Why Ethical AI Should Be a Top Priority for Every Tech Leader Today

Artificial intelligence is no longer the technology of the future; it is deeply embedded in how businesses operate, make decisions, and engage with customers. In India, AI adoption is accelerating. A  NASSCOM report last year noted that over 70% of enterprises are either piloting or scaling AI initiatives. From logistics and loan underwriting to customer service and diagnostics, AI is influencing decisions that directly impact lives. Yet, ethical governance is trailing behind. While leaders are quick to fund AI initiatives, few are addressing foundational concerns such as bias, privacy, and accountability. This widening ethics gap is no longer just a regulatory or reputational risk—it is a strategic vulnerability.

Bias and Explainability: Foundations of Trust

Bias in AI systems is among the most pressing concerns. These models learn from data that often reflects existing social and institutional inequalities. In India, where disparities around gender, caste, and access to opportunity persist, biased algorithms can compound real-world prejudice, whether in hiring, lending, or access to services. Tackling this requires proactive audits, more representative datasets, and inclusive design practices.

Many advanced AI models, especially those based on deep learning, operate like black boxes, producing outcomes with little clarity on how decisions are made. In highly regulated sectors such as banking, insurance, and healthcare, this opacity can be a serious liability. Explainable AI (XAI) frameworks are helping decode AI behavior and restore trust. Embedding explainability and fairness into the model development life cycle is not just a technical exercise—it’s essential for compliance, user confidence, and social credibility.

Privacy and Accountability: From Compliance to Competitive Edge

As AI systems consume vast amounts of personal and sensitive data, privacy and data protection are becoming non-negotiable. India’s Digital Personal Data Protection Act (DPDPA), enacted in 2023, has laid down clear rules around how companies must collect, store, and use data. Non-compliance carries financial and reputational consequences, making privacy by design a strategic imperative. Technologies like federated learning and differential privacy are emerging as viable solutions, enabling data-driven innovation without compromising user identities. For businesses operating across geographies, these practices are not just about meeting regulations; they’re also about earning consumer trust in a privacy-conscious market.

Simultaneously, accountability around AI decisions is coming into sharper focus. As AI gets deployed in mission-critical contexts, whether predicting creditworthiness or powering government schemes, clarity around responsibility is essential. Who takes the blame if something goes wrong: the algorithm’s creator, the deploying company, or the system itself? Indian enterprises must prepare by establishing formal governance structures, assigning responsibility at the leadership level, and monitoring the evolving global regulatory landscape. Several large IT and financial services firms have already formed internal AI ethics boards, signaling a shift from optional to essential oversight.

The India Imperative: Building Ethical, Inclusive AI

India’s digital public infrastructure is growing rapidly, and AI will increasingly intersect with essential domains like healthcare, education, and governance. In this context, ethical AI is not just a safeguard—it’s a differentiator. If done right, it can enable equitable access, enhance citizen services, and unlock long-term business value in one of the world’s fastest-growing digital economies.

We are at a turning point. AI innovation is outpacing the frameworks designed to guide it, and the risks are real—but so is the opportunity. By placing ethics at the core of AI strategies, addressing bias, ensuring transparency, prioritizing privacy, and embracing governance, tech leaders can shape AI that is not only powerful but also principled, inclusive, and trusted.

By Sneha Banerjee, Enterprise Analyst, ManageEngine, Zoho Corp.

(Disclaimer: The views expressed in this article are solely those of the author and do not reflect CyberMedia’s stance.)