Dow's AI Push: A Blueprint for the Industry or a Play to Investors?

When Dow announced it would lay off about 4,500 employees Jan. 29, the reduction in force was significant but by no means unusual. Several large players in the chemical sector have made similar moves in recent years to manage costs amid a weak market. 

But the Midland, Michigan-based company made a bold statement that connected two trends many workers fear are linked: job cuts and artificial intelligence adoption. 

A Dow spokesperson didn’t elaborate on how the AI initiative, called Transform to Outperform, would be deployed or exactly which job functions it would impact, but she indicated roles would evolve as the program advances.  

“The transformation is designed to strengthen how we operate by removing complexity, reducing bureaucracy and breaking down silos so it is easier and more efficient to get things done, said Dow spokesperson Sarah Young in a Jan. 29 email to Chemical Processing. “Headcount reduction decisions will be based on business need and the roles required going forward, as we put the right roles in the right areas of the company to better align with the changing market landscape and with the needs of our customers.”

AI-Linked Layoffs Spark Debate

The company’s ambiguous statement drew a strong reaction from several industry veterans. Some viewed the AI focus as a competitive necessity. Others dismissed Dow's emphasis on the technology as a ploy to please investors, a tactic that’s known as “AI washing.” 

One thing the former industry workers agreed on is that at the operations level, the sector is in the very early stages of AI adoption. 

Fan Li is an AI and R&D consultant who spent more than a decade at DuPont working in R&D and data science roles. He knows firsthand what major downsizing in the chemical sector looks like. 

After the Dow announcement, Li published a LinkedIn post that both offered support for the Dow move while empathizing with the laid-off employees. 

“What stands out is how openly Dow frames this move around AI and automation, while most companies avoid tying workforce adjustments directly to these technologies,” wrote Li owner of R&D AI and digital consulting firm Apex 974. “It is a bold choice, but also an understandable one. Dow has long been known for strong discipline in operational excellence, and this framing reinforces its willingness to lead the narrative rather than soften it.”

Li added that 10 years ago he experienced a major downsizing when DuPont dissolved its central R&D organization. Li landed with a DuPont spinoff before forming his own consultancy firm in 2023. 

Similarly, he has seen others adapt to emerging technologies by developing additional skills or applying their existing knowledge in different ways. 

“This could potentially be a new wave of workforce adjustment going through the industry,” he said in a follow-up interview with CP. 

Even so, the chemical sector, along with other manufacturing segments, is in the nascent stages of AI deployment, according to Govind Khalsa, head of marketing and strategy for workflow software company IntellaQuest. Many chemical process operations are still digitizing paper-based processes, such as ISO audits, said Khalsa, who serves as an adviser for Veridian Chemicals and is a former global vice president at Sachem Inc.

Khalsa speculated that Dow could use AI nearly anywhere in its operations, including non-production functions, predictive maintenance and emissions monitoring. 

“When you talk about these operational uses of the AI, you can also come back and think about jobs like marketing, business case management, product management, supply chain, managing your vendor,” he said. “Every single role that you see in a company, you can easily condense into fewer people needed to manage that function.”

Khalsa likened the trend to the outsourcing wave that industry experienced 20 years ago. Now, instead of moving jobs overseas to cut costs, companies are consolidating roles by equipping a single person with AI tools to perform a job faster and smarter, Khalsa said.

AI’s Impact Remains Limited

Despite the promise of AI, Dow’s job cuts were likely motivated by other factors, said Khalsa and other industry experts. 

“Looking at it as an outsider, it comes across as a classic reset of the cost base for a large chemical company and simplifying the operational model,” Khalsa said. “AI or no AI, it usually happens. You go through a three-year cycle or a five-year cycle. This time it's based on AI. If AI was not here with us, it could be based on something else.”

To some, the move is a classic example of AI washing, borrowed from term “greenwashing.”  Like ginned-up sustainability claims, AI washing suggests manufacturers are exaggerating their AI use to appear more innovative to investors and customers. 

“The AI narrative is simply too convenient, and it’s being used by so many different companies,” said Richard John Carter, an independent adviser and analyst based in Germany. 

Dow and other major chemical companies have been shedding assets due to declining demand in segments like polyethylene and demographic changes in mature markets, such as China, Japan and the EU, said Carter, a former senior executive at BASF. The AI announcement is simply a play to investors, he said. 

“How much more can you really squeeze out of petrochemical plants by applying AI? Let’s assume, for argument’s sake, you can run a plant 1% or 2% more efficiently,” Carter explained. “Well, that’s good, but it’s not going to move the needle in terms of the big picture. It’s not going to drive the bottom line significantly.” 

Former DuPont executive Peter Dmytro Geleta said AI is a convenient excuse for over-hiring and other poor management decisions. AI itself isn’t going to generate the savings the company is seeking in the near term, he said.

Dow said it’s expecting the cost-cutting/AI initiative to deliver at least $2 billion in earnings before interest, taxes, depreciation and amortization improvements by 2028. 

“Are you going to replace decisions that operators make with AI and get rid of operators in a chemical plant? No. Are your engineers going to become more efficient? Yes. How many engineers are you going to be able to eliminate because of that? Not many,” said Gelata, author of “Develop Business Execution Superpower With The CDX Method.” 

AI will eventually become a force in the industry, Geleta said. But widespread adoption could still be years away. He compared the challenge to the long road toward self-driving cars, noting that Tesla logged millions of hours of real-world driver data before the technology became viable.

"You can't do that in the chemical industry," he said. "You can't take a polyethylene plant and put it through every single type of upset that can happen and have the plant run itself. If it does happen, it's not going to happen in the next five or 10 years."

At least one technology vendor sees the AI trend differently. Digital twins now run many routine decisions during start-ups, shutdowns and grade changes, said Devan Pillay, president of the heavy industries segment at Schneider Electric. Such a scenario is already in play at European Energy’s Kassø Power to X e methanol plant in Denmark. Schneider Electric’s integrated EcoStruxure/Aveva ecosystem handles standardized sequences and remote operations at the plant.

“Our view is that this shift is fundamentally about redeployment, empowerment and upskilling — not replacement,” said Pillay in an email to CP. “In today’s plants, AI and operators work side by side. AI takes on the continuous, data heavy routine loops, giving operators more space to apply their judgement to the complex decisions, optimization challenges and problem solving that truly benefit from human expertise.”  

For now, AI adoption is not triggering a wave of workforce reductions, Pillay said. Instead, companies are using the technology to close talent gaps, strengthen safety, and support operators by assuming high-risk roles, he added. 

But plant closures and job cuts and their perceived connection to AI could make those talent gaps worse, warned Carter. If young engineers and scientists conclude the industry is shrinking rather than evolving, the sector risks losing the next generation of workers at the wrong moment.

“All this makes the chemical industry, unfortunately, less attractive when you and I know the need for innovation was never as high as it is today because of the challenges we’re facing,” Carter said.