Just as 2024 was the year AI went from an experiment to a mainstream business enabler, 2025 will be the year it begins to revolutionize the industrial sector at scale. While the technology is still maturing, it has sufficiently advanced to help address the industrial sector’s three most important objectives—increasing throughput, maximizing availability, and upskilling people.
The need to make certain our processes work more efficiently, our machines work harder, and our people work smarter is a universal constant that wise leaders (and savvy investors) should focus on every day. While you can approach each of these challenges in isolation, the smart play is to tackle them together by accelerating the move from automation to autonomy, and that is what I believe industry is ready to do in the year ahead.
Automation vs. autonomy
While “automation” and “autonomy” sound remarkably similar, they describe two very different states. In an automated facility, machines with pre-programmed instructions and deterministic outcomes govern the industrial process. In an autonomous facility, systems or machines can make recommendations and decisions that adapt to new conditions, changing environments, or unanticipated problems.
Both require skilled human interaction and intervention, but the beauty of industrial autonomous operation is that the machines are there to run everything, and serve as learned assistants, augmenting the humans on the team. The key difference—the element that jumps the divide between automated and autonomous operations—is artificial intelligence.
Consider the need to maximize availability—a core benefit of AI. By accessing years or even decades of historical data associated with equipment performance and service records, AI can analyze the data and provide recommendations that will extend the life of equipment or repair it most effectively. This means you face fewer unscheduled equipment outages, which reduces cost while maximizing throughput.
The delivery challenge
This only works if that data can be brought to the field and put to work in real time. The combination of AI with two other relatively recent innovations has sparked a “technology trifecta” that turns the theory of industrial AI into reality.
That trifecta includes the cloud, where we can store data and make it accessible to all users; 5G, which enables low-latency transmission of that data to power real-time operations and decision-making; and AI, which enables humans to interrogate the data in accessible ways and solve problems at the edge. This trifecta, which allows us to put AI to practical use, is the true industrial AI revolution.
Imagine a remote refinery in need of skilled operational staff to solve an issue or improve yield, or a company that owns multiple commercial buildings that needs to dynamically manage their facilities based on occupancy, improve their asset life, and meet new sustainability reporting requirements. With the trifecta, both can lean on historical data and AI-embedded tools at the edge to improve operations and enable true predictive maintenance. This leads to increased productivity at the refinery, and improved comfort, safety, and security for the tenants in all the buildings. In addition, by putting AI-enabled tools in the hands of workers, you can augment their skills with the experience of generations of others who have gone before them—enabling a worker with 3 to 5 years of background to operate as though they are a seasoned veteran.
The collaborative advantage
A significant lesson I’ve learned in my 35 years in this business is that successful partnerships can frequently take results from good to great. At Honeywell we have domain knowledge and a deep understanding of how to solve problems in aerospace, energy, and the building infrastructure sectors. By applying that knowledge in partnership with companies pioneering technology in the cloud and 5G space, we are able to develop revolutionary new products and services.
That’s the goal of the partnerships we’ve formed across the technology ecosystem, including recently announced collaborations with Qualcomm and Google. Others in this space have done the same—recognizing the benefits of teaming, while doing what each partner does best.
Of equal importance is a partnership with our industrial customers. One of the things I’ve learned over decades of work in this environment is that when you develop a solution that chases a problem, that solution is generally not adopted. Countless hours and dollars have been wasted by companies developing universally accessible solutions in a box, instead of using those resources to help a customer shape a solution that solves something real and present to them. The latter stimulates investment, and most often that technology scales.
The case for this year
We are at an inflection point in industry where we can significantly enhance our ability to work productively and profitably by harnessing the power of today’s technologies. We know we need our processes to work more efficiently, our machines to work harder, and our people to work smarter—and we have the technology trifecta of the cloud, 5G, and AI that can make it happen. That’s why I’m optimistic that 2025 is the year we truly begin the move, at scale, to industrial autonomy, where every day is your best day of operation, and every person is a world-leading expert.
Read more:
- Informatica CEO: How AI agents could find their way into most businesses—just as PCs did
- Nokia CEO: Making AI greener starts with smarter data center design
- Autodesk CEO: AI can help the U.S. fix its crumbling infrastructure before it’s too late
- AI ‘prompt and pray’ hasn’t cut it in the enterprise, but we’ve found the missing puzzle piece. Mass deployment is next
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
