Navigating the Rise of Shadow AI: What Businesses Need to Know
A recent report from Torii sheds light on a growing concern in the business world: the rise of "shadow IT," particularly when it comes to artificial intelligence (AI) tools. In today’s tech-driven landscape, many organizations understand the potential dangers of Shadow AI, which refers to unsanctioned AI use outside the purview of IT governance. However, the reality of how widespread this issue is may come as a surprise.
Understanding Shadow AI
Shadow AI encompasses AI technologies and capabilities that exist outside official company channels. These tools often tap into proprietary data, which raises significant security and compliance issues. Furthermore, many AI solutions operate on a consumption-based pricing model, which complicates budgeting and can lead to unexpected costs.
Interestingly, not all instances of Shadow AI stem from new applications. In fact, many are AI features embedded within already sanctioned software. This makes governance all the more complicated, reinforcing the idea that Shadow AI represents the latest chapter in ongoing software governance challenges.
The Size of the Problem
According to the report, a staggering 54% of managed applications are now classified as shadow IT. As companies expand their software portfolios, Shadow AI has driven a remarkable 21% increase in the total number of applications since the beginning of 2024, creating visibility and cost-management headaches for IT teams.
Unmanaged Apps on the Rise:
- The top four unmanaged applications are entirely AI-driven.
- Four out of the next five are also dependent on AI technology.
This fast-paced adoption of AI tools outside of IT oversight creates a significant hurdle—tracking costs becomes nearly impossible due to unpredictable pricing structures.
The Hidden Costs of Inactivity
In a surprising twist, 61% of Software as a Service (SaaS) applications sit idle, yet companies continue to pay for them. Many of these applications haven’t seen an active user in the last 30 days. So why do organizations hold on to these inactive licenses? The reasons can range from lack of visibility to misguided hopes of future utility.
A Case Study: Local Impact
Consider a mid-sized marketing agency in Kansas City that recently found itself overwhelmed with AI tools. As they tried to leverage AI-driven features from tools like Salesforce, they inadvertently stumbled into shadow IT territory. Despite being a well-managed company, they found themselves paying for five different AI-driven applications that no one was using, costing them thousands each month. This situation is not unique; businesses across various sectors face similar challenges.
Take Action: Addressing Shadow AI
To combat the challenges posed by Shadow AI, businesses can take a multi-step approach:
- Inventory Your Applications: List all active and inactive applications.
- Enhance Visibility: Implement monitoring tools that provide insights into application usage.
- Establish Governance Policies: Create clear guidelines around the use of AI tools to ensure they align with business objectives and remain secure.
- Engage Employees: Foster an open dialogue with teams to understand their needs for AI tools.
Conclusion
Shadow AI is a growing reality that organizations can no longer afford to ignore. With rampant adoption of AI technologies outside formal IT channels, understanding and managing these tools is crucial for maintaining security and managing costs.
The AI Buzz Hub team is excited to see where these breakthroughs take us. Want to stay in the loop on all things AI? Subscribe to our newsletter or share this article with your fellow enthusiasts.
