In sustainability, every drop counts—especially in the beauty industry. While conversations around eco-friendly packaging and cruelty-free products have gained traction, water usage remains a critical aspect of environmental impact. This article explores how Artificial Intelligence (AI)-driven Life Cycle Assessments (LCAs) are reshaping our understanding of water consumption across personal care routines, helping consumers and companies make more sustainable choices to reduce their water footprint.

Understanding Water Footprints in Beauty

A water footprint measures the total volume of freshwater used to produce goods and services. In the context of beauty, this includes not just the water in the product itself, but also the “hidden” water used throughout its production: cultivation of raw ingredients, manufacturing, packaging, consumer use (e.g., rinsing shampoo or shaving cream), and disposal methods.

The global beauty and personal care industry, expected to generate $677.19 billion in 2025, depends heavily on water. From hydrolyzed proteins in serums to hydrating cleansers and water-based emulsions, the average beauty product is composed of 60–85% water. Add to this the daily usage patterns of millions of consumers, and the cumulative effect becomes significant.

Accountability in Action

AI-powered LCA insights are increasingly central to brand and industry-wide efforts, enabling transparent, scalable water stewardship. As sustainability expectations rise, both market leaders and governing bodies are stepping up to address the beauty industry’s water footprint. This shift signals not just a trend—but a transformation in how environmental responsibility is measured and shared.

Conserving Beauty

This Australian-based brand is rethinking formulation from the ground up by eliminating water as an ingredient entirely. Their waterless product line reduces both embedded water in manufacturing and the need for rinsing during use. Beyond formulations, the company is working to improve water and energy efficiency across its supply chain—demonstrating how innovation and accountability go hand in hand.

EcoBeauty Score Initiative

Driven by industry leaders like L’Oréal, Cosmetics Europe, and other global stakeholders, the EcoBeauty Score aims to standardize how environmental impact is measured and communicated in beauty. Grounded in the EU’s Product Environmental Footprint (PEF) methodology, it requires brands to use Life Cycle Assessment (LCA) data to provide science-based scores on packaging, websites, and more. This initiative is setting a regulatory and consumer transparency precedent, pushing companies toward more rigorous environmental disclosures—particularly around water use.

Together, these brand commitments and policy frameworks are accelerating a culture of accountability where water stewardship is expected.

Traditional LCAs and Their Limitations

A Life Cycle Assessment (LCA) is a method used to evaluate the environmental impacts of a product across its lifespan—from raw material extraction to disposal. While LCAs are crucial for sustainability analysis, traditional approaches are time-consuming, data-intensive, and often rely on generic datasets that fail to capture the variability of real-world usage.

For instance, a traditional LCA might estimate the water footprint of a body lotion without considering differences in application frequency, regional water scarcity, or variations in consumer behavior. This is where AI enters the picture.

The Role of AI in Enhancing LCAs

AI brings a new level of precision, scalability, and personalization to LCAs. By incorporating machine learning models AI-driven LCAs can:

Parse Product Ingredients: NLP tools can analyze ingredient lists and match them to water consumption databases.

Model Consumer Behavior: AI can simulate and predict usage patterns based on demographic, geographic, and lifestyle data.

Improve Supply Chain Transparency: AI algorithms can trace complex supply chains and estimate water use at each step.

Enable Dynamic Assessments: Unlike static LCAs, AI models can be continuously updated with new data, improving accuracy over time.

These capabilities allow brands to move beyond static, one-size-fits-all assessments and embrace real-time, product-specific environmental intelligence.

How Consumer Use Drives Water Impact—And What Brands Can Do About It

Consumer behavior—especially during the use phase—often accounts for the largest share of a beauty product’s water footprint. For personal care brands aiming to reduce environmental impact, understanding and designing around this phase is crucial. AI-driven LCAs help brands identify where usage habits have the greatest impact, enabling smarter product design and consumer guidance. Here are strategies to help influence lower water use through thoughtful innovation and communication:

Develop Waterless and Low-Rinse Products

Solid shampoos, cleansing bars, and leave-in treatments not only reduce embedded water in manufacturing but also minimize water required during consumer use. These formats are especially effective in high-use categories like haircare and body wash.

Formulate Concentrated Solutions

Products that deliver results in smaller doses (such as concentrates or powders) help consumers use less water per application. Recommending smaller amounts and providing dosage guidance can further reduce in-use water waste.

Use Alternative and Less Water-Intensive Ingredients

Brands can reduce their footprint by replacing or supplementing traditional components with lower-impact alternative ingredients and packaging materials. Environmentally conscious consumers increasingly seek out products made with less harmful, responsibly sourced inputs.

Educate Through Packaging and Digital Touchpoints

Use product labels or QR codes to share data from AI-driven LCAs, helping customers understand how to use the product more sustainably—such as shorter rinse times or water-saving tips. Education not only builds trust but also reinforces brand values.

Embrace Transparency with Dynamic LCAs

Sharing the water footprint of a product—particularly the use-phase data—positions your brand as a leader in environmental responsibility. AI-powered LCAs can make this process scalable and accurate, allowing you to provide credible insights across your product portfolio.

By aligning product innovation with real consumer usage patterns, brands can meaningfully reduce their water impact and help shape more sustainable beauty habits at scale.

The Future: AI-Powered Impact Transparency

As AI becomes more integrated into sustainability assessments, consumers may soon see dynamic water footprint labels on product packaging or apps that provide real-time environmental scores based on personal usage. Brands that leverage these technologies will be able to differentiate themselves not just by their product quality, but by their environmental intelligence. Furthermore, regulations like the EU’s Digital Product Passport (DPP) will mandate this type of transparency. 

Ultimately, it’s AI that turns good intentions into measurable action—delivering the dynamic intelligence brands need to meet rising sustainability expectations. The beauty industry’s path to sustainability must address its water footprint—an often invisible but profound impact. AI-driven LCAs offer a promising tool to measure and mitigate water consumption with far greater nuance than ever before. By embracing these technologies, both consumers and companies can play a pivotal role in creating a more water-wise future.

Ready to reduce your brand’s water footprint with precision?

Our AI-driven Life Cycle Assessments (LCAs) empower personal care brands to accurately measure, understand, and minimize water consumption across product lifecycles—from ingredient sourcing to consumer use. Whether you’re aiming for sustainable formulation, transparent reporting, or consumer engagement, our platform delivers actionable insights to drive genuine water stewardship.

Contact CarbonBright and lead the way toward a truly water-wise beauty industry.