JP Mishra, Founder and CEO of Deep Algorithm, stated that cyberattacks are evolving from primarily human-led approaches to those propelled by intelligent systems that adapt in real time. “It’s essentially a conflict of AI against AI. Traditional security measures were designed to combat attacks from human adversaries. However, the current landscape shows that AI entities themselves are orchestrating these attacks,” he remarked in an interview with CNBC-TV18.
Mishra pointed out that these AI agents function at speeds and adaptability levels far surpassing those of legacy systems, constantly learning from each attempted breach and altering their attack methods. Consequently, organizations are compelled to implement equally advanced defenses. “To confront these types of attacks, we need AI defense systems, where autonomous AI red teams consistently scan for vulnerabilities, and autonomous AI blue teams address and patch them in real time,” he explained.
The implications are particularly profound for BFSI entities, as security breaches could lead to systemic ramifications. As financial institutions increasingly depend on digital frameworks—from payments to lending and wealth management—the attack surface has expanded, rendering traditional signature-based solutions progressively ineffective.
From an investment perspective, this technological evolution is causing a noticeable reallocation of resources. Bhaskar Majumdar, Managing Partner at Unicorn India Ventures, noted that funding is increasingly directed towards AI-native platforms that can continuously learn and adapt. “There’s a distinct shift in capital allocation—clearly moving away from static tools, which were primarily signature-based and rules-driven, towards adaptive, AI-native platforms that learn patterns on an ongoing basis,” he mentioned.
This shift is also transforming how cybersecurity is perceived within organizations. Once regarded as discretionary IT spending, it is now becoming integral infrastructure, particularly in heavily regulated sectors. Majumdar remarked, “In areas like BFSI… AI security is becoming as essential as core banking itself. Such platforms will integrate with transaction flows rather than act as overlays.”
The rise of AI-focused cybersecurity is also altering the way risk is evaluated. With both attackers and defenders employing intelligent systems, traditional underwriting models based on past breach data are becoming less relevant. While platforms designed for real-time detection and response can mitigate risk by reducing reaction times to mere milliseconds, they may also introduce new systemic vulnerabilities should widespread systems fail.
Mishra highlighted that the success of autonomous defense systems hinges on three key factors: speed, security, and governance. “For autonomous AI defense to be effective, three things are crucial: firstly, speed… secondly, native AI security; and thirdly, comprehensive governance of the entire ecosystem,” he added, noting that even defensive AI systems must be safeguarded against adversarial attacks.
Also Read | Explained: What is Mythos AI and why it is worrying banks and regulators
Conversations in boardrooms, especially in BFSI and other critical infrastructure sectors, are already mirroring this transition. The emphasis is shifting toward creating resilient, self-defending systems that can anticipate and neutralize threats before they arise.
As financial institutions intensify their digital transformation efforts, AI transcends being merely a tool for fraud detection or threat intelligence—it is increasingly becoming the battleground itself. In this developing paradigm, intelligent systems not only defend infrastructure but also learn continuously from equally intelligent adversaries, reshaping the future of cybersecurity and investment within the sector.
