Comau

1. How do you see the convergence of AI, green energy, and shifting social dynamics redefining the fundamentals of modern manufacturing ecosystems?

Artificial Intelligence enables real-time process optimization and predictive capabilities that are unlocking new levels of efficiency and adaptability. As a result, the convergence of AI, green energy, and changing social expectations is accelerating a shift from static manufacturing models to adaptive ecosystems. In parallel, the increased production and deployment of renewables, including solar and hydrogen, is allowing manufacturers to respond to society’s call for sustainable practices. Solar panel installation is expected to grow at a 10% CAGR (2022-2030) to reach 529 Gigawatts direct current by 2030. (Source: S&P Global IHS) and our Hyperflex mobile factory installs solar panels up to 30% faster with 35% lower costs, according to internal data gleaned at the EDP solar site. Similarly, Comau’s hydrogen solutions support the scaling of fuel cell and electrolyzer production in line with the sector’s projected 1000% growth by 2030 (Source: S&P Global IHS). What is happening, therefore, is a shift toward human-centric and environmentally aligned automation that pairs local sourcing with reduced emissions and dependencies. 

2. Beyond automation, what role do you believe AI will play in decision-making, predictive analytics, and workforce augmentation in the coming decade?

AI is already moving beyond simple automation and into the realm of real-time decision-making, quality assurance, and predictive analytics. AI-driven solutions like Comau’s in. Grid enables predictive maintenance and real-time process monitoring, which helps optimize maintenance cycles, forecast potential disruptions before they happen, and increase both uptime and productivity. Similarly, we are leveraging AI to model production scenarios and using AI directly within systems such as our MI.RA/OnePicker, a vision-based piece picking solution, through which the robot autonomously grasps randomly placed heterogeneous objects. AI is also helping guide complex manufacturing decisions. Analyzing and interpreting vast data sets in real time allows manufacturers to proactively adjust operations and mitigate risks. Comau is committed to training and using AI within the company as well as integrating AI within our solutions with the aim of making processes more efficient. The creation of the AI Competence Center is one example of this, as is the use of AI to power intuitive interfaces that allow operators to interact streamline tasks that previously required specialized training.

3. Sustainability has become a core priority for manufacturers. What structural changes are required in supply chains and production models to achieve real impact in green energy adoption?

True manufacturing sustainability will require a combination of local sourcing strategies that reduce transportation-related emissions and cost-effective green energy procurement. Remember, the need for industrial automation continues to grow at a constant rate. Market research indicates a projected CAGR of 11% from 2024 to 2030, which is confirmed by our experience with customers all around the world. 

In terms of supply chain structural changes, reshoring production, developing increasingly modular and scalable systems, and using virtual and/or digital tools to monitor, optimize, and trace processes are also necessary. Comau is helping localize the green energy production supply chain by automating fuel cell and electrolyzer manufacturing, and with innovative systems like Hyperflex, the mobile solar panel installation factory mentioned earlier. Hyperflex helps decentralize solar panel installation by integrating manufacturing directly within the field, which lowers energy consumption, speeds deployment, and will ultimately contribute to lowering the price point of green energy production. 

4. Workforce demographics are evolving with both an aging workforce and a younger, digital-native generation entering the industry. How can manufacturers balance skills transfer, upskilling, and cultural integration?

Workforce demographics changes can vary significantly from country to country and from industry to industry. I believe that balancing the needs of an aging workforce with the expectations of digitally fluent talents requires technology and tools that are intuitive, adaptable, and supportive across both physical and cognitive domains. AI-based programming interfaces that simplify robotics programming for users with limited experience are an example. Or wearable robotics, such as our MATE-XT and MATE-XB upper and lower back exoskeletons, which are a passive way to alleviate physical strain for both aging workers and anyone performing physically demanding or repetitive tasks.

