Sustainable Agentic AI – Green AI White paper

Most Agentic AI conversations are missing a key dimension: cost, carbon, and complexity.

While the spotlight is often on autonomy, orchestration, and innovation, the reality is that Agentic AI systems—if not designed intentionally—carry hidden risks that quietly erode value:
❗ Vague goals that trigger unnecessary actions, retries, and compute waste
❗ Over-planning and decision loops that burn resources without meaningful benefit
❗ Overuse of large models when smaller models would suffice
❗ Redundant tool calls and uncontrolled memory growth
❗ Silent system inefficiencies that drive up cloud costs and emissions without notice

As most organizations are experimenting with or just getting started on Agentic AI, this is the right time to embed efficiency, sustainability, and cost-awareness at the foundation—not as an afterthought.

That’s why I wrote Lean and Green Agentic AI—a white paper with a practical framework for building AI that is not only intelligent but also efficient, scalable, and economically viable.

The paper introduces:
✅ The six-stage Agentic AI lifecycle
✅ Lean principles to minimize cost, carbon, and complexity
✅ Practical techniques for energy-efficient models, inference, and carbon-aware execution
✅ A standardized approach to measurement using the Software Carbon Intensity (SCI) framework and its AI extension
📄 Access the full white paper here:
👉 https://github.com/navveenb/lean-agentic-ai/tree/main/research/Sustainable%20Agentic%20AI

The agentic future is coming fast. Let’s ensure it’s smarter, greener, and built to scale responsibly.