AI for Sustainability: From ESG Analytics to Agentic Operations

From sustainability data to governed operations

The book examines how AI changes ESG disclosure, ratings, greenwashing detection, carbon accounting, climate risk, earth observation and sustainable finance. It connects those applications with responsible AI, organizational design and capability building.

Indian and international cases, named frameworks, exercises and discussion questions support decisions about how a sustainability function should use and govern AI.

What readers will learn

Distinguish predictive, generative and agentic AI applications in sustainability.
Evaluate ESG data, disclosure and carbon-accounting workflows.
Assess AI applications in climate risk, adaptation and earth observation.
Examine verification needs in carbon markets and sustainable finance.
Choose what to buy, configure, build and govern in a sustainability function.
Connect responsible AI with talent, budgets and organizational accountability.

Connect the analysis with a management decision

Applied exercises and discussion questions ask readers to work with a specific organization, distinguish sourced facts from recommendations and justify their choices. The representative sample produces a capability-building plan with an indicative budget.

Read before you decide

Explore the book and its sustainability exercises

Read a representative chapter, then try its capability-planning exercise online.

Book sample · Chapter 14

Building AI-for-Sustainability Capability: A CSO Perspective

Vendor Selection, Build-Versus-Buy, Talent, and Governance From the Chief Sustainability Officer’s Seat

The chapter includes a build-versus-buy framework, case illustrations, an applied exercise, discussion questions and endnotes.

Read sample chapter →

Practical work sample

Sustainability Capability Exercise Sample

AI for Sustainability: From ESG Analytics to Agentic Operations

Prepare a plan covering tools, configuration, governance, talent, budget and supplier participation.

Read capability exercise →

A framework from Chapter 14

Frameworks from the book

The Build-Versus-Buy Decision Across the Three Waves

The chapter proposes a default for each wave, adjusted to the organization’s context:

Predictive measurement: buy mature tools and concentrate on selection and integration.
Generative reporting: buy and configure around the company’s data, frameworks and obligations.
Agentic operations: buy available components, build context-specific capability and govern autonomy internally.

The framework helps locate the internal work and budget required at each stage.

Read Chapter 14 for the framework and its application →

View all 16 chapters

Part I: Foundations

The Convergence of AI and Sustainability
Why Three Decades of Measurement-Bound Sustainability Are Coming to an End
AI Fundamentals for Sustainability Professionals
What the Sustainability Officer Needs to Know to Procure, Govern, and Trust AI

Part II: Esg Disclosure And Investor Tools

AI for ESG Data Extraction and BRSR Reporting
Why India’s Disclosure Framework Is Unusually Amenable to AI
AI-Powered ESG Ratings, Screening, and Investor Tools
Whether AI Resolves the Ratings Credibility Crisis or Deepens It
Greenwashing Detection: NLP, Anomaly Detection, and Disclosure Quality
Why Verification Continuity Wins the Arms Race Against Fluent Generation
AI in Corporate Carbon Accounting (Scope 1, 2, 3)
How the Three Waves Make the Unsolvable Scope 3 Problem Tractable

Part III: Climate, Nature, And Markets

AI for Climate Risk: Scenario Modeling, Physical Risk, and Transition Risk
How AI Collapses the Hazard-Data and Modeling Constraints, and Makes Climate Risk Continuous
Earth Observation: Satellite, Remote Sensing, and Biodiversity Monitoring
How the View From Above Became a Sustainability Commodity
AI for Climate Adaptation
The Under-Treated Half of Climate Response, Where India Is Most Exposed
AI in Carbon Markets: MRV, Registry, and India’s CCTS
Why India Should Build the World’s First Agentic-Native Compliance Carbon Market
AI for Sustainable Finance and Green Bonds
From Periodic Auditor Review to Continuous Use-of-Proceeds Tracking

Part IV: Governance, Capability, And The Indian Frontier

Responsible AI for Sustainability
The Footprint and the Accountability of the Tools That Dissolve the Constraints
The Reorganization of the Sustainability Function
Where the Thesis Pays Off: The CSO Role Strengthens for the AI-Fluent and Commoditizes for the Rest
Building AI-for-Sustainability Capability: A CSO Perspective
Vendor Selection, Build-Versus-Buy, Talent, and Governance From the Chief Sustainability Officer’s Seat
India’s Climate-Tech Ecosystem
The Practical Testbed for the Book’s Thesis
The Agentic Trajectory: What Comes Next
India’s Rare Chance to Build Sustainability Infrastructure for an AI-Native Era

Learning and teaching support

Teaching and study resources

Applied sustainability exercises

Exercises connect chapter concepts with plans, budgets and specific organizational decisions.

Discussion questions

Chapter questions support analysis of the argument and its application to an organization.

Frameworks and decision tools

Named frameworks help readers structure choices about capability, workflows and governance.

Case illustrations

Indian and international examples connect the concepts with sustainability practice.

Key terms and further reading

Chapter terms, endnotes and further reading support study beyond the public sample.

Academic evaluation

Faculty can enquire about inspection copies and the materials available for their intended use.

How resource access works

Public evaluation: read the chapter, exercise and framework example online.

Purchaser resources: resource packages and downloadable access will be confirmed when sales open. Purchaser access is not yet active.

Faculty resources: ask about inspection copies and currently available teaching materials. Restricted resources require faculty verification.

Academic inspection and resource enquiries

Considering this book for a course? Request an inspection copy or ask about student and faculty resources. Include your institution, role and intended teaching use.

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