Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry? 

I’m a Digital Transformation Leader specializing in Enterprise digitalization and Smart Manufacturing. With 15+ years of experience delivering large-scale industrial automation programs and tech-backed transformations for Siemens industrial clients and within one of Air Liquide’s regional businesses, I know how to manage strategic changes, set up PMOs, and architect and integrate IT/OT landscapes hands-on. I’ve managed multi-million P&Ls and led mid-sized cross-functional teams. Expert in bridging the gap between business strategy and technological execution, delivering complex digital roadmaps that drive operational excellence. 

Q2. How do you see AI, industrial IoT, and advanced analytics converging to reshape operational excellence across process industries? 

IIoT has been available for years, aiming to deliver instant process value and support faster production elasticity. The evolution from 2G to private 5G has made data transport extremely flexible. Until now, the bottleneck has been processing the huge data silos that IoT made easy to shape but difficult to process. Before AI, the most powerful applications in process analytics were APC and Predictive Analytics, which historically have been developed on ‘Big data’ ML methods. With recent advancements in AI, new opportunities have emerged due to the AI's unprecedented autonomy and ability to self-learn see high potential in applying AI to predictive analytics applications with broader autonomy in process control, while the decision making remains a human prerogative, and the most promising is Physical AI to transit the shop-floor from humans to pure robotic environments, especially in supply chain, warehousing, and routine maintenance. 

Q3. How is the competitive landscape changing as industrial companies increasingly compete on digital capabilities rather than manufacturing scale alone? 

I wouldn’t say industrial companies focus purely on their perception of being digital. Core drivers will remain the same:  maximum productivity with the lowest possible production cost. Therefore, new AI offerings for industries must demonstrate clear payoff, production cost savings, or evading losses. Few can afford numerous experiments in revolutionary business process redesign, despite their huge potential. However, several global process-intensive companies (say, in Pharma and F&B) may take high risks and set the first-principles standard; the rest will follow. 

Q4. How can digital transformation accelerate sustainability goals while simultaneously improving productivity and operational resilience? 

I think regulators' and companies’ leadership commitment to ESG will remain the core driver for the industry to incorporate sustainability goals. Achieving net-zero has become nearly standard for global players because of a combination of these factors. However, regional policies are not uniform, and efforts at theat the UN level to secure national governments’ commitments to strictly follow UN ESG principles should continue. 

Q5. How are supply chain regionalization, energy transition, and geopolitical uncertainty reshaping digital transformation strategies? 

We are in a phase of deglobalization, and enterprises' natural instinct is to source from regional suppliers while regional governments crack down with new regionalization requirements. I think this trend will persist for the next 5 years, but will inevitably be followed by a softening of international trade rules for purely economic reasons. 

Q6. As industrial companies increasingly adopt agentic AI and automation, what new evaluation criteria are emerging for enterprise technology investments? 

As the AI sandbox phase ends, new productivity KPIs are emerging as manufacturing efficacy benchmarks. For example, OEE levels are expected to rise as AI-powered maintenance services are widely adopted. AI-powered technologies will become mandatory expense items in IT and OT budgets, but decisions will still  be based on payback and productivity evaluation criteria rather than AI buzz itself. 

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management? 

Does your 5-year strategy already incorporate future-proof technologies like AI, Physical AI, and IoT as mandatory elements of your future operating model, from the shop floor to C-level decision-making support?