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62% Firms Experienced Deepfake Attacks Globally In Last 12 Months, AI Apps New Target: Report | Technology News


New Delhi: As many as 62 per cent of organisations experienced a deepfake attack involving social engineering or exploiting automated processes in the last 12 months, while 32 per cent experienced an attack on AI applications that leveraged the application prompt, a report said on Wednesday. Meanwhile, 29 per cent of cybersecurity leaders feel that their organisations experienced an attack on enterprise GenAI application infrastructure in the last 12 months, Gartner, a business and technology insights company, said in its report.

The companies found chatbot assistants vulnerable to a variety of adversarial prompting techniques, such as attackers generating prompts to manipulate large language models (LLMs) or multimodal models into generating biased or malicious output. “As adoption accelerates, attacks leveraging GenAI for phishing, deepfakes and social engineering have become mainstream, while other threats — such as attacks on GenAI application infrastructure and prompt-based manipulations — are emerging and gaining traction,” said Prashast Gupta, director analyst at Gartner.

While 67 per cent of cybersecurity leaders said emerging GenAI risks demand significant changes to existing cybersecurity approaches, the report suggested a more balanced strategy is warranted.“Rather than making sweeping changes or isolated investments, organisations should strengthen core controls and implement targeted measures for each new risk category,” Gupta added.

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The report was prepared based on a survey conducted from March-May 2025 among 302 cybersecurity leaders in North America, EMEA and Asia-Pacific. Earlier, Bain & Company said in a report that at least $2 trillion in annual revenue is needed to fund the computing power needed to meet anticipated AI demand globally by 2030.

However, even with AI-related savings, the world is still $800 billion short of keeping pace with demand. The report highlighted that by 2030, global incremental AI compute requirements could reach 200 gigawatts, with the US accounting for half of the power.

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