With a complex IT backbone, Mumbai-based Kokilaben Hospital struggled with fragmented security tools, making threat detection and response time-consuming. Managing cyber security across multiple dashboards required hours of manual effort, leaving potential security gaps. By deploying Check Point’s AI and ML-powered solutions, the hospital achieved real-time threat intelligence, automated vulnerability detection and a unified security platform. Kokilaben Hospital’s security team can now swiftly detect, analyse and remediate threats from a single intuitive dashboard.
Similarly, Alkem Laboratories, operating 24/7 in a highly regulated environment, faced rising cyber threats and an overwhelming volume of phishing attacks, with over 50 daily reports of malicious emails. Here again, Check Point’s AI-powered solutions helped the pharmaceutical giant with automated threat prevention, secure remote access, and real-time AI-driven threat intelligence. As a result, phishing reports have dropped from 50+ per day to zero, security management is streamlined, and Alkem’s cyber defences are future-proofed.
Sundar Balasubramanian, MD, Check Point Software Technologies, India & South Asia, said, “AI adoption is no longer optional but a competitive necessity. However, enterprises must address critical concerns like security, compliance, and ethical AI usage. AI-driven automation can streamline operations, but without robust safeguards, it can also introduce new vulnerabilities.”
Google’s decision to buy the cybersecurity firm Wiz for $32 billion comes at a time when AI is bringing new risks and multi-cloud and hybrid are becoming the norm. Recent reports underscore the growing cyber security risks fueled by AI. Check Point’s Threat Intelligence Report shows that Indian enterprises faced 3,284 cyberattacks per week in the last six months — almost double the global average. Against this backdrop, organisations are looking for cybersecurity solutions that mitigate AI risks, improve cloud security and span multi-cloud.
The Cisco 2024 AI Readiness Index reveals that only 18% of organisations in India are fully prepared to deploy AI technologies, down from 26% last year, underscoring growing security challenges. Despite 57% of companies investing 10-30% of their IT budgets in AI, many still face infrastructure challenges, data security risks, and governance gaps, hindering their ability to fully leverage AI securely. “With 73% of businesses expecting a cybersecurity incident within the next 12-24 months, the urgency to strengthen security frameworks and build cybersecurity expertise has never been greater,” said Samir Kumar Mishra, director, Security Business, Cisco India & SAARC.
According to Saket Verma, cybersecurity practice leader, Kyndryl India, the increased adoption in AI has led to an expanded attack surface making organisations more vulnerable. While data security gaps persist, and weak governance exposes sensitive information, many firms overlook AI-specific attack vectors, assuming traditional controls suffice. “To close these gaps, businesses must adopt zero-trust AI architectures and chief information security officers must take ownership of AI security, integrating robust governance, continuous monitoring, and least-privilege access to ensure AI remains a business enabler — not a security liability,” he added.
Understanding AI security risks varies across firms in India and globally. While large enterprises, especially in regulated sectors such as banking, life science and healthcare, and technologically mature enterprises, are prioritising AI security, many organisations still struggle with effective implementation. “AI security concerns are acknowledged, however, the proactive adoption of security measures is still evolving. Also, most companies today struggle with prioritising what, when, and how to quantify the risk and implement the right security measures, leading to gaps in their AI risk management strategies,” said Muthumari S, global head of AI Studio, Brillio.
Interestingly, while companies rush to integrate AI into their systems, many are yet to recognise that AI systems themselves can become targets. “We have reached a place where vulnerabilities, malware, and targeted attacks on AI systems are becoming real concerns,” said Sunil Sharma, vice-president — Sales, Sophos India and SAARC. If security isn’t built into AI adoption strategies from the start, businesses risk creating blind spots in their own defenses. He feels that businesses should also prepare for the rise of multi-agent AI systems, where attackers can orchestrate multiple AI models to automate complex cyberattacks.
In the process of AI adoption, enterprises must prioritise data privacy, model integrity, and cyber resilience to ensure secure and responsible implementation, feels Puneet Gupta, VP & MD, NetApp India & SAARC. Data poisoning — where malicious inputs compromise AI models, can lead to flawed decision-making, and threats like model theft pose risks to an enterprise’s intellectual property. Another risk is that AI-driven automation expands the attack surface, introducing potential vulnerabilities in cloud and hybrid environments. “It needs to be a practice to embed security at every stage of AI deployment, so that enterprises can harness AI’s potential without compromising data integrity, compliance, or cyber resilience,” he added.
