From Environmental Data to Business Value: How Consumer Goods Leaders Are Turning AI Into Action
At the Global Decarbonization Forum 2026 - New York held during Climate Week NYC, a roundtable of consumer goods and supply chain leaders explored what it takes to move environmental strategy from ambition and reporting into everyday business decisions.
Ann Tracy, Chief Sustainability Officer at Colgate-Palmolive; Sheri Hinish, Founder and CEO, Supply Chain Revolution Global (Supply Chain Queen®); and Prof. Dr. Christian Heinrich, CEO and Co-Founder of carbmee, discussed the intersection of environmental AI, procurement, supply chains, and business value. Across the conversation, one message stood out: environmental transformation does not happen through better reporting alone. It requires companies to connect environmental data with the products they make, the suppliers they work with, the costs they manage, and the decisions they make.
From Sustainability Priorities to Business Value
For large consumer goods companies, sustainability touches almost every part of the business, from product design and packaging to operations, sourcing, and supply chains. Ann Tracy highlighted how Colgate-Palmolive has increasingly focused on identifying where the company can have the greatest impact while creating clear value for the business. The company's current strategy puts a stronger emphasis on value creation, with teams expected to articulate the business value behind major sustainability priorities.
The shift is important. Environmental initiatives cannot exist separately from commercial priorities. Products still need to meet consumer expectations, work at the right price, and deliver for the business. This changes the conversation around sustainability from "What should we do?" to "Where can environmental action create meaningful business value?"
Environmental AI Starts With the Data
Sheri Hinish broadened the perspective, emphasizing that environmental stewardship in AI means looking beyond energy and carbon to areas such as water scarcity, land use, soil degradation, and the communities affected by new infrastructure.
The panel also challenged the idea that AI alone can solve environmental data challenges. Christian Heinrich emphasized that sophisticated AI use cases depend on the fundamentals: clean data, harmonized systems, reliable master data, and connected environmental information. For consumer goods companies, this means bringing together data from ERP, procurement, suppliers, products, and environmental sources. Different categories may require different environmental intelligence, from packaging and recycling to water consumption, product carbon footprints, or regulatory requirements. The objective is not to create another layer of complexity, but to reduce it. Once the underlying data foundation is in place, AI can help companies identify patterns, automate processes, surface data gaps, and support decisions at scale.
Sheri also emphasized that AI must be deployed with the people it affects in mind. As AI becomes more deeply embedded in business, questions of access, representation, and responsible adoption become increasingly important, particularly across global markets where technology infrastructure and resources are unevenly distributed.
Procurement as a Lever for Decarbonization and Resilience
The discussion repeatedly returned to procurement as one of the most powerful levers for environmental transformation. Supply chains are facing a growing combination of geopolitical uncertainty, regulatory requirements, price pressure, and resource constraints. In this environment, environmental data becomes relevant not only to sustainability teams but directly to sourcing and procurement decisions. Christian illustrated this through a procurement lens: if better environmental data enables a procurement team to negotiate with suppliers, identify cost-saving opportunities, or understand the financial implications of carbon, it becomes part of the business case rather than a separate sustainability exercise.
Sheri connected this to the broader transformation of supply chain strategy. With geopolitical shifts, tariffs, regulatory pressure, and increasingly complex global risks reshaping supply chains, companies need to rethink sourcing, supplier relationships, product design, and even where production takes place. Resilience, she argued, should not simply mean returning to the previous system after a disruption; it should also mean redesigning the system itself.
Moving From Perfect Data to Actionable Data
One of the challenges discussed was the persistent search for perfect environmental data. Ann pointed to the importance of continuing to move forward even when data and processes are not yet perfect. Christian similarly argued for starting with high-value use cases rather than waiting for every data point to be complete.
A practical approach is to begin with strategic categories or suppliers, establish reliable primary data, verify the underlying calculations, and then scale the process. For procurement teams, the value lies not in knowing every detail of a product carbon footprint. It lies in having environmental information that can be integrated into a repeatable business process, from supplier engagement and negotiation to sourcing decisions and internal carbon pricing. This creates a shift from data collection as an objective to data as an enabler of action.
Scaling Transformation Through Alignment
The panel also explored alignment across the consumer goods value chain. It highlighted Colgate-Palmolive’s work on recyclable packaging and how innovations can become more impactful when they are shared across an industry. The development of recyclable tubes, for example, demonstrated how product innovation can extend beyond one company and contribute to broader systems change.
The speakers emphasized that this type of alignment is essential for addressing challenges that no single company can solve alone. Companies can align on infrastructure, standards, circularity, supplier development, and other challenges while continuing to compete on product innovation, execution, talent, and consumer value. This becomes particularly important for circular supply chains, where no individual company controls the entire system. Progress depends on alignment across manufacturers, suppliers, recyclers, policymakers, investors, and consumers.
From Supplier Data to Supplier Inclusion
Supplier engagement remains another major challenge, particularly beyond Tier 1. The panel discussed how many suppliers, especially smaller companies and those in emerging markets, face significant barriers when asked to provide environmental data or meet increasingly complex requirements. Sheri highlighted the risk that increasingly demanding environmental and technology requirements can unintentionally exclude suppliers that lack the necessary infrastructure, interoperability, or financial resources. Supplier transformation therefore needs to be accompanied by education, access to technology, financing, and practical support.
The solution requires more than simply asking suppliers for better data. Companies need scalable processes, clear expectations, education, technology, and incentives that enable suppliers to participate. For global consumer goods companies, this means treating supplier engagement not simply as a data request, but as part of a broader strategy for building more transparent, inclusive, and resilient value chains.
Environmental Intelligence as a Business Capability
The discussion ultimately connected environmental intelligence with a much broader transformation of how consumer goods companies operate. Environmental data needs to move closer to the decisions that determine business performance: which products to make, which materials to source, which suppliers to engage, how to design for circularity, where to invest, and how to manage risk. It also needs to reach the suppliers and markets that risk being left out of the transition, so that environmental requirements become a pathway into global value chains rather than a barrier.
AI can accelerate this shift, but only when it is grounded in reliable enterprise data and embedded into business processes. For consumer goods leaders, the opportunity is therefore not simply to use AI for sustainability. It is to build an operating model where environmental intelligence becomes part of how the business understands costs, risks, suppliers, products, and opportunities. The next phase of decarbonization will not be defined by how much environmental data companies collect. It will be defined by what they are able to do with it.
