Nearly three in every four enterprise businesses are planning to deploy agentic AI within the next two years, according to Deloitte’s 2026 The State of AI in the Enterprise report.
Adoption of physical AI is expected to reach 80 per cent in the same timeframe, with manufacturing, logistics and defence leading the way.
At the Hannover Messe 2026 event, more than 4,000 companies will highlight how cloud and AI is driving measurable performance across factories, supply chains and mobility networks. For Dayan Rodriguez, corporate vice president of global manufacturing and mobility at Microsoft, this is the moment to move from traditional methods to AI-driven, scalable and autonomous operations. We spoke with him to find out more.
Tell us about your professional background and what drew you to Microsoft.
I began my career with degrees in engineering and programming, working on systems that had to perform on factory floors under pressure. Over time I moved into product management, general management, and profit and loss leadership. At Rockwell Automation, I led global businesses across the industrial internet of things (IIoT), cloud, cybersecurity, and the convergence of IT and operational technology. Later, I served as global vice president and general manager within Honeywell Industrial Automation, accountable for growth, operational execution and financial performance.
What shaped me most was spending time in factories with operators and plant managers who expected technology to improve safety, quality, throughput and cost. In industrial automation, ideas only matter if they deliver measurable impact on a production line. That grounding has stayed with me throughout my career.
Today, I lead AI transformation with customers and partners. As a sales leader on the industry side at Microsoft, my focus is on advancing agentic AI, robotics capabilities and autonomous driving technologies across manufacturing and mobility sectors, which have customers and partners with a range of priorities on innovation. I came to Microsoft in 2024 because it combines global scale, a secure cloud platform and advanced AI in a way that can accelerate industry transformation at a pace we have not seen before. I’m privileged and honoured to work with a talented team who thrive on innovating, collaborating and challenging the status quo.
Wayve has used Microsoft Azure to build an AI-powered driver that can be installed into any new car (Photo: Wayve)
How does your background in industrial automation help drive value for Microsoft in manufacturing?
My experience allows me to connect strategy to operational execution. At Rockwell Automation and Honeywell, I carried responsibility for margins, delivery and growth. I understand how technology decisions affect both financial outcomes and operational performance. This unlock has been key for my professional development.
In my current role, I push our teams and our customers to deliver AI impact through return on investment (ROI) within six months. That means moving quickly from use case prioritisation to tangible results. We focus on AI and cloud capabilities to fuel agentic AI, robotics and autonomous driving solutions that reduce downtime, improve asset utilisation, strengthen cybersecurity and unlock new revenue streams. Manufacturers measure success in overall equipment effectiveness, safety metrics and profitability. Our strategy has to show progress in those areas within a defined period. Our mobility capabilities with AI have changed the game with automakers and it’s exhilarating to see value unlocked.
What separates leaders who turn disruption into advantage, from those who fall behind?
Leaders who succeed stay curious and decisive. They remain close to their teams and customers, and they test new technologies against operational data instead of protecting legacy systems.
During the Industry 4.0 shift at Rockwell Automation and the digital acceleration at Honeywell, and now at Microsoft, I’ve witnessed leaders create advantage by linking innovation directly to financial and operational goals. They were willing to act before everything was perfectly defined, and they created clarity around priorities so teams could move with confidence. Those who waited for complete certainty often lost momentum.
The same dynamic is playing out with agentic AI that soon evolves to physical AI, as we recently experienced this year at CES in Las Vegas, USA, and soon at Hannover Messe in Germany. Leaders who align technology adoption to measurable outcomes will move ahead, and quickly.
As AI gets deployed, what mindset do executives need to truly unlock business value?
Executives need to treat AI as an operational capability embedded in daily workflows. In manufacturing and mobility at Microsoft, we start with defined outcomes such as safer operations, higher quality, faster cycle times and lower maintenance costs.
Agentic AI becomes powerful when leaders clearly define intent and constraints, and the system executes with speed and consistency. Robotics and autonomous driving technologies follow the same pattern. When AI is integrated into scheduling, maintenance, logistics and mobility operations, it shifts from an interesting technology to a performance driver.
The mindset shift is from exploring possibilities to executing against clear business objectives.
What are the most promising and practical AI applications in manufacturing today?
The strongest use cases link digital intelligence directly to physical systems. For example, computer vision can guide robotic systems and detect defects instantly, while agentic AI optimises production schedules across multiple facilities. Autonomous driving technologies enhance safety and efficiency in industrial yards and fleet operations, and AI systems capture the expertise of experienced technicians, scaling knowledge across the workforce.
Because I have led IIoT and cybersecurity portfolios, I understand the complexity of legacy infrastructure and fragmented data environments. At Microsoft, we bring together cloud, AI and security to unify those systems and enable co-ordinated decision-making across plants and fleets. That integration reduces cost, increases resilience and creates new service opportunities. The opportunity is to convert top AI use cases into ROI efficiently and effectively.
Rodriguez (centre) with Bosch’s Tanya Rueckert (left) and Paul Thomas at CES 2026, announcing their joint work on agentic AI for production (Photo: CES 2026)
How would you describe the partner community in industrials and manufacturing, and where is it adding the most value?
Industrial transformation depends on collaboration. From my experience, the strongest results come from co-ordinated ecosystems of original equipment manufacturers, system integrators and technology innovators. The future favours the bold customers willing to take risks with Microsoft and our thousands of experienced, global partners.
Microsoft provides the AI platform, secure cloud infrastructure and global reach. Our partners contribute deep expertise in robotics integration, intralogistics, autonomous systems and vertical industry processes. The most value is created when we align around a specific operational objective and execute together. That could mean modernising a facility with robotics, deploying agentic AI across a supply chain, or scaling autonomous driving solutions across a mobility network. It’s all about adding value and growth opportunities!
Microsoft partners contribute deep expertise in robotics integration, intralogistics, autonomous systems and vertical industry processes (Photo: Microsoft)
How should manufacturers measure the ROI of AI initiatives, and what tangible results or evidence have you seen from deployments that were particularly successful?
AI ROI must connect directly to operational and financial performance. Meaningful indicators could be reduced scrap, higher equipment availability, improved safety performance, faster product launches and margin expansion.
Momentum builds when value is demonstrated quickly. The most successful deployments identify high impact use cases, execute with discipline and expand once measurable gains are achieved. I have seen predictive models prevent costly equipment failures and autonomous systems significantly reduce safety incidents. When those outcomes appear in operational dashboards and financial statements within months, AI becomes embedded in how the organisation operates. AI is one of the most consequential opportunities of our lifetime and the future is so exciting when value is attained.
Discover more insights like this in the Spring 2026 issue of Technology Record. Don’t miss out – subscribe for free today and get future issues delivered straight to your inbox.