The scenario is further complicated by a worldwide shortage of skilled workers in the manufacturing & automation field. We are working to help close the skills gap with the patented e.DO™ educational robot, which is a key part of our educational offering. The e.DO™ robot can also be used for advanced skills training. When combined with Seabery Soldamatic technology, the highly calibrated and parameterized system creates the most realistic welding training experience aside from actual welding. 

Upskilling training and education are also important. For companies engaging in cross-generational upskilling, training initiatives that focus on collaboration rather than replacement are preferred. Especially given that these types of initiatives help promote experience-based knowledge sharing across the extended team.

5. With geopolitical tensions disrupting supply chains and trade, how should manufacturing leaders rethink resilience and localization strategies without compromising global competitiveness?

Localized sourcing is already considered a strategic necessity within the EU, and the same can be said for manufacturers. The growing focus on nearshoring and flexible production is driving the need for software-driven systems that can be rapidly reconfigured and/or relocated.  Manufacturers should also avoid single-region dependencies for any of their critical processes to limit the risk/fragility of an exclusively global supply chain.

6. You’ve highlighted that we are at a crucial juncture of industrial and social transformation. What interdependencies between industry and society are most critical to address in shaping the future of manufacturing?

Right now, the most critical interdependencies between industry and society concern sustainability, labor transformation, and technological democracy. As automation continues its double-digit growth across both automotive and non-automotive sectors, there is an urgent need to address labor shortages as well as upskill workers for the digital era. MR4Weld was designed in collaboration with one of the world’s leading shipbuilders (Fincantieri) as a direct response to the shortage of welders. It’s an outdoor mobile robot that can help improve quality, performance, and well-being during labor-intensive welding activities by autonomously welding up to 170 meters of steel in a single shift – a 3-fold increase compared to manual processes. At the same time, industrial innovations that are directly tied to societal goals such as climate action and energy transition demonstrate how economic growth and environmental responsibility are increasingly co-dependent.

7. Despite the promise of AI and digitalization, adoption lags in many sectors. What do you see as the most underestimated barriers - technical, cultural, or organizational - that companies must overcome?

I believe that, although many companies recognize the benefits of AI and digitalization, adoption is often hindered more by internal resistance than by technical limitations.  Automation tools can be perceived as being too complex or disconnected from day-to-day operations. Another challenge is cultural inertia and siloed decision-making, or organizations that view digitalization as an IT issue rather than a strategic imperative. The solution is to develop plug-and-play, intuitive solutions that bridge the gap between operators and high-tech systems. 

It’s also essential to test AI through targeted projects to understand its real-world value and avoid investments driven by hype. Many AI applications are still rooted in consumer-level use cases, and their translation into industrial contexts requires validation. Additionally, data security, copyright concerns, and cyber risks are real barriers that companies must address from the outset. Ultimately, a strategic, measured approach that balances innovation with operational realities and safeguards is necessary for effective AI adoption.

8. How do you envision the next stage of human-machine collaboration, especially in contexts where robotics and AI intersect with creativity, safety, and decision-making?

Comau is one of the early leaders in developing and deploying industrial-speed collaborative robots, starting with AURA (Advanced Use Robotic Arm) in 2018. Offering the highest payload and reach for a collaborative robot, it features a dynamically managed high-speed mode when collaboration is not required and a collision avoidance system that covers both the robot and its tools. Since then, rather than launching a series of isolated products, we have developed a family of collaborative industrial solutions featuring both high and low payload systems. One example is the Racer5 COBOT, which combines collaborative safety features with high repeatability and accuracy and automatically switches from industrial to collaborative speed when a human enters its workspace.

With the increasing integration of AI, we are now creating systems where machines handle both physical and data-intensive tasks while human operators supervise, interpret, and innovate. Take solutions like MR4WELD or MI.RA/OnePicker, for example. These robots perform tasks, but they also learn and adapt to new variables, which enhances safety, reduces fatigue, and lets human operators focus on creativity and decision-making rather than manual activities. Another example can be seen in wearable robotics, such as the MATE-XT and MATE-XB exoskeletons, which were designed from the ground up for human-centric automation. 

