligence
Research conducted by the Boston Consulting Group (BCG) highlights a growing divide between companies that master artificial intelligence (AI) and those that stall in their efforts. Currently, only 5% of companies manage to generate significant value from their AI investments at scale. In contrast, 60% of firms achieve no material value, signaling minimal gains despite considerable investments in this technology.
Reinventing Business Operations
High-performing companies, designated as “future-built” by BCG, go beyond the automation of existing processes. They focus on the fundamental reinvention of their operations. These companies report revenue growth 1.7 times higher and EBIT margins 1.6 times greater than their less performing counterparts. By transforming their business models, they increase return on investment for their shareholders while improving productivity.
Growing Investments from Leading Companies
These companies, which have already reaped the benefits of early AI implementation, are reinvesting their gains to solidify their lead. They expect a 26% increase in their IT spending and a commitment of 64% of their IT budget to AI by 2025. Consequently, future companies anticipate revenue increases twice as significant and cost reductions 1.4 times more notable thanks to their AI applications.
The Vicious Cycle of Lagging Companies
The remaining 35% of companies are trying to make progress but admit they are not advancing fast enough. In light of this reality, BCG speaks of a “vicious cycle” that comes into play. Lagging companies, often mere executors, assign AI strategy to mid-level management. This lack of a clear vision contributes to a dispersion of resources across disconnected initiatives.
Leadership and Executive Commitment
One of the fundamental reasons for this gap lies in the lack of leadership. Within the AI elite, almost all C-level leaders are actively engaged with AI technologies, making them 1.5 times more likely to adopt a model of shared accountability between business and IT departments. Leaders who invest and actively participate in AI strategy stand out distinctly from others.
Focus on Training and Talent Integration
The human element plays a decisive role in the success of AI strategies. Unlike their counterparts, high-performing companies train and support more than 50% of their employees to work synergistically with AI. This dynamism in training investments promotes adoption and builds trust among teams.
The Rise of Agentic AI
The development and investment in agentic AI, which combines predictive and generative capabilities, promise a revolution in workflow management. These digital agents, capable of performing complex tasks with minimal human intervention, already represent 17% of the total AI value in 2025, and this proportion could nearly double by 2028.
Technological Infrastructure and Data Management
Leading companies avoid isolated approaches by unifying their efforts on an integrated AI platform, three times more common than that of stagnating companies. They also establish common data models, facilitating access to reliable and regulated data. More than half of these companies use a central data model, compared to only 4% of lagging companies.
Facing Organizational Challenges
The challenges behind the inability to derive value from AI investments are not technical, but *organizational*. They pertain to issues of people, strategy, and processes. According to BCG’s recommendations, a successful transformation should focus 70% on people and processes, 20% on technology, and only 10% on the algorithms themselves. Time is running out for lagging companies, as the value gap continues to widen rapidly.
Additional Resources
To delve deeper into the subject of artificial intelligence, relevant resources remain available, such as this article on the promises and stakes of agentic AI or an analysis on the obstacles of AI in organizations. Other studies show how AI can transform payroll management, as indicated in this article on the strategic importance of automation. A focus on the challenges of AI projects can be consulted here: the execution gap of AI. Finally, the current technological dynamics also anchors a reflection on Europe’s digital sovereignty in this global context: the assertion of technology in Europe.
Common Questions about the Value Gap Related to Investments in Artificial Intelligence
What are the main reasons for the value gap in artificial intelligence investments?
The value gap is mainly due to a lack of leadership, poor definition of investment objectives, and a dispersion of resources across disconnected initiatives. Companies that succeed in deriving value from AI adopt a strategic and targeted approach.
How can companies reduce this value gap in their AI investments?
To reduce the value gap, companies must focus on establishing a clear AI vision, strengthening executive commitment, and prioritizing integrated initiatives that trigger measurable benefits. This also involves rethinking internal processes and prioritizing employee training.
What are the success indicators of companies that derive value from AI?
High-performing companies generate a revenue growth rate 1.7 times higher and EBIT margins 1.6 times greater than less performing companies. They also have well-integrated AI initiatives, with 62% of their projects already deployed.
What is the share of agentic AI in the value gap?
Agentic AI already represents 17% of the total AI value and is expected to nearly double by 2028. Companies that adopt it quickly, particularly in customer service, are able to restructure their workflows and achieve significant gains.
How does company culture influence the success of AI initiatives?
A company culture focused on collaboration between departments, executive engagement, and a shared approach to AI results promotes smoother adoption and better return on investment. High-performing companies also more often involve their employees in designing workflows.
What organizational obstacles hinder investments in AI?
Key obstacles include rigid hierarchical structures, lack of clarity in AI strategies, and absence of coordination among initiatives. These issues prevent the full exploitation of AI’s potential and increase the value gap.
What role does employee training play in reducing the value gap?
Employee training is essential, as it prepares staff to work effectively with AI. High-performing companies plan to upskill more than 50% of their employees, enabling them to collaborate and innovate with AI technologies.
How can companies measure the value generated by their AI investments?
Companies must define clear KPIs before launching AI projects, such as revenue increases, cost reductions, and process improvements. A systematic assessment of these indicators allows for measuring the real impact of AI on the organization.
Why is it crucial to focus on processes and people rather than technology itself in AI initiatives?
Focusing on processes and people ensures that AI technologies are adopted and used effectively. Companies should invest 70% of their efforts in people and processes to ensure that technological tools are beneficially integrated into the organization.
