Founders, These Are the 5 Industrial Sectors Where AI Will Matter Most
by Fabian Erici, Principal at Europe's leading impact fund at Norrsken VC
AI is transforming productivity across sectors, but in industrials and manufacturing – where energy use, emissions and material waste are especially high – it holds massive untapped potential. These are the spaces where founders can create solutions that drive both impact and financial returns.
The AI technology’s precision and power allow us to achieve far more with far less. In heavy industry, that translates into meaningful emission and cost reductions. At Norrsken VC, we carried out a deep dive to understand where AI can unlock the biggest efficiency gains. We assessed the most promising industrial use cases and ranked them based on their potential to reduce energy use, material resource reduction and emissions.
Three types of AI applications consistently stood out. First, resource efficiency; reducing raw material use or enabling the shift to more sustainable materials, which lowers embedded emissions. Second, energy and process optimisation; making energy-intensive production cleaner, faster and more efficient. And third, predictive maintenance; extending equipment lifespan and preventing costly, energy-wasting breakdowns. What these applications have in common is that they not only reduce environmental impact but also cut operating costs, directly improving margins and profitability for industrial players.
Here they are:
1. Textiles
The textile industry is one of the largest contributors to global emissions, responsible for around 7 percent. Waste rates are extremely high, reaching up to 25 percent, more than any other major sector. Dyeing and finishing processes are especially carbon-intensive, accounting for around 3 percent of global emissions and a main driver of energy, typically representing 5 to 10 percent of a company’s energy costs. AI can help across the board, from predicting demand and reducing overproduction to cutting fabric waste and improving energy efficiency in manufacturing. The potential for change is enormous and long overdue.
2. Green tech
You might expect solar panels and batteries to be clean, and when in use, they are. But producing them is another story. These are technically complex products with sophisticated manufacturing processes, where waste rates in battery production alone can range from 10 to 30 percent, or even higher. Supply chains are often complex and lacking in transparency. While overall emissions are lower than in traditional heavy industries, the production itself is highly energy-intensive and difficult to scale profitably. This is where AI becomes a critical enabler. By optimising production flows, reducing defects, lowering energy use, and bringing greater transparency to the supply chain, AI can make the economics work while reducing the footprint. And because green tech underpins the broader decarbonisation of the economy, making its production more competitive and sustainable has a powerful ripple effect.
3. Cement
Cement production is an even bigger contributor to industrial emissions than textiles, responsible for around 8 percent of the global total. The primary issue is clinker, a carbon-heavy ingredient used in the mix. AI tools like Alcemy help reduce clinker use without compromising quality, cutting emissions by up to 65 percent. With energy representing around 30 percent of cement production costs, AI also plays a critical role in optimising heating systems and improving fuel efficiency across the board.
4. Steel
Steel manufacturing generates about 7 percent of global emissions and is another sector with huge potential for AI-driven efficiency. With energy accounting for more than 20 percent of production costs, even small improvements make a big difference. AI can anticipate equipment failures, avoid energy losses from unnecessary restarts, and fine-tune heating equipment in real time. These kinds of upgrades pay off fast, cutting both carbon and cost.
5. Chemicals
The chemicals sector also belongs to the most energy-intensive in the world, contributing roughly 5 percent of global emissions. Energy costs often exceed 10 percent, and while waste rates are relatively low due to tight regulation, the opportunity for efficiency gains is significant. AI platforms like Juna.ai can cut energy use by as much as 30 percent through continuous optimisation. Predictive maintenance and digital simulations add further value, improving consistency and reducing the environmental footprint of production.
Scaling these solutions takes more than smart technology. It takes ambition, capital and – most of all – founders who are passionate about solving our biggest problems. That’s why we built this framework, to help founders and future founders spot the opportunities where their solutions can have the largest impact. If you're building, or thinking about building in AI, this is where you’ll find the white space to create both financial and impact returns.
