Trustworthy AI: India’s Blueprint for Innovation with Integrity

In the global race to harness artificial intelligence, the question of how we innovate has become just as important as what we innovate. Around the world, organizations are racing to deploy AI technologies, right from generative models to autonomous agents, with the promise of efficiency, insight, and transformation. But amid this acceleration, a critical imperative is emerging: the need for AI governance, not as an afterthought, but as a matter of design.

According to the IDC Data and AI Impact Report commissioned by SAS, Indian organizations are 21% more likely than their global counterparts to prioritize decision-making and innovation over cost savings. Their lowest priority? Personal productivity. This signals a strategic shift: AI is being viewed not as a convenience, but as a catalyst for core business reinvention. This shift also underscores the need for businesses to incorporate AI into current governance modalities, or create new ones, without compromising innovation and trust.

Trust in GenAI: Cautious Optimism over Blind Faith

Globally, trust in generative AI is surging, sometimes outpacing the reliability of the technology itself. The study found that GenAI is perceived as 200% more trustworthy than traditional AI, despite the latter being more explainable and mature. In India, however, the narrative is more nuanced. Indian organizations report 8% less trust in GenAI than the global average, yet this skepticism hasn’t slowed adoption. For enterprises, this means oversight, compliance, operating procedures and normative cultural behaviors must also evolve.

India’s AI momentum is being accelerated by a powerful convergence of public policy and private enterprise. Government initiatives like the IndiaAI Mission and Deep Tech Fund are laying the groundwork for infrastructure, domain-specific models, and start-up financing. This is complemented by corporate giants and a thriving start-up ecosystem, creating a fertile environment for scalable innovation.

The Data Paradox: Readiness Meets Complexity

50% of organizations surveyed in the study reported data infrastructure readiness. Yet, data centralization and governance remain top challenges. This paradox underscores a critical truth: as data maturity grows, so does the complexity of managing it. The rapid expansion of AI applications, coupled with dynamic data environments, demands continuous investment in data excellence.

Given the proliferation of AI features in a variety of enterprise applications, all desiring unfettered access to data for generative purposes, ethical data practices replete with intuitive privacy and security are increasingly becoming a shared responsibility for technology, processes and people alike.  

A Global Imperative: Trustworthy AI by Design

Organizations that invest in trustworthy AI are 1.6 times more likely to double their ROI. But beyond metrics, trustworthy AI is about values: fairness, transparency, inclusion, and accountability. At SAS, we believe in an “ethical by design” approach, ensuring that AI systems are explainable, auditable and aligned with human values throughout the AI lifecycle.

Through initiatives like the Coalition for Responsible Evolution of AI (CoRE-AI), we’re fostering collaboration across academia, industry, and government to advance trustworthy AI in India and beyond.

What Comes Next

In 2026, the AI debate will no longer be one of innovation versus trust. As government regulation of AI remains inconsistent, corporate self-governance will extend to include the necessary guardrails to enable AI in the enterprise responsibly. The organizations that thrive won't simply be those that deploy AI first; it will be those that recognize the strategic reality that governance isn't a restraint on innovation; it's a necessary companion.

As AI becomes more autonomous and embedded in critical decisions, the stakes will only grow. India’s journey reminds us that trust is not a byproduct of technology but a prerequisite for its success. The future will be shaped not just by algorithms, but by the choices we make today about governance, inclusion, and ethics.

By Reggie Townsend, Vice President – Data Ethics Practice, SAS

(Disclaimer: The views and opinions expressed in this article are solely those of the author and do not reflect the views of CyberMedia or its affiliates.)