AI technologies are increasingly influencing how organizations operate across business, sustainability, policy, and organizational development domains. In 2025, generative AI is already being used to support decision-making, enhancing collaboration, optimizing operations, and driving systemic change in complex real-world environments where values, context, and care matter deeply.
Beyond technical tools, AI is beginning to reshape organizational structures, governance frameworks, and environmental practices. Understanding these shifts is essential for those leading strategy, systems change, sustainability, or organizational development.
This page presents a curated set of resources and reports that explore AI’s widening role within social, ecological, and organizational systems. These insights highlight opportunities and challenges related to governance, workforce evolution, environmental impact, and ethical AI use—offering a grounded view of what responsible AI adoption means in practice.
The state of AI: How organizations are rewiring to capture value
This 2025 McKinsey survey offers a practical snapshot of how organisations are adapting to generative AI in real time. It’s useful reading for those working in strategy, systems change, or organisational development, showing how firms are shifting workflows, investing in governance, and responding to risks like inaccuracy, IP concerns, and cybersecurity. With insights on where AI is being applied—and how roles, policies, and capabilities are evolving—it provides a grounded view of what mainstream AI adoption looks like in practice.
Environmental impact of AI: Balancing innovation with sustainability
This article explores AI’s environmental footprint—from intensive energy use in data centres and hardware production to escalating carbon emissions and water consumption—while acknowledging its potential to optimise renewables, conservation, agriculture, and climate modelling (reducing emissions by up to 4%). It’s essential reading for anyone in sustainability or systems design: it outlines both the urgency of greening AI infrastructure and practical actions—from edge‑AI to greener data centres and conscious AI use—that organisations can follow.
Environmental impact of AI: Balancing innovation with sustainability
Michael Vereb (2025) compiles research detailing AI’s substantial environmental footprint, including intensive energy use in data centers, hardware production, and water consumption. Alongside these challenges, the resource highlights AI’s potential to optimize renewable energy, conservation, agriculture, and climate modeling—helping reduce emissions by up to 4%. Sustainability and systems design practitioners will find this content useful for navigating the urgency of greener AI infrastructure and adopting practical, responsible AI practices.
AI governance and responsible use
Published by PwC (2025) and supported by frameworks from OECD, this resource examines emerging legislation, corporate governance, and transparency in AI use. It provides essential guidance for governance, risk management, and compliance professionals responsible for aligning AI initiatives with ethical standards and evolving legal expectations. Practitioners gain insights into accountability measures and reporting frameworks critical for responsible AI governance in complex organizational contexts.
The GenAI divide: State of AI in business
The State of AI in Business 2025 Report, by Aditya Challapally and colleagues at MIT NANDA, examines how generative AI is being adopted in practice. Drawing on 300+ case reviews and 52 interviews, it highlights the “GenAI Divide”: while many firms experiment, only 5% report real transformation or ROI. For practitioners, it offers clear insights into adoption pitfalls, vendor strategies, and the conditions where AI can deliver meaningful impact.
More information on the use of AI can be found through the LfS generative AI landing page. This includes links to the related resource page Using AI in research and practice and the accompanying posts: AI as a thought partner: reflections on collaborative practice and systems work and AI prompts for shared thinking: a light framework for purposeful prompting.
[* Image by Jintana / Adobe Stock]
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