A few weeks ago, we shared why we believe industrial sectors are primed for AI-driven transformation. While software has revolutionized many industries over the last two decades, manufacturing, logistics, energy, and construction have been slower to digitize—largely because their workflows are deeply physical, complex, and built on legacy systems.

But that’s changing—and fast.

Now that we've established why industrial sectors need specialized AI, let's dive into where the biggest opportunities lie. From agentic automation revolutionizing logistics to AI copilots empowering frontline workers in energy and intelligent systems refining manufacturing, AI is already making a profound impact. Here’s where we see the most exciting advancements happening right now.

Making sense of complexity → AI for knowledge & understanding

AI can solve one of the biggest challenges across all industrial sectors: scattered, hard-to-access knowledge.

Industrial operations generate massive amounts of data, but much of it remains locked away in disconnected systems, legacy databases, and unstructured formats like PDFs and maintenance logs. Workers waste time searching for information, manually cross-referencing sources, or making decisions based on incomplete data.

Retrieval-augmented generation (RAG) systems are changing that. By retrieving, synthesizing, and interpreting information in real time, they act as an industrial brain—helping teams make faster, better-informed decisions.

A great example is our investment Trunk Tools, that integrates across numerous systems, stitching together insights from drawings, schedules, submittals, and more. It creates a knowledge system that teams can query and use to track workflow delays. CEO and Founder Sarah Buchner embodies the ideal blend of academic rigor and hands-on expertise, pairing a PhD with invaluable on-site construction experience—exactly the kind of leader we’re excited to support.

Automating & accelerating workflows → AI that does the work

Industrial workflows are riddled with repetitive, manual tasks. AI agents can finally take them off people’s plates.

Many industrial processes haven’t changed in decades, whether it’s managing production schedules or approving procurement requests. These tasks require navigating cumbersome ERP and MES systems, with heavy reliance on manual data entry and human coordination.

AI is stepping in—not just as an assistant but as an agent that can take action, orchestrate workflows, and even fully automate key processes.

Consider  HubFlow, an early-stage team building an agent for logistics brokers and carriers. Their AI automates appointment scheduling between receivers and shippers, reducing back-and-forth coordination and minimizing errors. They integrate directly into carriers’ existing TMS, promising better data quality while streamlining operations. And, as with the best industrial AI founders, CEO Nick Hubbard comes from logistics himself.

Engineering & discovery co-pilots → AI as a creative engine

AI isn’t just improving operations—it’s enabling upstream discovery and engineering.

In areas like materials science, advanced manufacturing, and engineering, AI is unlocking new ideas that humans might never have considered. Whether it’s discovering the next breakthrough in battery chemistry or optimizing complex part geometries, AI can augment engineering time by automating simulations, offloading lower-value work, and pulling forward manufacturing cost insights.

Take Cadstrom, an Innovation Endeavors portfolio company building a co-pilot for electrical engineers. They’re starting with PCB design verification and validation but have a much bigger vision: a generalizable system that understands board intent, components, and required simulations. CPO & co-founder Scott Bright led engineering teams at large consultancies—Cadstrom’s first customers—giving him firsthand insight into what engineers need most. Read more here.

Compliance & risk mitigation → AI to parse and monitor standards

Compliance is one of the biggest hidden costs in industrial sectors—AI can streamline it while reducing risk.

Industrial companies operate under strict regulatory and compliance requirements—whether it’s FDA safety rules, OSHA workplace regulations, environmental policies, or industry-specific standards. Compliance is often a major cost center and an operational bottleneck, requiring extensive documentation, audits, and manual oversight.

AI can automate compliance monitoring, flag risks, and generate reports in real time. This not only reduces liability but also ensures companies stay ahead of evolving regulations without unnecessary overhead.  This use case is a great fit for foundation models, given that policy and regulation is highly textual and structured.

Conductor AI is tackling compliance in the government sector, reviewing policy documents to ensure they meet regulatory standards. Their system augments compliance teams by automating tedious review processes, allowing them to focus on higher-value tasks. Founders Zach Long & Eric Schwartz, both Palantir alums, deeply understand the complexities of this space and are building for the customers they know best.

Why does all this matter?

AI is no longer just a nice-to-have experiment for industrial companies—it’s becoming a core enabler of efficiency, intelligence, and, ultimately, competitiveness.

The best industrial AI startups will:

• Deeply integrate with existing workflows & systems (rather than requiring companies to rip and replace).
• Deliver real ROI in low-margin environments (AI for AI’s sake won’t cut it here).
• Combine the power of foundation models with industry-specific expertise (bridging generic AI advances with real-world industrial needs).

AI for the physical economy is not a niche opportunity — it could transform foundational parts of the economy. Startups that crack these problems will scale fast, and the winners are being built now.

If you’re building in this space, we want to hear from you. Let’s build the future of industrial AI.