Industrial automation has begun a structural transformation in which value stops focusing on control and moves on to intelligence, according to the new Bain & Company report: Industrial Automation: From Control to Intelligence.
By 2030, Bain predicts that almost half of the industrial automation sector’s revenue will depend on AI-based solutions, reflecting the growing importance of intelligence in value creation. Industrial automation thus advances from traditional control systems towards software, data and AI, transforming the structure of the sector and its profit pools from a “pyramid” model to an “hourglass” model.
According to the consulting firm’s analysis, more than 80% of the benefits of the industrial automation sector will be concentrated in two areas: software, data and AI on the one hand, and smart devices on the other, while traditional control systems will lose weight. The greatest weight will correspond to software, data platforms and AI-based solutions, which will generate more than half of the total profit, along with smart field devices, which will contribute an additional 25% to 30%. In contrast, the traditional control layer will no longer be the main driver of profitability of industrial automation, although it will continue to be relevant within the industrial ecosystem.
Integrate and orchestrate data, software and smart devices
Companies that are already integrating and orchestrating data, software, and smart devices at scale are seeing tangible results. These organizations report productivity increases of between 30% and 50%, maintenance cost reductions of up to 35% and a longer useful life of their assets. These advances demonstrate the impact that industrial automation is having on the efficiency and competitiveness of organizations.
“What is changing is not only the technology, but the place where economic value is generated in the market,” says Manuel de Soto, partner at Bain & Company. “As software, data and smart devices gain prominence, industrial companies will need to rethink how to maintain and continually reinforce their differentiation, where to find new sources of scale and leadership, and how to capture value sustainably over time.” In this context, industrial automation becomes a strategic element to promote this transformation.
AI-based solutions alone could generate up to $70 billion in new market value by 2030, equivalent to 22% growth. Bain’s analysis indicates that a limited number of use cases—such as adaptive robotics, predictive maintenance, or knowledge-based systems—concentrate a particularly relevant portion of that potential, and that much of the value will be realized within one to five years. In these areas, AI is no longer a differentiating element, but rather an imperative to compete within industrial automation.
Competitive pressure is increasing throughout the sector. The historical advantages of established players are eroding faster than many anticipate. Pressure is coming from both ends of the value chain: on the one hand, hyperscalers and native AI players expand into industrial software and data platforms; On the other hand, particularly aggressive hardware manufacturers are tightening margins on key industrial automation components.
Risk factors in industrial automation
For established players, the result is increasing pressure from both ends of the market. At the same time, switching costs decrease due to the decoupling of software and hardware and greater interoperability. The main risk is not a sudden disruption, but a progressive loss of relevance in the industrial automation market.
AI-based solutions alone could generate up to $70 billion in new market value by 2030
According to the Bain report, almost 60% of the industrial automation sector’s incremental growth through 2030 will be driven by vertical-specific offerings. These solutions, adapted to the needs of each industry – incorporating process knowledge, data semantics and regulatory requirements – will be the main driver of future growth, as companies prioritize sectoral specialization over horizontal scale.
As intelligence becomes continuous, value creation tends to move from one-off solutions to orchestration throughout the entire life cycle. Customers increasingly value partners who stay involved beyond the initial start-up, improving performance during startup, operation and optimization phases. This approach favors recurring relationship models and companies that take responsibility for results over time, a change that is redefining industrial automation.
As industrial automation moves toward greater levels of autonomy, competitive advantage will increasingly depend on the ability to integrate software, data, and smart field devices into unified solutions. Companies that manage to orchestrate intelligence across systems, operations and ecosystems will be better positioned to capture value in the next phase of evolution of the industrial automation sector.
