The manufacturers that will define the future won't be the ones with the most AI projects — they'll be the ones that invest in their people and use AI to unlock human potential on the factory floor.
Adjusting Expectations around Timelines for AI & Industry 5.0 Transformation
Q&A with Vineet Thuvara, Chief Product Officer at | Fluke Corporation
Tell us about yourself and your role with Fluke.
I joined Fluke with more than 20 years of experience building technology products, most recently leading the Alexa Echo product organization at Amazon, where I helped develop AI-powered devices and experiences. Before Amazon, I spent 15 years at Microsoft in leadership roles and co-founded an industrial design company focused on bringing products from concept to market.
At Fluke, I’m focused on driving innovation that helps customers solve their toughest challenges and simplify the way they work. By combining our expertise in sensing, measurement and industrial technologies with emerging capabilities like AI, we’re creating smarter solutions that improve productivity, increase confidence and keep the world running.
Over the past few years, many manufacturers have approached AI with a sense of urgency and experimentation. What signals are you seeing now that indicate the industry is entering a more mature phase of industrial AI?
Manufacturers are now prioritizing AI technology that improves day-to-day operations rather than experimenting with new tools for the sake of innovation. We’re seeing clear signals in recent survey data from Fluke that show the three main AI technologies manufacturers are investing in: predictive maintenance, digital twins, and condition monitoring. With these technologies now central to operations, manufacturers are increasingly focused on solutions that drive profitability, resilience, and enterprise value.
Have manufacturers changed expectations around timelines for Industry 5.0 transformation? What is driving this shift in expectations?
The race to achieve Industry 5.0 is shifting, with manufacturers placing greater emphasis on building a strong foundation that fosters greater organizational cohesion. As AI is adopted across the enterprise, both internal and external stakeholders have recognized the importance of aligning on which technologies will most benefit workers and operations while delivering the strongest bottom line rather than chasing the newest tools. While this may not reflect the widely discussed Industry 5.0 transformation, it highlights the value of long-term strategies for enterprise-wide adoption of technologies that prevent downtime and support more sustainable implementation and ROI.
Many companies can successfully launch AI pilots, but scaling those solutions across facilities, plants, and workflow is often much harder. What are the biggest operational or organizational barriers preventing companies from moving from experimentation to enterprise-wide impact?
It’s clear that organizational readiness is key to ensuring technology investments truly pay off. If there are communication bottlenecks across an organization, these issues will spread to the factory floor, halting important work and impacting both money and time spent. Manufacturing is a highly connected ecosystem, so alignment from top to bottom is essential. Building a strong workforce can help overcome these barriers, and talent should be considered just as important as power and infrastructure. Companies that invest in their workforce will be best positioned to attract investment and sustain AI-driven growth.
As manufacturers invest in long-term transformation strategies, how are supply chain volatility, workforce readiness, and data infrastructure shaping AI deployment priorities?
There is much in this world that is out of our control, but it all comes back to building a solid foundation. With that in place, it becomes easier to stay agile in the face of disruption. We are seeing the need for better organized data on the factory floor to fully leverage predictive maintenance tools that help prevent downtime. Adopting enterprise-wide technologies that reduce downtime is a practical way to prepare for unexpected supply chain disruptions. Manufacturing organizations that invest in a skilled workforce are also better positioned for long term success. This can include partnerships with community colleges and trade schools, as well as supporting certifications and apprenticeships. A future-ready workforce will help ensure lasting success.
Looking ahead, what will separate the organizations that achieve sustained operational impact with industrial AI from those that remain stuck in the pilot phase over the next several years?
Organizations that invest in broad, end-to-end AI transformations without grounding them in real workflows and the needs of their workforce will face the greatest challenges moving beyond the pilot phase. The companies that successfully scale AI will be those that integrate it seamlessly into daily operations, using technology to empower employees, improve decision-making and solve real-world challenges.
The future of industrial AI is not about replacing people — it’s about giving workers the tools, insights and capabilities they need to be more productive and effective. That requires investing in both technology and the workforce through training, education and continuous skill development. Manufacturers that build a strong partnership between people and technology will be the ones best positioned to drive lasting operational improvements, adapt to change and lead the next era of industrial innovation.
The manufacturers that will define the future won’t be the ones with the most AI projects — they’ll be the ones that invest in their people and use AI to unlock human potential on the factory floor.
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow
Featured Product
