Leveraging Technology for Sustainable Design

Using Gemini to help visualize an upcoming home design on Lake Michigan using mass timber is getting interesting! Prompting's an art, with trial & error leading to instant learning and improvement - for both Gemini and myself. Some outputs match the intention while others can miss or even surprise, sparking new ideas. I've been around for (*cough*) let's say (*cough*) a while, and I have seen architecture evolve: from hand-drawn plans using ink pens and electric erasers on mylar (my undergrad and first job out of school), to early Autocad (in grad school), to Catia and Rhino (at Frank Gehry's office), and soon after to Revit, Sketchup, and Grasshopper. Each new tool required testing and learning how to best to leverage the capabilities in order to maximize the intended creative output. Now AI's my favorite chapter! Gemini can pull from vast data – think biomimicry – which can unlock incredible design potential. I have been using Gemini also to help me research on things like mass timber best practices in a midwest climate, building code requirements, shifting my research time from weeks to hours, giving me more time for design. Mass timber best practices, material and structural efficiency, sustainably-sourced forests, instantly accessible. It feels like a superpower. I believe this next chapter with AI will democratize sustainable design, helping us all to move it the architecture and construction industry forward in ways we can't even imagine today, and make building beautiful, healthy, durable housing that is also affordable the default. #MassTimber #Gemini #GenAI #notebooklm

🌍 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐌𝐞𝐞𝐭𝐬 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐒𝐮𝐬𝐭𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲: 𝐀 𝐍𝐞𝐰 𝐄𝐫𝐚 𝐨𝐟 𝐄𝐒𝐆-𝐃𝐫𝐢𝐯𝐞𝐧 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 🤖 As businesses strive to meet ambitious Environmental, Social, and Governance (ESG) goals, #AgenticAI—AI systems capable of autonomous, proactive decision-making—can help. But its true potential is only realized when embedded within a governed, strategic enterprise architecture. To drive meaningful sustainability outcomes, we need to move beyond pilot projects and isolated green initiatives. #EnterpriseArchitects must become sustainability stewards, aligning business capabilities, digital transformation, and technology investments with ESG goals and SustainableIT.org EA principles, 668452443b06446b965a671a_SIT-Sustainability-Principles-for-Enterprise-Architecture-v1-final.pdf . Application of #AgenticAI to reach your sustainability goals: ✅ Responsible #AI by Design: EA teams should embed fairness, transparency, and carbon awareness into the #AI lifecycle. 📌 Example: A Copilot embedded in your architecture review process could flag when sustainability metrics are missing or when AI models lack transparency audits. ✅ ESG-Driven Capability Mapping: Align capabilities like low-carbon logistics or inclusive service delivery with digital transformation efforts. 📌 Example: An AI agent in a strategic planning tool could identify underperforming ESG capabilities and suggest targeted investments or transformation roadmaps. ✅ Circular IT Strategies: Plan for energy-efficient infrastructure and e-waste reduction across the IT estate. 📌 Example: AI agents can continuously monitor data center emissions, recommend workload shifts, or suggest decommissioning underutilized assets. ✅ Portfolio Governance with ESG Metrics: Score initiatives by sustainability value, not just financial ROI. 📌 Example: AI agent could analyze portfolio performance and recommend reallocation of funds toward higher ESG-impact initiatives. ✅ Architecture Decision Records (ADRs) for ESG: Document traceability of sustainable choices, alternatives, and KPIs. 📌 Example: A Copilot could auto-generate an ADR entry summarizing the sustainability trade-offs considered during an architecture review, based on design discussions and system impact data. 💡 #AIAgents are not just assistants—they can become active stewards of sustainability, monitoring emissions, optimizing processes, and ensuring compliance in real time. #AgenticAI #Sustainability #EnterpriseArchitecture #ESG #DigitalTransformation #ResponsibleAI #GreenIT #CircularEconomy #ESGGovernance #ITLeadership #SustainableIT

To leverage AI for sustainability, it is critical that this technology itself continues to improve (reduce!) its environmental impact. Today, I am happy to share that Google published a first-of-its-kind study on the lifetime emissions of Tensor Processing Units (TPUs), and outlined how they have become 3x more carbon-efficient over the last 4 years! (Blogpost here https://lnkd.in/dVnuzaaf). But what are TPUs? They're specialized hardware accelerators that help advance artificial intelligence (AI). Their efficiency impacts AI's environmental sustainability. This progress is due to more efficient hardware design, which means fewer carbon emissions for the same AI workload. Here are some of the highlights: 🟢 Operational electricity emissions make up more than 70% of a Google TPU's lifetime emissions. So, this 3x operational efficiency gain is extra important!! 🟢 While manufacturing emissions are still notable and will increase as operational emissions decrease with the use of carbon-free energy. 🟢 We've also significantly improved our AI model efficiency (i.e. the software not just hardware), reducing the number of computations required for a given performance.   🟢 This is key for our strategy to run on 24/7 carbon-free energy (CFE) on every grid where we operate by 2030. These findings highlight the importance of optimizing both hardware AND software for a sustainable AI future. It's important to remember where AI has important implications for reducing emissions and fostering sustainability - ex. AI can optimize energy consumption in buildings, improve traffic flow, and develop new materials for renewable energy technologies. On a personal level, as someone who pursued a masters in environmental management with a focus on industrial ecology, I'm particularly proud to see this kind of full lifecycle / LCA review of AI :) By taking a holistic view, we can identify and address the biggest contributors to AI's carbon footprint. #Sustainability #AI #GoogleCloud #TPU #CarbonFootprint #TechForGood #Innovation #IndustrialEcology #LifecycleAssessment