Op-ed by Dr Gohar Sargsyan, Head of Sustainability Business, Tata Consultancy Services (TCS) Europe, and Prof Dr Ernesto Damiani, Università degli Studi di Milano, Italy, President of the Consorzio Interuniversitario Nazionale per l’Informatica (CINI) and Acting Dean of Computing and Mathematical Sciences at Khalifa University in the UAE.
As the green transition accelerates, businesses face a dual challenge: meet increasingly complex sustainability regulations and remain competitive in a rapidly evolving market.
Driven by cost optimisation and profit maximisation, businesses often overlook crucial social costs in their decision-making. Artificial Intelligence (AI), particularly generative AI (GAI), is being hailed as a solution. But how do we ensure that these powerful tools serve sustainability goals rather than undermine them?
In our recent research, we propose a practical and forward-looking solution: use AI not just to automate decisions, but to make them ethically sound, regulatory compliant, and resilient from the outset. This is especially urgent when AI is involved in high-stakes areas like sustainable finance or gender equality, where poor decisions can have long-term social and environmental consequences.
The problem with ‘smart’ decisions
Organisations often rely on AI models optimised for cost and performance. However, left unchecked, these models can produce outcomes that unintentionally violate sustainability or human rights standards.
Consider a hiring tool that prioritises historical success metrics, often skewed against underrepresented groups. Or an AI-powered lending model that favours financially stable, traditional businesses over innovative green startups that lack credit history.
The result? A system that might reinforce inequality or stall green innovation, despite a company’s stated values.
Embedding sustainability at the core
Rather than patching models after they’ve made harmful decisions, we advocate for embedding sustainability into their very logic. Our method is based on training models with ‘legends’, idealised profiles of individuals or projects that exemplify sustainability and ethical leadership.
These legends, derived from existing regulations like the EU Green Deal Framework or Gender Equality directive, act as north stars for the AI. By feeding these profiles into the model, we help it recognise and reward behaviour aligned with ESG principles.
This is not a theoretical exercise. In a hiring context, for example, a legend might be a synthetic profile of a female leader who embodies the values promoted by EU gender equality policy. In a green finance setting, it might be a small renewable energy startup with high innovation potential but limited financial history. Training AI systems with such exemplars teaches them to balance compliance and ethics alongside profitability.
Cybersecurity and resilience: The unsung heroes
But ethics alone aren’t enough. For sustainable AI to work in the real world, it must be secure and resilient. Without robust cybersecurity, models can be manipulated, intentionally or accidentally, leading to biased decisions or regulatory breaches.
For instance, a corrupted dataset might lead to ‘greenwashing’ loans going undetected or allow adversarial attacks on hiring algorithms. Resilience also means having the flexibility to adapt quickly to new laws or risks.
Our proposal includes maintaining multiple model versions, a kind of ‘AI version control’, so organisations can instantly switch or update decision frameworks when regulations change. Think of it as a sustainability-ready reset button for AI.
From burden to differentiator
Too often, businesses view sustainability regulations as a burden. But with the right approach, compliance can become a competitive differentiator. Ethical and resilient AI systems aren’t just good for society, they build trust, prevent reputational crises, and enable faster, more adaptive decision-making.
By combining legends with secure infrastructure and model redundancy, companies can lead the way in building intelligent systems that are not only green-aware but green-driven.
The time to act is now. AI can be a powerful tool in the sustainability transition, but only if we teach it to think like a responsible leader.
Our research is ongoing: stay tuned as we further explore AI’s role in building ethical and sustainable business.
About the authors
Dr Gohar Sargsyan is Head of Sustainability Business at TCS Europe and drives the company’s sustainable business growth. She has over 25 years of experience in business and IT, including in leadership roles, and has a proven track record of implementing complex multidisciplinary initiatives and solutions for different industries. She focuses on emerging topics such as Green IT, deep tech, cybersecurity, 5/6G, ethical AI and how they can contribute to a better world. Dr Sargsyan is the recipient of the 2024 IEEE TCHS Outstanding Leadership Award.
Prof Dr Ernesto Damiani is a Full Professor at the University of Milan, Italy where he leads the SESAR Lab, and President of Consorzio Interuniversitario Nazionale per l’Informatic (CINI). He also serves as Acting Dean of Computing at Khalifa University, UAE. His research focuses on secure SOA, certifiable robust AI and data analytics models, and cyber-physical systems. He holds a doctorate honoris causa from INSA Lyon. In 2022, Ernesto was awarded the rank of the Officer of the Order of the Star of Italy for contributions to international scientific AI collaboration.
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