The rapid adoption of artificial intelligence (AI) tools across workplaces is creating a new cybersecurity challenge for enterprises and opening up a growing market for startups focused on AI governance, monitoring and security.
As employees increasingly use public AI platforms such as ChatGPT and Claude for drafting emails, analysing documents, writing code, creating presentations and conducting research, companies are grappling with a phenomenon known as Shadow AI — the unauthorised use of AI tools outside approved corporate systems.
Industry experts say the trend is emerging as one of the biggest blind spots for enterprise security teams because sensitive company information can be shared with external AI models without the knowledge of employers.
According to Gartner, more than 40% of enterprises globally are expected to experience security or compliance incidents linked to unauthorised Shadow AI usage by 2030.
“In India, this risk is amplified because enterprises are digitising rapidly while many are still early in their AI governance journey,” Rahul Agarwalla, managing partner at SenseAI Ventures, told Fe. “As AI adoption accelerates, visibility and control over how employees use AI will become a major enterprise priority.”
Blind Spot
Cybersecurity experts compare the phenomenon to the rise of Shadow IT, when employees adopted unauthorised software and cloud applications. However, they add that Shadow AI presents a more complex challenge because conventional security tools often cannot see what data employees enter into AI interfaces.
“When a developer copies proprietary source code into a public large language model, the data moves through an encrypted session that traditional monitoring tools cannot inspect,” Pankit Desai, co-founder and CEO of Sequretek, said. “Once proprietary code or intellectual property enters a public AI model, organisations lose visibility and control over how that information may be used.”
Startups Pioneer Traffic Monitoring
The growing concern is driving demand for new categories of cybersecurity products designed specifically to monitor AI usage, detect data exposure risks and enforce governance policies.
Deep Algorithm, a cybersecurity startup backed by Unicorn India Ventures, has developed tools that identify and classify AI-related traffic across enterprise networks. Its Connection Classification Mechanism analyses network connections and flags both known and previously unseen AI services being accessed by employees.
The company said it is seeing increasing demand from sectors such as financial services, healthcare, manufacturing, legal services and technology, where concerns around compliance and data protection are particularly high.
Another startup, AIONOS, is targeting the market through AI-powered zero-trust security systems that continuously verify users, devices and applications before granting access to enterprise data. The company also offers real-time monitoring tools aimed at detecting unusual data movements that could indicate information being shared through unauthorised AI channels.
“We see the strongest demand from highly regulated industries where data leakage can trigger significant compliance consequences,” Arjun Nagulapally, chief technology officer at AIONOS, said.
Investors and industry executives expect the opportunity to expand as enterprises move beyond AI experimentation and begin implementing governance frameworks around employees’ use of generative AI tools.
“AI is creating entirely new attack surfaces through agents, copilots and autonomous systems,” Agarwalla said. “At the same time, it is creating demand for new security layers focused on governance, monitoring and automated risk management.”
As AI adoption spreads across corporate India, cybersecurity firms expect Shadow AI management to emerge as a distinct spending category, creating opportunities for startups building tools to secure the next generation of enterprise technology.
