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Digitalisation: from strategy to standard practice
How coatings and raw material manufacturers are embedding digital technologies into their operations – and what comes next. By Kirsten Wrede.
Digitalisation and automation have moved from aspiration to operational reality across the coatings industry. Companies along the entire value chain – from raw material suppliers to paint and coatings manufacturers – are deploying artificial intelligence, machine learning, cloud platforms, robotics and digital twins to accelerate product development, improve manufacturing efficiency and deepen customer engagement. Yet the journey is far from complete. While technologies are increasingly powerful, the real challenges lie in adoption, organisational culture, regulatory complexity and the sustained effort required to turn digital investments into measurable business value. For this market report, European Coatings has interviewed representatives from four companies – Adler-Werk Lackfabrik, Dow Coating Materials, Gebrüder Dorfner and PPG – to explore where the industry stands, what is driving change, and what obstacles remain. Where the industry stands All four companies have moved well beyond the exploratory phase and are now focused on scaling and integrating digital capabilities across functions and geographies.
At Adler, the Austrian coatings manufacturer, digital transformation is firmly anchored in strategy. “We began addressing this issue strategically at an early stage. Nevertheless, we are currently in the midst of an active digitalisation phase,” says Chief Technology Officer Dr Albert Rössler. A central focus lies on what he calls the company’s “digital backbone” – the ERP system connecting processes, data, systems and departments while supporting internationalisation. “In recent years, many manual processes have been replaced simply through the introduction of our modern water-based paint plant, a new, highly automated raw materials logistics system, and a laboratory automation system and software,” Rössler adds.
Brad Budde, Chief Digital Officer at PPG, frames the current moment in broader terms: “The paradigm has changed from being on a journey with a beginning and an end, to one that is a lifestyle of technological evolution.” PPG views AI as “a catalyst that is already reshaping how coatings are developed, manufactured and applied at customer sites. Our approach combines digital intelligence with trusted material science expertise, recognising that the next era of our industry will be defined by companies capable of this integration.”
Oliver Drum, Head of Application Engineering at Gebrüder Dorfner, describes the company as being “at an advanced stage of digitalisation and automation”. All processes have been systematically reviewed to identify efficiency potential. A cornerstone is the rollout of Microsoft Dynamics 365 in the cloud, extending to international subsidiaries. In production, the company analyses plant data using AI models and retrofits sensors; in sales, “for the first time, AI-powered agents are taking the pressure off our staff whilst improving service quality.” In R&D, digital twins of measurement devices accelerate formulation development.
Dan Wu (R&D Digital Transformation Leader), Partha Majumdar (Principal Research Scientist) and Kevin Henderson (TS&D Scientist) at Dow Coating Materials describe the company as “well advanced in our digitalisation and automation journey, with a strong focus on laboratory digitisation, data connectivity, and advanced analytics.” Dow has established a robust data infrastructure connecting laboratory test methods directly to digital databases. Beyond technology deployment, the team has invested significantly in change management to ensure digital tools are “embedded into daily workflows rather than operating as standalone solutions.”
Drivers of change
While specific triggers vary, common themes emerge: efficiency pressures, faster innovation cycles, growing customer expectations, and regulatory and sustainability demands.Rössler at Adler points to interconnected drivers: “Today, the industry must be able to efficiently handle single-unit production, and digitalisation is essential to this. When it comes to the shortage of skilled workers, digitalisation is no longer an option but a necessity. Ever-increasing regulatory requirements and shorter product life cycles are also driving the shift towards digital formulation technology.”
Budde at PPG emphasises the convergence of technology and ambition: “Traditional formulation development historically has relied heavily on physical experimentation, which is both time and resource intensive. Digital tools now allow us to learn quicker and bring products to market faster while maintaining the rigorous quality expectations that customers expect.” Oliver Drum, Dorfner, highlights supply chain resilience: “Shortages of raw materials and supply bottlenecks pose a significant challenge, meaning that the ability to respond flexibly to fluctuations in raw material availability is crucial to our business.” Sustainability requirements and faster, more precise product development have become clear competitive differentiators.
The Dow team frames its drivers around three pillars: productivity – “automation reduces repetitive manual tasks, allowing scientists and engineers to focus on higher-value problem solving”; accelerated innovation through “faster experimentation, improved data reuse, and more quantitative, insight-driven development”; and customer engagement via “modern, data-driven tools to enhance technical engagement and their experience.”
Technologies in action
The technology portfolios are remarkably broad, spanning AI, cloud computing, IoT, robotics, digital twins and advanced analytics – and they are already delivering tangible results.Rössler provides a concise overview: “For us, AI and machine learning, the cloud, automation and robotics, as well as digital twins and end-to-end data integration are key. This enables us to tap into potential that was previously unattainable. Energy and quality costs are reduced, productivity is increased, and we are able to develop more effective solutions for the market.”PPG’s portfolio is extensive. Budde describes deploying “generative AI and large language models with our decades of documented experience for development and field service applications” as well as “digital twins using deterministic AI models in research and development, which allowed us to successfully leverage historical formulation data to rapidly develop a new clearcoat.”
Customer-facing tools include the PPG “LINQ” digital ecosystem, which “improves bodyshop productivity by 15%,” and the PPG “DigiMatch” product, which “captures multiangle imaging data, connecting digital renderings with color formulations achievable in real-world scenarios.” The company is also applying AI inside manufacturing equipment using sensors and predictive models, a new approach that predicts performance to minimise downtime.
At Dorfner, the impact on formulation development is dramatic. Drum reports: “Our AI platform for formulation development enables a significant increase in efficiency by reducing laboratory processes that previously took nine weeks to just one day.” The company also deploys cloud technology for data processing and advanced visualisation tools that “facilitate the analysis of complex datasets, support informed decision-making and enhance transparency.”
Dow highlights two customer-facing platforms: “Dow Paint Vision,” offering coatings knowledge, formulation insights and data-driven guidance, and “Dow Specification Tracker,” supporting specification management in regulated applications. Internally, the team deploys generative AI, computer-vision applications and high-throughput robotics. “Together, these technologies have improved operational efficiency, increased data consistency, and accelerated learning cycles,” the team notes.
Navigating obstacles
Despite progress, significant challenges remain. Dr Rössler emphasises: “Digitalisation rarely fails because of the technology itself – but usually because of organisational structures, culture, processes and people.” He warns that “unrealistic expectations are a major stumbling block to digitalisation” and stresses that reproducible test methods form “the foundation for any further digital processing of data. Without it, digitisation, automation, data analysis and AI models cannot be relied upon”. Budde at PPG acknowledges physical realities: “In a coatings manufacturing environment, physics rules still apply – we have labs, plants and material supplies that require AI-enabled workflows to be re-written around them. Digital tools provide faster, better insights, but we need a human in the loop to ensure they loop into our key business processes.”
Drum from Dorfner points to regulatory complexity: “Requirements such as compliance audits, data protection regulations, extensive documentation obligations and necessary security clearances significantly increase the workload – particularly for projects in the fields of artificial intelligence and cloud solutions.” The Dow team identifies challenges including sustained change management for tool adoption, the complexity of demonstrating ROI for knowledge-based tools, building digital expertise amid rapidly evolving technologies, and “organisational digital uplift – embedding digital ways of working across the organisation so that they become the standard approach, rather than isolated initiatives.”
Outlook
The industry has moved decisively beyond whether to digitalise and is now grappling with how to do so effectively at scale. Technologies are proven and business cases compelling. But success depends on data governance, change management, skills development and organisational alignment.
