How Dow Is Turning Automation into a Strategic Engine for Scalable AI

As AI dominates industry conversations, the energy sector risks overlooking the foundation that enables it: automation. 

In this interview, Jack Hu, Process Automation Director at Dow, makes the case for treating automation as a strategic investment and the backbone of operational excellence, safety and scalable AI. Drawing on Dow's decades-long automation heritage, Jack explains how organizations can build the business case, scale across complex operations and develop the talent required to unlock long-term value. 

At the Operational Excellence in Oil and Gas Summit this November 3-5, Jack will present a live case study on Strengthening the Control Layer to Unlock Modern Process Automation, including a closed-loop AI deployment that delivered nearly $1 million in value in just months. 

Lily Mae Pacey: Can you start by outlining your role and what process automation involves? 

Jack Hu: Process automation is a specialized discipline focused on automating manufacturing operations. These assets often run for decades, so automation plays a critical role in improving output, preventing losses and ensuring process safety. 

To be effective, it needs to be viewed strategically, not just in terms of technology, but across investment, organizational structure and talent development.  

Ultimately, my focus is on helping teams get the most out of their assets across their entire lifecycle. 

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Lily Mae Pacey: Dow has challenged the idea that automation is just a line item in capital projects. Why does it need to be seen as a strategic investment? 

Jack Hu: At Dow, we're proud of the automation capability we've built over decades. But, when we look across the industry we also feel a responsibility to help elevate overall standards, particularly as automation underpins both operational excellence and the transition into AI.  

While AI dominates the conversation, automation remains overlooked. In many cases, the energy sector is still two to three decades behind what current automation technology can deliver. 

That gap isn't because the technology doesn't exist, it's often because energy organizations simply don't know what's possible or what they're missing. 

Automation drives operational excellence, process safety and forms the foundation for AI. If energy organizations take a more strategic approach, there's significant untapped value to be unlocked. 

Lily Mae Pacey: How do you build the business case to secure leadership buy-in? 

Jack Hu: It starts with one question: how much value are you leaving on the table? From there, energy organizations can quantify increased production, reduced losses and lower long-term costs. 

In hydrocarbon processing and refining, we already have strong benchmarks for what good looks like. The opportunity now is transferring that knowledge into newer energy sectors, where many organizations are still earlier in their automation journey. 

The biggest challenge is awareness, many organizations simply don't realize what's achievable. 

"While AI dominates the conversation, automation remains overlooked. In many cases, the energy industry is still two to three decades behind what current automation technology can deliver." 

Lily Mae Pacey: What are the biggest challenges energy organizations face when scaling automation? 

Jack Hu: The most important step is making the value case clear. Without that, it would be difficult to change the drive. 

Once the "how much value" question is answered, the challenge becomes organizational, ensuring the right structure, leadership alignment and long-term vision are in place. 

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Lily Mae Pacey: How should energy organizations think about ROI and measuring success? 

Jack Hu: It's not always straightforward to measure ROI in traditional ways. If you treat automation as a one-off investment, you might not see the full picture. 

Instead, companies should look at how much more they can produce and the loss they can prevent. 

It's like buying an iPhone and only using it to make calls. The technology may be there, but if you're only using a small fraction of its capability, you're not unlocking its value or future-proofing your operations. 

Automation is ultimately about futureproofing, ensuring you can fully leverage the capabilities you invest in. 

Lily Mae Pacey: Have you seen any unexpected benefits from your automation strategies? 

Jack Hu: Yes, particularly when automation is treated as a continuous process rather than a project. 

In some cases, we've been able to outperform vendor-provided systems, not because the technology is different, but because we operate with an ownership mindset. 

"If you treat automation as a one-off investment, you might not see the full picture." 

Vendors deliver systems as projects. But as operators, we live with those systems every day. That means we continuously improve them, working closely with operations to extract more efficiency over time. 

The key is ownership: building, operating and continuously improving, rather than delivering and moving on. 

Lily Mae Pacey: How does automation underpin AI, and what does that foundation look like in practice? 

Jack Hu: AI can generate recommendations, but the real challenge is execution. 

If your level of automation is low, operators are already overwhelmed by alarms. Adding AI recommendations on top of that doesn't solve the problem, it risks being ignored. 

To turn insights into outcomes, you need: 

• Integrated automation systems
• Simulation capabilities to validate actions
• A platform that connects data, insights and execution 

Without this, AI risks becoming insight without impact. 
 
Lily Mae Pacey: What role does talent play in this transformation? 

Jack Hu: Talent is critical. Process automation requires deep, multidisciplinary expertise, which can take 10-20 years to develop. 

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There's also a misconception that automation is less attractive than AI. As AI scales, we may see thousands of people who can build models, but far fewer with deep process expertise. 

That imbalance will make domain expertise even more valuable in the future. 

Energy organizations that invest in developing this capability will have a strong competitive advantage. 

"AI can generate recommendations, but the real challenge is execution … Without this, AI risks becoming insight without impact." 

Lily Mae Pacey: Looking ahead, how do you see automation strategies evolving and what will be critical to unlocking the next wave of value? 

Jack Hu: There are two priorities.  

1. Maintain momentum, continuing to deliver short-term value through increased production and reduced loss
2. Prepare for the long term. That means understanding emerging technologies and ensuring the company is ready to adopt them

Ultimately, success will depend on two things: talent and organizational readiness. 

Lily Mae Pacey: Looking ahead to your participation at the Operational Excellence in Oil and Gas Summit this November 3-5, what made it important for you to be part of this year's conversation, and why do you see this event as a critical platform for discussing operational excellence from a Dow perspective? 

Jack Hu: In manufacturing, energy companies do not build most of the core infrastructure: pipes, electrical systems and equipment typically sit with vendors. What organizations can control is how effectively they operate those assets. 

Automation is one of the most powerful levers they have to drive performance and it's critical that this message reaches senior decision-makers.

Key Takeaway: Automation is no longer just a technical enabler, it is a strategic foundation for operational excellence, resilience and scalable AI. 

Organizations that recognize this early, and invest in both technology and talent, will be best positioned to lead the next phase of industrial transformation.