Industrial AI is no longer a distant prospect. According to the IFS Invisible Revolution Study 2025, the use of AI in manufacturing companies is predicted to almost double in the next 12 months, from 32% today to 59%. At the same time, profitability improvements are already widespread, with 88% of organisations worldwide reporting that AI has had a positive impact on their bottom line.

"AI is a key driver of business performance. Now is the time to close the adoption gap - bringing people, processes and products together to deliver tangible results," says Kriti Sharma, CEO of IFS Nexus Black.

For example, in the US, 90% of senior decision makers plan to increase AI investment in 2025 compared to 2024.

AI First Becomes the Norm

The shift in organizational AI maturity is even more dramatic. Today, just under one-third of businesses (32%) claim to be “AI First,” meaning AI is deeply embedded into workflows and decision-making. But within a year, nearly 60% expect to achieve this level of integration. The number of companies still “experimenting” with AI is expected to plummet from 24% to just 7%.

The research shows that companies are rapidly moving beyond pilot projects and concept testing. The proportion of organisations still "experimenting" with AI is expected to fall sharply, from 24% today to just 7% within a year.

This marks a decisive shift towards integrating AI into key functions such as asset management, supply chain optimisation and manufacturing.

But the momentum also reveals vulnerabilities. More than half of executives admit that their organisations do not yet fully understand AI. This lack of clarity can undermine adoption at a time of increasing competitive pressure.

Training gaps become critical

Skills development has emerged as one of the most pressing challenges. Most managers believe that up to 60% of their workforce will need retraining to adapt to AI-enabled activities. Significantly, a third of respondents estimate that this need could apply to all employees in their organisation.

This training gap is already being felt in recruitment. Many managers describe hiring AI talent as "extremely difficult", even in countries where the education system is seen as supporting the skills of the future. Without large-scale retraining programmes, organisations risk being left behind just as the AI revolution accelerates.

Over half of US firms (54%) offer formal training, yet 65% of US senior decision makers say their businesses still lack the knowledge to use AI to its fullest. By contrast, just 46% of respondents in Japan feel this gap exists, pointing to stronger internal confidence.

AI Gains Without Strategy

Another barrier is the lack of a strategy. More than half of managers, 53%, admit that their organisation does not yet have a coherent AI strategy.

Despite this, financial returns have exceeded expectations. Globally, 70% of respondents report better-than-expected returns on their AI initiatives, which has driven investment. This figure rises to 92% in the US and 94% in Germany.

Companies are achieving measurable benefits but do not yet have the strategies and governance models needed to sustain long-term change.

Trust remains a barrier

Over half of US organizations are already using automation AI (56%), predictive AI (54%), and agentic AI (35%), systems that can act autonomously to execute decisions. Globally, the numbers are slightly lower but still significant, demonstrating early momentum across industries.

Despite improved profitability and operational efficiency, many managers remain hesitant to hand over decision-making power to AI. Only 29% say it would be easy to let AI systems make strategic decisions on their own. A large majority - 68% - believe that human judgement is still necessary before AI-based insights can be deployed.

Concerns about bias and fairness remain acute. In the US, 63% of respondents consider bias to be a major concern, compared to only 40% in the Nordic countries. This difference shows how cultural and regional differences influence the speed and scale of AI adoption.

Global AI Oversight

That lack of trust extends to how AI is governed. While many enterprises are moving forward with implementation, the call for oversight is growing louder. 71% of US senior decision-makers, and 62% globally, believe AI needs some form of regulation.

Notably, 65% of global respondents support the creation of an international, independent body to oversee AI development and deployment, signalling that organizations are not only concerned about risk within their own walls but are calling for globally coordinated oversight as AI becomes more deeply embedded in critical systems.

However, respondents in Japan (22%), Nordics (19%), the Netherlands (16%), and Germany (13%) were the most resistant to the idea of a global independent AI organisation.

Transforming Business

AI is no longer just transforming operations; it’s redefining business models. 77% of respondents (and 85% in the US) believe servitization — the shift from selling products to delivering value through services and outcomes — will become a dominant revenue model enabled by AI.

Furthermore, 80% of senior decision-makers globally (and 90% in the US) expect AI-driven savings to be reinvested into their enterprises, fueling further innovation, growth, and expansion. Nearly three-quarters (73%) plan to pass some of these savings on to customers through improved pricing and enhanced service.

However, this customer-centric view is not universally shared, particularly in asset-heavy industries where margins are tight and competition is fierce. In these sectors, many expect efficiency gains from AI to be channelled directly into strengthening profitability rather than shared externally.

Environmental impact is also firmly on the agenda. 86% of senior decision-makers believe AI will help organizations meet sustainability goals — from energy efficiency and emissions reporting to CO₂ management.

Source: IFS Invisible Revolution Study 2025. 

text: Vaula Aunola

photo: iStock