Growth has become the defining challenge for industrial and energy companies, but the path forward is shifting. This is no longer a story about optimizing the core. It is about building new businesses and doing so faster, with less capital, and in more repeatable ways than has been possible.
A small set of repeatable, AI-enabled business-building plays is emerging as the fastest path to growth for industrial and energy leaders. Companies that treat venture building as a repeatable capability consistently outperform, achieving faster time to market, lower capital intensity, and higher success rates.
AI is the catalyst. Our research shows that 88 percent of companies now use AI in at least one function, and 62 percent are either experimenting with or scaling agentic AI.1 AI is accelerating everything from product design to model testing to customer engagement, reducing the barriers that have long made industrial innovation slow, expensive, and talent intensive.
The macro environment is becoming more favorable to business creation. Higher capital costs are pushing companies toward faster payback models and recurring revenue. At the same time, valuation corrections have opened a window for strategic M&A—particularly acqui-hires, data assets, and early-stage ventures that can accelerate internal builds. In the first half of 2025, global deal value for transactions over $25 million rose 22 percent to $2 trillion, and average deal size reached a five-year high of $544 million. For incumbents, this creates an opportunity to buy capabilities, talent, and technology that would otherwise take years to assemble.
This article offers a practical playbook for industrial and energy leaders seeking to capture the venture-building opportunity. It identifies five growth opportunities where value is emerging—each combining structural market tailwinds with new AI-enabled venture economics—and outlines the three operating shifts required to execute them successfully.
Recurring-revenue models
Transforming one-time sales into service offerings is shifting industrial economics as companies turn one-off equipment sales into new, service-led businesses. By bundling maintenance, analytics, and guaranteed outcomes into long-term contracts, companies can smooth cash flows while helping customers reduce downtime and risk.
Demand for these models is growing. Supply chain shocks and geopolitical uncertainty have made reliability a board-level issue, and service contracts provide the resilience buyers are seeking. Investors also are rewarding recurring revenue: Companies with embedded service streams and stickier customer relationships are commanding higher valuations and attracting private equity interest. On top of that, sustainability pressures are adding momentum. Extending product life cycles and reducing waste align directly with net-zero goals, allowing manufacturers to differentiate while embedding environmental responsibility into profitable business models.
Take Goodyear, for example. Its tire-as-a-service business reflects the company’s expansion of its total mobility offering. This subscription-based solution, available for commercial and last-mile delivery fleets in the United States and Europe, can save time and improve total cost of ownership through outsourced tire management.2
For industrial incumbents, recurring-revenue models are often the fastest path for translating existing assets into new ventures.
Actions to take
- Monetize existing strengths. Identify capabilities, such as maintenance, logistics, and analytics, that can be packaged into customer-facing service offerings. Goodyear, for example, leveraged its global service footprint and tire-monitoring technology to build a fleet management offering on top of its core product business.
- Shift to outcome-based models. Build contracts tied to uptime, efficiency, or performance rather than one-time product sales. In Goodyear’s case, its tire-as-a-service model uses a pay-per-mile structure, directly linking revenue to fleet usage and aligning incentives with customer cost savings.
- Rewire incentives. Align sales and delivery teams around recurring revenue and long-term customer value.
Green ventures and circularity
As decarbonization targets tighten, global energy and industrial companies are under pressure to cut emissions, reduce waste, and secure sustainable inputs. New ventures built around recycling, reuse, and alternative fuels are rapidly becoming engines of growth.
While circularity began as a regulatory mandate, it has quickly proven an economic advantage as well. Governments across the world are fueling the momentum with funding and tax incentives, from the EU’s Circular Economy Action Plan to the US Inflation Reduction Act. Carbon prices have climbed sharply, and sector-level targets in industries such as automotive and construction are pushing companies to embed circular practices across their operations.
The scale of the opportunity is evident. Aluminum demand is projected to grow from about 106 million metric tons in 2025 to about 130 million by 2035, mainly driven by growth in the automotive industry and increased adoption of electric vehicles (EVs)—leaving recycling to fill the gap at a fraction of the energy cost. In transport, zero-emission trucks must rise from less than 2 percent of sales today to one-third by 2030 to meet regulatory targets, despite a current cost disadvantage of up to 40 percent compared with diesel. These gaps create openings for ventures in charging networks, battery reuse, and alternative fuels.
This momentum is already translating into results. In Europe, Cylib recently secured €63.4 million in public funding to build an industrial-scale lithium iron phosphate battery recycling facility in Germany, accelerating its ability to recover lithium, graphite, and other critical materials at commercial scale. The grant supports expansion, but the underlying model is built on structurally attractive economics: recovering scarce inputs at lower energy intensity and reduced supply chain risk.3 Similarly, BASF’s ChemCycling program channels significant annual investments into circular raw materials that feed its chemical production network.
For leaders in energy and industrial sectors, circularity is increasingly shifting from compliance requirement to scalable growth platform.
