By Sammy Lakshmanan, PwC US Digital & AI-enabled Sustainability Principal
Companies have spent years investing in sustainability to cut costs, strengthen resilience, and meet emissions targets. Yet many haven’t realized the full value because the underlying data has been scattered across systems that don’t talk to each other and a disproportionate amount of time is being spent on collecting data rather than analyzing and acting on such information.
In 2026, that changes.
AI is pushing organizations to modernize the data foundations that power decisions across operations, finance, and the supply chain. As sustainability metrics flow into those same environments, AI and sustainability will become mutually reinforcing. When AI can see how a company uses energy, materials, and transport, its insights become directly tied to margin and operational performance.
Four business-critical themes emerge where this shift can deliver greater impact: energy optimization, supply chain intelligence, customer insight, and operational resilience.
1. Optimize Energy Use Strategically
Rising energy demand and tightening grid capacity make energy management a front-office priority in 2026. AI brings new precision to this challenge by forecasting grid carbon intensity, congestion, and short-term prices across regions. Companies can schedule energy-intensive workloads—cloud compute jobs, model training runs, batch processing, and even certain manufacturing cycles—when the grid is cleaner, cheaper, or more available.
The organizations moving early are already seeing where 2026 gains will come from: lower energy costs, fewer grid-related disruptions, greater resilience across data-heavy environments, and emissions reductions achieved without new capital. In the year ahead, leaders will be more intentional about when AI runs, approving compute-intensive workloads only when the value case is clear.
2. Leverage Supply Chain Data
Supply chains remain one of the most financially material aspect of the sustainability equation, and in 2026 AI turns previously fragmented supplier and procurement data into a single source of insight. AI will also give companies new ways to cut waste across transport, material choices, and production flows. By cleaning, connecting, and analyzing complex datasets, AI helps leaders spot where emissions, resource use, and operational risk converge and where interventions will have the greatest payoff.
Companies gain the ability to identify lower-volatility materials with reduced environmental impact, anticipate continuity risks from climate exposure or water scarcity, optimize logistics to cut fuel costs, and trace materials in ways that protect brand integrity and improve compliance as global regulations evolve. In 2026, this deeper, more connected view of supply chain data becomes a direct contributor to cost control, resilience, and stronger supplier performance.
3. Understand Customer Preferences
Sustainability continues to shape customer expectations around quality, durability, and long-term value. In 2026, AI gives companies far sharper visibility into which attributes matter most and which customers are willing to pay for them. By analyzing first-party and market signals, AI can highlight where recycled materials drive preference, where product longevity increases conversion, and where low-carbon delivery influences buying decisions. Companies can design and price products with greater accuracy and elevate sustainability attributes in digital channels to meet customers where they are.
What emerges is a closer alignment between what customers value and what companies deliver—strengthening product differentiation and opening new revenue opportunities tied to sustainability-focused features and services.
4. Strengthen Operational Resilience
AI will play a bigger role in resilience planning in 2026 as companies face more climate pressure and tighter resource conditions. Scenario modeling, real-time simulations, and advanced analyses of facilities and fleets will help leaders see how operations and supply chains perform under different climate, energy, and resource-stress scenarios. These insights will shape capital planning, procurement choices, site selection and continuity strategies.
The organizations that use these tools effectively can gain a sharper view of where disruptions are likely, where redundancy investments deliver the greatest return, and how to protect performance in a more resource-constrained operating environment.
AI and Sustainability Come Together to Drive Business Value
AI and sustainability will converge in 2026 as a single performance system. The companies that treat them as strategic partners can move faster and compete harder. AI and sustainability won’t sit in separate strategies anymore; they’ll power the same engine.
