India’s software outsourcing industry is globally recognised for its scale, expertise, and cost efficiency. It has evolved from basic IT to high-end services like AI, cloud, and cybersecurity, and now holds over 50-59% of the global IT outsourcing market. However, the rapid rise of “Shadow AI” – the use of unauthorised, unmonitored artificial intelligence (AI) tools by employees – is posing a significant threat to the industry. While designed to boost productivity, this trend creates critical vulnerabilities that threaten the industry’s reputation for data security, compliance, and reliability.
“Outsourced software development teams in India work under intense pressure to deliver quickly and cost-effectively, making productivity-enhancing AI tools irresistible even without approval. The distributed nature and shared infrastructure of outsourcing work makes oversight inherently more challenging than with centralised in-house teams,” says Ofer Klein, co-founder and CEO of Reco, a SaaS and AI security company, which is headquartered in New York and has significant operations and engineering based in Tel Aviv, Israel.
Reco offers a comprehensive approach to managing shadow AI by providing real-time visibility into both sanctioned and unsanctioned AI usage. With its advanced monitoring tools, security teams can continuously track AI usage, detect suspicious activities, and mitigate unauthorised access. Its platform helps reduce the SaaS attack surface by managing risky vendor connections, monitoring data exfiltration risks, and ensuring proper governance of all applications.
Klein explains that shadow AI has become a pervasive enterprise security threat. It refers to developers using generative AI tools like ChatGPT, Claude, or GitHub Copilot without authorisation from their organisation’s IT or security teams. These tools actively process and learn from submitted data, creating unique risks around intellectual property theft and data leakage. “Many Indian developers are in their early careers and may not understand the legal implications of using unauthorised tools,” he adds.
Why Client Trust is at Stake
For outsourcing firms serving multiple clients, developers may inadvertently mix proprietary code from different projects when using the same AI tools. The primary risk is data exposure when developers paste proprietary code, API keys, or business logic into public AI tools that may retain and train on this information. AI-generated code may also introduce licensing issues, security vulnerabilities, or fragments from other organisations’ codebases.
For teams handling multiple clients, there is cross-contamination risk where insights from one project influence another through AI assistance. Unauthorised AI usage often violates contractual obligations and regulatory requirements like GDPR or HIPAA that clients expect their vendors to maintain. This translates to direct liability. The integrity of the software supply chain is compromised, risking IP leakage, regulatory penalties, and reputational damage. The very cost and agility benefits of outsourcing are negated by these hidden AI exposures.
As India is a global hub for outsourced software development, companies here could face contractual penalties, client losses, and litigation potentially worth millions if shadow AI leads to intellectual property theft or data breaches. “India’s outsourcing sector, which has spent decades building trust, could see major IT firms face negative impact,” says Klein.
Three-Pronged Strategy for Secure AI
In his opinion, outsourcing companies need to implement clear written policies defining approved AI tools, permissible data types, and consequences for violations, with mandatory developer acknowledgment. They need to provide enterprise-grade alternatives like GitHub Copilot for Business or Amazon CodeWhisperer that offer data privacy guarantees, while maintaining productivity benefits. They should also deploy technical controls including data loss prevention software, network monitoring for unauthorised AI services, and endpoint security to detect shadow AI usage.
Klein recommends conducting regular training on shadow AI risks using real incident case studies and practical techniques for safe AI usage, while establishing a formal request process for evaluating new AI tools, turning developers into partners rather than rule-breakers.
Reco’s technology provides comprehensive visibility into all SaaS and AI applications across an organisation. The platform can identify which developers access unauthorised AI services, what data they are exposing, and whether usage violates client contracts or regulations. The technology can also monitor for risky behaviours like unusual data transfers to AI platforms or suspicious patterns between code repository access and AI service usage.
“For outsourcing firms managing multiple clients, Reco segments visibility by project to ensure compliance across all engagements. The platform also automates policy enforcement by blocking high-risk AI tools, while allowing approved alternatives,” he adds.
