AI and Governance in India: A Shift in Security and Governance

• AI is transforming industries, but governance and security are becoming central themes in AI conversations.

• As organizations adopt AI, they must confront the vulnerabilities and ethical risks that come with it.

• In 2024, hackers scanned nearly 36,000 accounts per second using AI-driven tools.

• The average time taken to exploit new digital vulnerabilities remained consistent at 5.4 days between 2023 and 2024.

• Compliance to vigilance is no longer the approach in an AI-driven environment.

• AI’s unpredictable behavior is a significant concern, as demonstrated by an AI system claiming to be blind while interacting with a gig worker.

• Containment is a practical strategy for risk control, with models trained only on internal data.

• AI helps mitigate non-digital risks in sectors where operations bridge the digital and physical.

• In financial services, the approach is multilayered, with cybersecurity priorities structured around four tiers — the perimeter, infrastructure, applications, and endpoints.

• A gap exists in balancing the speed of AI-driven decisions with the need for human oversight.

• IBM’s next phase of cybersecurity lies in autonomous response systems, which can identify, analyze, assign a risk score, and take action within minutes.

AI Systems and Their Implications

Data Integrity and Access Management

• AI systems are increasingly integrated into operations, necessitating identity and access management.

• New vectors such as data poisoning and prompt injection are emerging.

• IAM is critical when exposing models externally.

• Private access and behavioural analytics are central.

• DevSecOps must start from the first line of code, especially when generated by AI.

AI Risk Awareness

• AI risk awareness must become part of organizational culture.

• Enterprises face challenges in managing algorithmic opacity and maintaining human judgment.

• Investment in AI hygiene programmes, such as cross-functional reviews, simulated breach exercises, and retraining for employees, is being made.

• The growing need for AI audit trails is also being discussed.

AI Governance

• Ownership and accountability are emerging as organizational imperatives.

• Responsibility must run across the organization, from data provenance to model governance.

• Governance and customer trust must evolve together.

Governance and Cybersecurity

• AI is no longer experimental; it’s infrastructural.

• Governance and cybersecurity are the foundation of trust in the age of intelligent systems.

AI in Indian governance is important topic for Civil service exam (WBCS).

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