Integrating generative AI effectively into sustainability strategies (SUS205)
Integrating Generative AI into Sustainability Strategies
Key Takeaways
Generative AI (Gen) is revolutionizing various industries and can be leveraged to address sustainability challenges.
Customers are interested in understanding how Gen can help them achieve their sustainability goals and targets.
Successful Gen applications for sustainability require a solid data foundation, comprehensive data platforms, and effective data governance.
Mercado Diferente, a Brazilian online grocery startup, is using Gen to build innovative solutions to reduce food waste and improve customer experience.
Architectural considerations for leveraging Gen in sustainability solutions include identifying high-impact opportunities, choosing the right tools, defining clear KPIs, and educating teams on emerging technologies.
Leveraging Generative AI for Sustainability
Emerging Opportunities with Gen
Gen is being used across industries, including finance, supply chain, marketing, and sales, to solve sustainability challenges.
Examples include NASDAQ using Gen to build risk profile scores based on sustainability parameters and customers in agriculture and ocean transportation using Gen to tackle complex problems.
Applying Gen to the ESG Workflow
Gen can help address pain points in the typical ESG workflow, such as market trend analysis, ESG compliance, and data collection and validation.
Customers are using Gen-powered chatbots to streamline ESG reporting and identify data gaps for meeting new regulations.
Operational Challenges with Gen
Data challenges: Collecting the right data and dealing with the digital transformation of sustainability data.
Technology integration: Integrating Gen applications with different platforms and scaling them across the business.
Importance of data governance: Ensuring proper data lineage, access controls, and governance for sustainability data.
Mercado Diferente's Sustainability Journey
Company Overview
Mercado Diferente is an online grocery store in Brazil focused on making healthy, fresh food more accessible and fighting food waste.
They use machine learning algorithms to personalize grocery selections based on customer preferences and dietary needs.
Introducing Tedy: An AI Kitchen Assistant
Tedy is a Gen-powered AI assistant on WhatsApp that helps customers reduce food waste by providing recipe suggestions, meal planning, and product information based on their refrigerator contents.
Tedy has achieved significant engagement, with over 700,000 messages in the first four weeks and 71% of customers interacting more than five times per week.
Architectural Approach
Mercado Diferente's architecture leverages AWS services, including Amazon Bedrock, Amazon EKS, Amazon OpenSearch, and Amazon S3, to power Tedy's Gen-based functionality.
Key strategies include prompt engineering, retrieval-augmented generation, fine-tuning, and continued pre-training to customize the Gen models to their specific business needs.
Recommendations for Implementing Gen in Sustainability Strategies
Identify high-impact opportunities to solve with Gen.
Choose the right tools and services to ensure flexibility, scalability, and data governance.
Define clear KPIs to measure the impact of your Gen-powered sustainability initiatives.
Invest in educating your team on the latest developments in Gen and other emerging technologies.
Start small, customize with your data, and scale your Gen-powered sustainability solutions.
Additional Resources
AWS Sustainability website: [QR code]
AWS sustainability solutions and data sets: [QR code]
Reach out to the presenters (Raul, Paulo, Bianca) for further assistance.
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