Industrial automation is facing a structural transformation—from traditional machine control to the orchestration of intelligent systems. This is the conclusion of the study “Industrial Automation: From Control to Intelligence” by the international consulting firm Bain & Company. According to the study, nearly 50 percent of revenue in the industrial automation sector is expected to be based on AI-driven offerings by 2030. Value creation is thus shifting fundamentally toward software, data, and artificial intelligence.

Industry structure shifts from a pyramid to an hourglass

As a result, the industry’s architecture and profit distribution are also changing: the traditional “pyramid” is increasingly becoming an “hourglass.” In the future, more than 80 percent of the profit pool will be concentrated at the respective ends of this structure: While software, data platforms, and AI-supported layers account for more than half of the profits, another 25 to 30 percent is attributable to so-called intelligent field devices—that is, networked sensors, machines, and components that collect, evaluate, and transmit data in real time.

Traditional control layer comes under pressure

As a result, the traditional control layer is coming under noticeable pressure. While it remains an essential component, it no longer constitutes the most profitable core of industrial automation. Globally, companies that orchestrate data, software, and smart devices on a large scale are already achieving measurable results. They are increasing their productivity by 30 to 50 percent, reducing maintenance costs by up to 35 percent, and extending the lifespan of their equipment.

AI is becoming a key value driver

“What is changing is not just the technology, but also where economic value is created in the market,” emphasizes Adrien Bron, a Bain partner and co-author of the study. “With the growing importance of software, data, and intelligently connected devices, companies active in industrial automation must reassess and further develop their differentiation strategies. At the same time, they need to clarify where they can achieve economies of scale and leadership positions, and where they can create value in the long term.”

AI-powered solutions alone could unlock up to $70 billion in additional market value by 2030—a growth of more than 20 percent. The Bain study shows that a few specific application areas, such as adaptive robotics, predictive maintenance, and knowledge-based systems, account for a disproportionately large share of this potential. A significant portion of the value creation is likely to be realized within the next one to five years. In these areas, AI is no longer a differentiator but a prerequisite for market access.

Vertically specialized solutions drive growth

At the same time, competitive pressure is noticeably increasing across the industry. Established competitive advantages are losing their significance faster than many providers expect. The pressure is coming from both ends of the value chain: While hyperscalers and AI-native companies are increasingly penetrating industrial software and data platforms, aggressive hardware providers are putting pressure on margins for key automation components. “For established automation companies, this results in growing pressure from multiple sides,” explains Michael Schertler, a Bain partner and co-author of the study. “At the same time, switching costs are falling as software becomes increasingly decoupled from hardware and interoperability rises. The greatest danger lies not so much in abrupt disruption as in creeping marginalization.”

According to the Bain study, by 2030 nearly 60 percent of additional growth in industrial automation will come from vertically specialized solutions tailored to specific industries. For food and beverage manufacturers, for example, the focus is on traceability and hygiene. Battery and automotive manufacturers, on the other hand, prioritize manufacturing efficiency, throughput, and flexible production changeovers. In the life sciences sector, validation and regulatory compliance are central requirements—not merely additional functions. “Against this backdrop, growth and value creation are increasingly shifting toward verticalized solutions that combine software, data, and hardware into integrated end-to-end systems,” says Schertler. “Competitive advantages are increasingly derived from a deep understanding of the respective industry—and not solely from the control of individual machines.”

Business models are shifting toward lifecycle partnerships

With the increasing availability of continuous, data-driven intelligence, value creation is shifting from one-off, isolated solutions toward long-term business models oriented toward the product lifecycle. Companies increasingly prefer partners who remain involved beyond the commissioning of their products and continuously improve performance during the startup phase, operation, and optimization. This particularly strengthens recurring business models and providers who take long-term responsibility for results.

“As we move toward autonomous systems, the competitive advantage for providers will increasingly depend on combining software, data, and intelligent field devices into integrated end-to-end solutions,” concludes Bain expert Bron. “Companies that successfully orchestrate intelligence across systems, processes, and ecosystems will realize the greatest value creation potential in the next phase of industrial automation.”

Video