What is Shadow AI? Risks & How to Overcome It
Artificial intelligence (AI) has firmly rooted itself as an indispensable tool for many organizations. Today, 37% of companies harness AI's capabilities, with a striking 93% of leading brands setting sights on AI investment. The perceived benefits of AI are plentiful, with an overwhelming 83% of businesses banking on AI to bolster or maintain their competitive advantage. Market analysts forecast that the AI sector will touch a staggering $300 billion in the coming years.
As we navigate the AI age, it has sparked diverse conversations, from ethical dilemmas to the intricate layers of its technical prowess. The transformative power of AI is undeniable. Bill Gates stated that AI is set to redefine facets of our lives, including our work, learning, travel, healthcare, and communication patterns. Thus, integrating AI is imperative, not merely an option.
However, in the corporate IT realm, a pressing issue emerges the rise of Shadow AI. This refers to AI tools or software employees utilize without a formal nod from their IT departments. This clandestine use mirrors the challenges posed by its predecessor, Shadow IT. Both are often linked to SaaS platforms, but it's vital to underscore that Shadow AI pertains specifically to tools driven by artificial intelligence. This post delves deep into the nuances and implications of these AI-focused tools.
What is Shadow AI?
Shadow AI is unauthorized use of artificial intelligence tools and solutions within a company, often without the knowledge or consent of the IT department. This phenomenon can introduce potential risks, from data breaches to compliance issues, as these tools haven't undergone the usual vetting and security protocols.For example, a marketing team deploying a chatbot on the company website for customer support without informing the IT department is a typical instance of Shadow AI in action.
The Risks of Shadow AI
In the "Top 10 Strategic Technology Trends for 2020", Gartner highlights Shadow AI as a major upcoming challenge for organizations. Gartner describes strategic technology trends as those emerging technologies to majorly impact or reach critical adoption levels in the next five years.
According to this report, by 2022, nearly a third of organizations using AI for decisions will find shadow AI as their primary obstacle to effective decision-making. Gartner suggests that organizations create AI strategies to safeguard against shadow AI risks while reaping benefits.
IBM's recent research underscores the growing trend where 42% of businesses consider embedding AI into their workflows. Another. However, this swift adoption of AI brings with it the emergence of unauthorized and unchecked tools known as Shadow AI. This covert technology layer operates beyond the usual IT oversight, presenting many intricate challenges.
Compliance Challenges
In an era where regulations like GDPR and CCPA govern data privacy and usage, IT departments have their hands full, ensuring all tools conform. Shadow AI introduces a blind spot. Without IT knowledge, these tools might handle data or operate in ways that contravene regulations. Non-compliant tools not only risk heavy penalties but also tarnish a company's reputation, requiring firms to be extra vigilant.
Data Security Concerns
Data today is more than just information; it's an asset. Whether it's a client's personal details or an internal strategy document, such data holds immeasurable value. IT departments continually fortify their digital domains with cutting-edge firewalls, encryption techniques, and stringent access protocols. Yet, Shadow AI tools, operating on the fringes, might not be privy to these protective measures. The result? They become low-hanging fruit for cybercriminals, posing a tangible threat of data breaches and exposure.
Reliability and Trust Issues
Shadow AI tools often sidestep the rigorous vetting processes that sanctioned IT solutions undergo. This can lead to inaccuracies in their outputs or even misinformation. Misplaced reliance on these tools by employees can inadvertently steer business decisions in the wrong direction. Highlighting the pitfalls of unchecked AI, The Guardian has pointed out instances where tools like ChatGPT have produced misleading or fabricated information. It underscores the pressing need to evaluate the trustworthiness of information generated by AI systems.
Suggested reading: ChatGPT Security Risks
Overcoming the Risks of Shadow AI
While Shadow AI shares similarities with its counterpart, Shadow IT, in that they operate beyond the IT department's purview, managing them requires a proactive strategy. Relying on employees to consistently report their use of tools can be unreliable, given the natural inclination of individuals to streamline their work without always considering the broader implications.
Given this backdrop, it's evident that automated solutions are the key to detecting Shadow AI's covert operations. Most AI tools employ quick login methods, often via trusted platforms like Google or Microsoft. Users frequently overlook the permissions they grant during these seamless logins, inadvertently exposing data or system access.
Employing SaaS security platforms such as Resmo can be a game-changer. These solutions can autonomously detect when business credentials are used to log into any tool. More crucially, they can identify the types of permissions these tools request and obtain.
This hands IT departments a dual advantage: not only can they discern the range of Shadow AI tools in operation, but they can also gauge the potential risks associated with the permissions these tools command.
By leveraging such proactive measures, organizations can preemptively mitigate risks, ensuring a safer and more compliant digital environment.
It's important to keep an eye on all your tools. Want to learn more? See our guide "What is SaaS Security? Best Practices & Challenges."
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