AI Productivity Will Stall Without Stronger Cybersecurity

The Story in Brief

Enterprises are adopting artificial intelligence to automate work, analyse data, improve customer service and speed decisions. But the source warns that security practices are not keeping pace with deployment. AI tools can connect to internal data, APIs, cloud systems and external platforms, widening the attack surface and creating risks such as adversarial attacks, data poisoning, prompt injection and vulnerable third-party components.

The spread of generative AI beyond specialist teams can also create blind spots when business units deploy tools without security review. Chief information security officers must now protect AI ecosystems while supporting faster experimentation. The source argues that security should be built into the full AI lifecycle, including training-data checks, access controls, API protection, authentication, encryption and continuous monitoring.

The Indian Opinion

The loudest claims around AI often promise instant productivity or portray security teams as obstacles to innovation. Both views are lazy. A tool that exposes confidential data, accepts manipulated inputs or inherits a flaw from an external component can erase its claimed gains. Yet demanding perfect certainty before every experiment would also slow useful work. The practical test is whether firms can show access controls, testing and ongoing monitoring for each important deployment.

Source: ciso.economictimes.indiatimes.com

This story was synthesised by AI from the source linked above.

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