9. As a CMO, you bring a solutions and market perspective. How do changing customer expectations influence not just product design but also manufacturing operations and business models?

Clients demand results. They need faster deployment, lower footprints, and higher agility. This manufacturing mentality shift means that solutions providers like Comau need to move from fixed-line solutions to modular and scalable systems that are easier to configure and use despite being more advanced. We have developed standard arc welding cells, for example. This “plug-and-play” solution pairs fast installation and commissioning with an ease of use that reduces the number of training hours, thus saving time and costs. Our new MyMR robots also reflect this new scenario, offering mobility, configurability, and operational payback in non-traditional sectors. Our customers also require increased customization, both in terms of the solutions we provide and the products they can produce. We are even looking at new service-based models for some markets. 

10. When faced with competing pressures - automation, sustainability, workforce training, and supply chain resilience - how should manufacturers prioritize investments for maximum long-term value?

In my experience, long-term value is created when investment in a program or a platform is able to intersect priorities, such as automation that improves sustainability while addressing labor shortages. In some cases, it can be more prudent to invest in quick-win solutions; however, in order to continue investing in a promising technology even if it has a slower growth than expected. This is the case with mobility and hydrogen, for example. Long-term value can also be created by flexible technologies that deliver ROI across multiple fronts, including quality, speed, and energy efficiency. More and more often, we find that taking a Design for Engineering approach, whereby we work with our customers from the design phase of their projects to ensure a holistic strategy and not fragmented spending, is the best way to ensure a sustainable investment path.

11. With manufacturing increasingly becoming data-driven, how can organizations strike the right balance between leveraging data for efficiency and protecting intellectual property/security in volatile environments?

The combination of a secure-by-design architecture and cybersecurity awareness allows companies to fully harness manufacturing data with limited risks. Another part of the big data puzzle is the interpretation and presentation of such data. Resilience, therefore, lies in balancing openness for optimization with safeguards against escalating cyber threats. This can be done, for example, with a digital solution like ours. Grid platform, which allows secure, real-time monitoring and data analysis without exposing proprietary information. 

12. What leadership qualities are most crucial for executives guiding manufacturing organizations through this period of unprecedented transformation?

Leadership is an area I am very involved in both within and beyond the manufacturing ecosystem. We are currently faced with transformation on multiple levels, from the obvious technological changes to geopolitical and demographic challenges. For this reason, today’s manufacturing leaders navigate uncertainty and foster collaboration across disciplines. They also need to drive cultural transformation in addition to technological innovation. Leadership means guiding with clarity while embracing complexity, especially as we transition toward increasingly digital, sustainable, and human-centric operations. At Comau, we’ve seen firsthand how transparency, adaptability, and a strong commitment to lifelong learning empower teams to thrive amid disruption

13. Looking ahead to the next decade, what do you believe will define the “winning” manufacturing companies? Will it be technology, agility, sustainability, or something else entirely?

Manufacturers will need to successfully embrace what I call intelligent transformation with a humanized edge, or the convergence of technology, agility, and sustainability, to win in the future. This includes seamlessly integrating automation, adapting to fast-changing markets, encouraging accountability within their organizations, and reducing their environmental footprints. With the industrial automation market projected to grow at over 11% CAGR, and sectors like collaborative robotics growing at 15% (2024–2030)*, I would argue that the companies that invest early in scalable, human-friendly innovation will be the ones who stand apart. *(According to Comau’s internal analysis backed by published market research).

14. From your vantage point as CMO at Comau, what has been the most surprising lesson or insight about transformation in manufacturing that leaders across industries should take to heart?

One of the most important lessons I’ve learned over the years is that transformation is as much about mindset as it is about machinery. The role of people and cultural change are often ignored or underestimated. Yet whether on the shop floor or in a strategic role, people who are empowered, involved, and supported become change agents. They will promote change, which is much more powerful than simply accepting it. Transformation, therefore, requires evolving how we think, lead, and collaborate. This is why I believe true progress only happens when innovation is inclusive and grounded in real-world needs.