As AI instruments turn out to be extra accessible, staff are adopting them with out formal approval from IT and safety groups. Whereas these instruments could increase productiveness, automate duties, or fill gaps in present workflows, in addition they function exterior the visibility of safety groups, bypassing controls and creating new blind spots in what is called shadow AI. Whereas much like the phenomenon of shadow IT, shadow AI goes past unapproved software program by involving methods that course of, generate, and probably retain delicate information. The result’s a class of threat that almost all organizations are usually not but outfitted to control: uncontrolled information publicity, expanded assault surfaces, and weakened identification safety.
Why shadow AI is spreading so rapidly
Shadow AI is increasing quickly throughout organizations as a result of it’s simple to undertake and immediately helpful, but largely unregulated. In contrast to conventional enterprise software program, most AI instruments require little to no setup, permitting staff to begin utilizing them instantly. Based on a 2024 Salesforce survey, 55% of staff reported utilizing AI instruments that had not been permitted by their group. Since many organizations lack clear AI utilization insurance policies, staff should resolve which instruments to make use of and use them on their very own, usually with out understanding the safety implications.
Workers could use generative AI instruments like ChatGPT or Claude in on a regular basis workflows, and whereas this will enhance productiveness, it may end up in delicate information being shared externally with out oversight. Whether or not or not the AI vendor makes use of that information for mannequin coaching is determined by the platform and account sort, however in both case, the info has left the group’s safety boundary.
At the division stage, shadow AI could seem when groups combine AI APIs or third-party fashions into purposes and not using a formal safety evaluation. These integrations can expose inside information and introduce new assault vectors that safety groups can not see or management. Quite than attempting to eradicate shadow AI totally, organizations should actively handle the dangers it creates.
How shadow AI is a safety downside
Shadow AI is commonly framed as a governance situation, however it’s a safety downside at its core. In contrast to conventional shadow IT, the place staff undertake unapproved software program, shadow AI includes methods that actively course of and retailer information past the scope of safety groups, turning unsanctioned AI utilization right into a broader threat of information publicity and entry misuse.
Shadow AI can result in untraceable information leaks
Workers could share buyer information, monetary info, or inside enterprise paperwork with AI instruments to finish duties extra effectively. Builders who troubleshoot code could inadvertently paste scripts containing hardcoded API keys, database credentials, or entry tokens, exposing delicate credentials with out realizing it. As soon as the info reaches a third-party AI platform, organizations lose visibility into how it’s saved or used. As a outcome, information can depart a company with out an audit path, making it troublesome, if not not possible, to hint or include a breach. Underneath GDPR and HIPAA, this kind of uncontrolled information switch can represent a reportable violation.
Shadow AI quickly expands the assault floor
Each AI instrument creates a brand new potential assault vector for cybercriminals. When unapproved instruments are adopted with out oversight, they could embrace unvetted APIs or plugins which can be insecure or malicious. Workers accessing AI platforms by means of private accounts or gadgets place that exercise totally exterior the group’s safety controls, and conventional community monitoring can not see it. As organizations start deploying AI brokers that function autonomously inside workflows, the danger grows much more extreme. These methods work together with a number of purposes and platforms, creating complicated and largely hidden pathways that cybercriminals can exploit.
Shadow AI bypasses conventional safety controls
Conventional safety controls weren’t constructed to deal with at present’s AI utilization. Most AI platforms function over HTTPS, that means customary firewall guidelines and community monitoring can not examine the content material of these interactions with out SSL inspection in place — a management many organizations haven’t deployed. Conversational AI interfaces additionally don’t behave like conventional purposes, making it more durable for safety instruments to observe or log exercise. Due to this, information could be shared with exterior AI methods with out triggering any alerts.
Shadow AI impacts identification safety
Shadow AI introduces severe Identification and Entry Administration (IAM) challenges. For instance, staff may create a number of accounts throughout AI platforms, resulting in fragmented and unmanaged identities. Builders could even join AI instruments to methods utilizing service accounts, creating Non-Human Identities (NHIs) without proper oversight. If organizations lack centralized governance, these identities can become poorly monitored and difficult to manage throughout their lifecycle, increasing the risk of unauthorized access and long-term exposure.
How organizations can reduce shadow AI risk
As AI becomes more integrated into daily workflows, organizations must aim to reduce risk while enabling safe, productive usage. This requires security teams to shift from blocking AI tools altogether to managing how they are used in the workplace, emphasizing visibility and user behavior. Organizations can reduce shadow AI risk by following these steps:
- Establish clear AI usage policies: Define which AI tools are allowed and what data can be shared. Security policies should be easy to follow and intuitive, since overly restrictive rules will only push employees toward using unsanctioned tools.
- Provide approved AI alternatives: When employees don’t have access to useful tools, they are more likely to find their own. Offering approved, secure AI solutions that meet organizational standards reduces the need for shadow AI.
- Improve visibility into AI usage patterns: While full visibility may not always be possible, organizations should monitor network traffic, privileged access and API activity to better understand how employees are using AI.
- Educate employees on AI security risks: Many employees focus only on the productivity advantages of AI tools rather than the security risks. Providing training on safe AI usage and data handling can dramatically reduce unintentional exposure.
Benefits of effectively managing shadow AI
Organizations that proactively manage shadow AI will gain greater control over how AI is used across their environments. Effectively managing shadow AI provides several benefits, including:
- Full visibility into which AI tools are in use and what data they are accessing
- Reduced regulatory exposure under frameworks like GDPR, HIPAA, and the EU AI Act
- Faster and safer AI adoption with vetted tools and thorough guidelines
- Higher adoption of approved AI tools, reducing reliance on insecure alternatives
Security must account for shadow AI
AI adoption is becoming normalized in the workplace, and employees will continue seeking tools that help them work faster. Given how easy AI tools are to access and how rarely usage policies keep pace with adoption, some degree of shadow AI in any large organization is inevitable. Instead of trying to block AI tools entirely, organizations should focus on enabling their safe use by enhancing visibility into AI activity and ensuring that both human and machine identities are properly governed.
Keeper® supports this approach directly, helping organizations control privileged access to the systems AI tools interact with, enforce least-privilege access for all identities, including human users and AI agents, and maintain a full audit trail of activity across critical infrastructure. As AI agents become more prevalent in enterprise workflows, governing the identities and access paths they rely on becomes as important as governing the tools themselves.
Note: This article was thoughtfully written and contributed for our audience by Ashley D’Andrea, Content Writer at Keeper Security.