Actions to take
- Target near-term value. Focus on green ventures with short payback periods and clear eligibility for public funding or subsidies.
- Embed sustainability in strategy. Position circularity not as compliance but as a growth lever that differentiates the brand and attracts investors. Cylib’s scale-up—from its pilot facility in Aachen to a planned industrial plant in Dormagen with 60,000-metric-ton annual capacity (including a dedicated lithium iron phosphate line)—reflects a model built for commercial viability and supply chain relevance.4
- Scale what works. Pilot quickly, measure results, and double down on models that deliver both financial and environmental returns. Honeywell’s UpCycle platform illustrates this approach. Rather than scaling alone, it has partnered through joint ventures and supply agreements—including with Sacyr in Spain and TotalEnergies—to accelerate deployment, secure feedstock, and build ecosystem support.5
Direct-to-customer (D2C/B2B2C)
Industrial buyers increasingly expect digital, personalized, and frictionless experiences. For manufacturers—especially in categories like appliances—building direct-to-customer channels has become a top strategic priority. More than 80 percent of appliance companies expect their websites to become more sales centered within the next three years, reflecting a broader push to bring distribution, data, and brand experience closer to the customer.6
Despite growing traffic, most manufacturers’ websites remain underleveraged. Roughly 32 percent of customers visit them during the purchase journey, yet fewer than 2 percent make a purchase.7 Most visitors come to explore, not to buy—but that’s precisely where the opportunity lies. Companies that combine transparent pricing and seamless delivery with standout serviceability, convenience, and thoughtful extras (such as free accessories or proactive support) can convert casual browsers into committed buyers.
The economics are compelling. By bypassing intermediaries, manufacturers can lift gross margins while gaining direct access to demand signals and usage data. Direct channels also unlock faster innovation cycles, enabling real-time testing of new products, bundles, and pricing models often in weeks rather than months.
Leading companies are already demonstrating what direct engagement can unlock. Consider another example from Goodyear, which is embedding agentic AI into its customer journey through a network of digital agents. These include personal shopping assistants that guide customers to the right tire based on vehicle and driving patterns, as well as sales and service agents that automate recommendations, follow-ups, and appointment scheduling. By integrating these capabilities into its direct channels, Goodyear is simplifying the buying process, increasing conversion, and creating a more personalized, end-to-end customer experience.
Direct channels are becoming a critical route to margin expansion, faster learning cycles, and closer customer ownership.
Actions to take
- Define the value proposition and manage channels. Articulate a clear customer value proposition that differentiates on service, convenience, and trust. Actively manage potential channel conflict as direct sales grow.
- Design the full customer journey. Drive qualified traffic to digital channels, make discovery and purchase effortless, and create post-purchase experiences that build loyalty and repeat sales.
- Build cross-functional enablers. Stand up a dedicated D2C organization supported by an agile operating model, scalable tech and data foundations, and tight integration across marketing, supply chain, and fulfillment.
AI acceleration and data monetization
Industrial companies are sitting on vast stores of data, such as equipment performance, production flows, and customer usage, but much of it remains underutilized. Turning this data into products, platforms, and services is becoming a high-value growth strategy, particularly as AI makes monetization easier and faster. Beyond unlocking new revenue streams, AI is reshaping how these ventures are built—compressing concept validation, accelerating product iteration, and enabling leaner teams to scale faster than traditional models.
Momentum is building across the ecosystem. Public investment is rising, with programs such as the EU’s InvestAI designed to fund large-scale industrial platforms. Adoption is accelerating as manufacturers, logistics operators, and energy players move from pilots to scaled deployments. At the same time, the cost of storing and processing data has fallen dramatically over the past decade, making it feasible to package and sell operational data sets at scale.
Agentic AI is amplifying this shift. By reasoning across complex data sets and acting on insights in real time, agents can automate analytics, streamline R&D, and lower the cost of building new data-driven ventures. The payoff is significant. McKinsey research estimates agentic AI could unlock $450 billion to $650 billion in annual revenue by 2030 in global energy and industrial leaders, alongside 30 to 50 percent cost reductions.
This shift is already taking shape across industries. Consider HERE Technologies, which aggregates location data from 70 OEMs and sells APIs to more than 1,300 clients. Walmart’s Scintilla grew 173 percent year on year after evolving into an AI-powered intelligence platform.
For many industrial incumbents, proprietary data is increasingly becoming one of the most scalable and defensible growth assets.
Actions to take
- Audit and activate data assets. Identify proprietary data sets with commercial potential and test pilot products within 90 to 120 days. John Deere, for example, has built a powerful data moat from more than 370 million acres of land, with field-level models that improve over time and increase switching costs. Similarly, HERE aggregates anonymized location data from more than 90 OEM brands—spanning hundreds of millions of vehicles—and layers it with third-party inputs to create real-time location intelligence.8
- Build scalable models. Choose monetization paths—platforms, embedded analytics, or outcome-based services—that create recurring value. Exemplifying this approach, HERE applies a transaction-based API model across services such as routing, geocoding, and mapping.9
- Link insight to impact. Tie data products directly to measurable customer outcomes to reinforce loyalty and differentiation. John Deere’s outcome-based pricing model reflects this shift. Farmers pay per acre only when measurable savings are delivered, which aligns revenue directly with customer value and strengthens long-term loyalty.
