Fighting smarter: How AI is helping plug cyber gaps before hackers strike

The adoption of AI is rapidly growing, enabling new business models and products and driving efficiencies. This spans a wide range of technologies, including self-driving cars, deepfake models and voice assistants, while also transforming industries such as finance, consumer services and healthcare.

According to a 2025 “Deloitte State of GenAI in the Enterprise” report, nearly 80 percent of surveyed organisations expect to increase their overall AI spending in the next fiscal year, signalling a widespread commitment to AI-driven transformation. Companies need to define how humans and machines interact with each other and other supply chain collaborators to optimise AI use. This would steer an enterprise-wide strategy for AI.

Key trends in using AI for cyber

In cybersecurity, AI can shift the operating model from a reactive, defence-driven approach to a proactive strategy that enables the adoption of emerging technologies while keeping organisations secure.

AI supports the development of systems that enable adaptive learning and continuous improvement. Developing an effective cybersecurity strategy with AI requires a deep understanding of the organisation’s vision, existing infrastructure and the practical applications of AI within that framework. Agentic AI enables autonomous decision-making and outcome generation. Predictive AI examines behaviour and patterns to deliver data. GenAI, on the other hand, uses creativity to generate entirely new data.

Enhancing cyber resilience through AI in cyber use cases

AI is increasingly becoming a force multiplier in cybersecurity, especially in threat detection and response. The financial impact of ransomware incidents is often severe, compounded by delays in detection and containment that increase overall risk. AI can enhance cybersecurity by identifying patterns through user and system behaviour analysis, enabling faster response times and helping organisations anticipate attacker movements before they occur.

AI enhances endpoint detection by powering advanced malware identification and enabling EDR systems to monitor suspicious activities on endpoints. These capabilities improve the detection of new and emerging threats and strengthen overall cyber defence.

One of the biggest threats organisations face is phishing, which AI can detect and prevent. For detecting phishing, AI can analyse anomalies and malicious emails and help organisations prevent it. ML also allows AI to understand user profiles and behaviours and helps prevent spear phishing. AI also helps organisations design phishing awareness campaigns for their employees through GenAI by creating customised content.

AI enhances incident response workflows by enabling automation for swift and effective reactions. These capabilities also support Governance, Risk and Compliance (GRC) functions through automated assessments, reporting, KRI and KPI tracking and control testing. In risk management, they contribute valuable insights throughout the assessment lifecycle, streamlining workflows and ensuring responsible resource allocation.

In identity and access management, AI engines provide recommendations for role maintenance, automate the access requisition lifecycle and simplify privilege access management.

AI helps organisations manage network security and cyber defence at scale by enabling decision support systems and enhancing behavioural analytics across users and devices.

Approach for unlocking the value of AI for cyber

To move towards an AI-enabled cybersecurity service, organisations must accelerate progress across several key areas. This starts with embedding AI into the existing technology stack and setting clear KPIs to track business outcomes. Establishing effective AI governance is also essential, as it involves creating guidelines and standards for development, promoting transparency and accountability in decision-making and addressing concerns such as bias, discrimination and misuse.

Organisations need to rethink their cybersecurity strategies by integrating AI capabilities and updating frameworks and policies to reflect this shift. Reskilling the workforce is important to ensure teams can use AI tools effectively to improve efficiency and reduce risk. Finally, designing scalable AI solutions is critical. These systems should be able to process large volumes of data, reduce false positives, deliver accurate results, incorporate regular human feedback and support continuous retraining.

AI: Cybersecurity’s powerful ally

The advantages of using AI in cybersecurity revolve around its ability to learn from new data, handle a vast volume of data, self-improve the model through constructive feedback and reduce costs. Automated systems help redirect resources towards high-priority tasks by handling routine operations efficiently.

With the increase in cyberthreats and sophistication of cyberattacks, AI-powered security solutions enable organisations to stay ahead in threat detection, incident management and various aspects of cyber. While AI implementation raises important security concerns, such as data and privacy, access control, integrity, logging and monitoring, its potential to enhance cybersecurity capabilities makes it a worthwhile investment. Ethical AI use, guided by trustworthy frameworks, is becoming essential as regulations evolve to protect people and organisations from potential risks.

Views are personal. Author is a Partner at Deloitte India.