As India becomes increasingly dependent on digital payments, online banking, cloud services and connected devices, cybersecurity is becoming more important than ever. Every digital transaction creates an opportunity for convenience, but it can also create a potential target for cybercriminals.

Artificial intelligence is now changing both sides of this battle. Security teams are using AI to detect suspicious activities and investigate threats, while cybercriminals are using similar technology to make scams more convincing and automate attacks.

The growing importance of this issue was highlighted at the India Mobile Congress 2026, where cybersecurity, AI security and protection of digital infrastructure emerged as major themes. Discussions also emphasised the need to address threats such as cyber fraud and deepfakes.

What Is AI-Powered Cybersecurity?

Traditional cybersecurity systems often rely on predefined rules, known malware signatures and security alerts. These methods remain useful, but they may struggle when attacks change their behaviour or exploit previously unseen weaknesses.

AI-powered cybersecurity uses machine learning and other AI techniques to analyse large volumes of information, identify unusual patterns and help security teams prioritise potential threats.

For example, a security system may flag a login attempt because it differs significantly from a user's normal activity. It could also identify unusual network traffic, suspicious email attachments or a series of transactions that appear inconsistent with established behaviour.

AI does not eliminate the need for cybersecurity experts. Instead, it can help them examine information more quickly and focus on the incidents that require attention.

Five Ways AI Is Transforming Cybersecurity

1. Detecting Fraud in Digital Payments

Digital payment platforms process enormous numbers of transactions. Identifying fraudulent activity among legitimate payments can be challenging, particularly when criminals change their methods frequently.

AI systems can analyse transaction patterns, device information, account activity and other signals to estimate whether a transaction appears suspicious.

For instance, an unusual sequence of payments or a sudden change in account behaviour may trigger additional verification. However, automated systems can also produce false alarms, so financial institutions need effective processes for reviewing flagged transactions.

2. Identifying Phishing Emails and Fake Messages

Phishing scams attempt to trick people into sharing passwords, banking details or verification codes. Attackers may impersonate banks, delivery companies, employers or government departments.

Generative AI can make fraudulent messages sound more natural and help criminals produce personalised communications at scale.

Cybersecurity systems can also use AI to identify suspicious wording, misleading links, unusual sender behaviour and other warning signs. Nevertheless, no detection system is perfect.

Users should remain cautious of unexpected requests for money, urgent demands for confidential information and links received through unverified messages.

3. Detecting Deepfakes and Voice Scams

AI-generated images, videos and voices can be used to impersonate real people. In a common type of potential fraud, a criminal may imitate a manager or family member and request an urgent payment.

AI tools can help analyse audio, video and digital metadata for signs of manipulation. However, deepfake detection is an evolving field, and a detector's result should not be treated as conclusive proof.

A safer approach is to verify unusual requests through a separate, trusted communication channel. For example, call the person using a number you already know rather than relying on the number or link provided in the suspicious message.

4. Finding Software Vulnerabilities

Software vulnerabilities can allow attackers to gain unauthorised access to systems. Security teams are increasingly exploring AI tools to review code, identify suspicious patterns and help investigate potential weaknesses.

These tools may accelerate parts of security testing, but findings still need validation. AI can overlook genuine problems or report issues that are not exploitable.

Organisations should combine automated analysis with secure development practices, regular updates, independent testing and responsible access controls.

5. Responding to Cyberattacks Faster

When a cyberattack occurs, security teams must understand what happened, identify affected systems and decide how to contain the incident.

AI-assisted systems can help correlate alerts, summarise technical evidence and recommend possible response steps. Some systems can also automate carefully defined actions, such as isolating a suspicious device.

However, high-impact actions should be governed by clear policies and appropriate human oversight. An incorrect automated response could interrupt legitimate services or damage important systems.

Why AI Can Also Make Cybercrime More Dangerous

AI is not exclusively a defensive technology. Criminals may use it to generate convincing phishing messages, translate scams into multiple languages, imitate voices or automate parts of their operations.

A Reuters report published on October 9, 2026, described increased cybersecurity concerns in South Korea and Japan amid the growing use of AI-assisted techniques by attackers. The report highlighted the importance of strengthening defences as these tools become more accessible.

This creates an ongoing challenge: security teams must improve their defences while attackers continually experiment with new methods.

How Can Ordinary Users Protect Themselves?

Technology can help identify threats, but everyday habits remain essential.

• Use strong, unique passwords and enable multifactor authentication wherever possible.

• Never share an OTP, banking PIN or password in response to an unsolicited call or message.

• Verify urgent payment requests, even if the caller appears to be someone you know.

• Avoid opening unexpected attachments or clicking suspicious links.

• Keep your phone, computer, browser and applications updated.

• Review bank alerts and account activity regularly.

• Download applications only from trusted sources and check the permissions they request.

If you suspect a financial cybercrime in India, contact your bank promptly and report it through the National Cyber Crime Reporting Portal or the national cybercrime helpline at 1930.

What Businesses Need to Do

Companies should treat AI cybersecurity as part of a broader security strategy rather than a standalone solution. This includes controlling who can access sensitive information, monitoring unusual activity, maintaining backups and preparing an incident-response plan.

Businesses using AI systems should also restrict the information and actions available to automated tools. Regular assessments can help identify weaknesses before attackers exploit them.

Employee awareness is equally important. Even sophisticated security software cannot prevent every incident if staff members are tricked into revealing credentials or approving fraudulent requests.

The Future of Cybersecurity

AI is likely to become an increasingly important part of digital security. It can help organisations process information, detect patterns and respond to threats more efficiently, but it also gives attackers new ways to scale their activities.

The future will therefore depend on a combination of smarter security technology, strong regulation, responsible AI deployment and informed users.

As digital services continue to expand, cybersecurity will no longer be merely a technical concern for IT departments. It will be a basic requirement for protecting personal information, financial assets and public trust in the digital economy.