New materials and ingredients
As the energy transition accelerates, demand for critical inputs such as lithium, cobalt, and rare earth elements is surging. Supply, however, is struggling to keep up. For global energy and industrial players, this creates openings to build differentiated materials businesses that address supply gaps while capturing premium margins.
These opportunities are unfolding amid a broader reconfiguration of global supply chains. Trade flows are shifting, regional production networks are deepening, and manufacturers are reassessing concentration risk in critical materials. Rather than relying on single-source geographies, many companies are diversifying through localized processing, regional partnerships, and more resilient value chain architectures. Leaders that anticipate these shifts can position themselves within newly emerging supply ecosystems, balancing operational discipline with the upside of first-mover advantage. The economics, however, are shifting.
Extracting traditional resources is becoming more expensive and environmentally intensive, while recycling and processing are moving to the center of industrial strategy. Policymakers are reinforcing this pivot. The EU Critical Raw Materials Act sets ambitious 2030 targets for domestic extraction, processing, and recycling. Funding is expanding through initiatives such as the EU Advanced Materials Strategy and the LIFE Programme, which together mobilize hundreds of millions in public–private investment. At the same time, nearshoring and shifting trade flows are forcing OEMs to rethink supply chains, creating opportunities for localized processing and recovery ventures.
Across the value chain, new ventures are redefining how materials are sourced and scaled. Take Redwood Materials as an example. It is scaling from recycling into lithium ion input production, having recently raised $350 million to expand its ability to supply grid-scale energy storage systems as electricity demand surges.10 These ventures demonstrate how incumbents can use compliance, certification, and supply security as competitive moats to carve out durable positions in fast-growing markets.
As supply chains regionalize and critical inputs tighten, materials innovation is becoming both a growth opportunity and a strategic moat.
Actions to take
- Spot and spin out hidden assets. Identify materials, tools, or processes with stand-alone market potential. Redwood Materials illustrates this shift. Rather than stopping at recycling, it has vertically integrated into the production of battery-grade materials, such as copper foil and cathode inputs, capturing more value across the supply chain.11
- Build defensible moats. Use certification, compliance, and strategic partnerships to secure competitive advantage. Redwood has anchored its position through supply chain partnerships with OEMs including GM, Lyft, Panasonic, Toyota, and Volkswagen—securing both feedstock and offtake while reinforcing its role in the battery ecosystem.12
- Localize and scale. Leverage regional supply chain shifts and policy incentives to anchor new ventures closer to end markets.
These opportunity spaces show where growth is emerging. What will increasingly separate winners, however, is not simply where they choose to play but how they build across these spaces.
Three shifts that will separate the next generation of successful builders
Many of the next growth engines are extensions of what leading companies already do well, but first movers will shape the economics and lock in advantage. What distinguishes leaders is not just where they play but how they rewire their operating model for AI-first venture building. As outlined in our latest AI venture-building research, the same three shifts are increasingly differentiating the leaders across these growth spaces.
1. Reset performance expectations across asset-heavy ventures
Successful business builders will shift from incremental gains to step changes—faster paths to product–market fit across service, circularity, and direct-to-customer ventures, and lower cost to launch and materially shorter validation cycles for asset- and service-heavy ventures. Leaders are proving this is achievable even in asset-heavy environments. Cylib’s progression from pilot facility to industrial-scale plant and Redwood Materials’ rapid expansion from recycling into battery-grade material production demonstrate how ventures can validate early and scale quickly, compressing years-long timelines into much shorter cycles.
2. Build the industrial data and AI backbone
Leaders will combine autonomy to move fast with integration to scale fast, anchoring ventures in shared operational data, customer signals, industrial technology stacks, and AI-enabled tooling from day one. This means building on proprietary data advantages. John Deere’s agronomic data platform, HERE’s global location intelligence ecosystem, and Goodyear’s sensor-enabled fleet data exemplify ways in which a robust data foundation enables AI to scale, and scale is necessary for AI to differentiate. The strongest builders treat data as core infrastructure.
3. Rewire domain workflows with AI
Builders that join the next generation of leaders will redesign how work gets done across engineering, commercial, and supply chain domains. They will embed AI into core workflows to scale expertise, reduce handoffs, and accelerate iteration. This enables smaller, cross-functional teams to build and scale ventures across complex industrial environments.
For industrial and energy leaders, AI is fast becoming the new operating system for venture building. The winners will be those that can build, test, and scale systematically, repeatedly, and at a pace that fundamentally resets venture economics.
