From AI rush to AI trust: Why CIOs must become Chief Governance Officers

AI is fast becoming a business imperative, but unchecked deployment threatens trust and resilience. With governance lagging adoption, CIOs are now at the centre of enterprise risk and accountability.

Arijit Goswami, Client Partner at MarketsandMarkets Research

From AI rush to AI trust: Why CIOs must become Chief Governance Officers

As Indian enterprises are crossing the chasm from experimentation using AI to value realization, Chief Information Officers (CIOs) can no longer be technology enablers. Rather, they need to evolve into enterprise trust custodians, balancing innovation with data, risk, ethical and regulatory guardrails. As enterprises rush to deploy AI as a productivity booster and competitive differentiator, the rapid uptake has outpaced governance maturity, exposing enterprises to operational, ethical and compliance risks. IBM’s AI at the Core 2025 study showed 74% of organizations had only moderate (37%) or limited (36%) AI risk and governance coverage across technology, third-party and model risks. Just 23.8% reported strong frameworks, while AI adoption accelerated, with 72% of companies reported using AI in at least one business function in 2024.

India is not an exception to this phenomenon. The PHD Chamber of Commerce and Industry (PHDCCI) found that India’s AI market is projected to grow at 25-35% CAGR through 2027. This has made the imperative for robust ethics and governance frameworks more critical than ever. CIOs are now being called upon to fill this gap, not merely deploying technology but architecting the frameworks that make AI trustworthy.

The glaring gap in governance

Risk and governance frameworks are critical to keeping AI systems safe and reliable. In their absence, companies may end up introducing new vulnerabilities in their systems. In such circumstances, recovery from cybersecurity incidents may take longer, which can further impact business operations and reputation. The issue gets escalated when we consider AI-generated phishing attempts are four times more likely to compromise security measures. Yet preparedness remains weak.

IBM reported in October 2025 that 97% of organizations hit by AI-related cybersecurity incidents lacked proper AI access controls. In India, a 2025 Alvarez & Marsal study found that although 60% of firms had basic AI governance policies, only 19% conducted structured legal and ethical risk assessments, and just 22% performed AI-specific third-party due diligence, even as AI becomes embedded in customer, operational and mission-critical systems. The reasons are not hard to guess. Cost pressures, resource gaps and the speed of AI-enabled threats make governance difficult. And that is pushing many CIOs to assume an expanded role that resembles a Chief Governance Officer.

A shift in CIO’s role

In the wake of AI development outpacing governance, CIOs need to step up and plan an intentional approach to integrate governance, create security policies and assign accountability early on. This means, the CIO’s mandate is shifting from simply rolling out AI tools for productivity to institutionalizing trust by ensuring AI aligns with enterprise risk appetites, legal obligations and ethical principles.

CIOs are no longer expected to only lead their company's IT strategy and align technology with strategic business goals, they are additionally expected to convene governance bodies, such as boards, ethics committees, AI oversight councils, that embed accountability across functions. Since governance intersects with areas traditionally outside core IT, such as risk management, internal audit, legal/compliance and human resources, CIOs need a cross-functional strategy to implement governance mechanisms across the enterprise.

Vantage position of CIOs

CIOs are uniquely positioned to be chief governance officers because they already own enterprise technology, data pipelines, compliance and risk frameworks, which are the very foundations on which trustworthy AI must be built. Their cross-functional view helps align AI initiatives with business strategy, security, ethical guardrails and operational resilience, blending innovation with accountability.

CIOs must map AI systems to risk registers and align their governance structures with existing frameworks and government guidelines. They must also implement audit trails for training data and production usage; embed bias detection and explainability checks in continuous integration and deployment pipelines. Companies must also deploy continuous monitoring to detect drift and use AI governance platforms to automate policy enforcement and model lifecycle control, as Gartner projects a significant reduction in ethical incidents with mature governance tooling.

Way forward for CIOs

For CIOs, the real shift is mindset. AI governance cannot be treated as a brake on innovation, rather it must be positioned as the engine that makes scale possible. Trust is fast becoming a business metric, influencing customer loyalty, investor confidence and regulatory comfort. That means governance must be shared, not siloed.

The most effective leaders are building cross-functional councils where risk, legal, data and business teams co-own AI decisions instead of reacting after deployment. Equally important is measuring how safely AI performs, how bias is reduced and how resilient systems remain. As AI grows more autonomous, governance must evolve continuously, guided by leadership that sees responsibility as a strategic advantage, not a compliance burden.

In an era where AI ubiquity is undeniable, trust will define long-term enterprise value, not just technology. This demands CIOs to reimagine their role as Chief Governance Officers to steer their organizations through compliance complexity, ethical risk and stakeholder expectations, making AI safe, reliable and future-ready.