The shadow AI problem: A cost perspective

You’re seen it before. A new tool pops up, seemingly out of nowhere, rapidly gaining traction within the organization. Users are raving about the benefits, departments are integrating said app with other applications, and suddenly, it’s a crucial part of the infrastructure – all without a single “approved” stamp from IT. This is called shadow IT and it’s a constant battle, but there’s a new, more sophisticated invader on the scene: Artificial Intelligence (AI).

AI is no longer a futuristic fantasy. It’s here, it’s being adopted, and it’s often doing so under the radar (and surprising us all at renewal). Marketing teams are using AI-powered content creation tools, sales is leveraging AI for lead scoring, and even HR might be experimenting with AI-driven resume screening. While the potential benefits are undeniable, this rapid, often uncontrolled adoption of AI introduces significant challenges for IT.

The AI paradox: Innovation vs. vulnerability

Organizations are rightly pushing for AI adoption to gain a competitive edge. The promise of increased efficiency, improved decision-making, and personalized experiences is too tempting to ignore. However, this very push creates a paradox. The speed at which AI is being integrated often outpaces security considerations, turning these innovative tools into potential vulnerabilities, and making security, ultimately, IT’s responsibility.

Think about it:

• Data security: AI algorithms thrive on data. Are you confident that the data being fed into these AI applications is secure and compliant with regulations like GDPR or HIPAA? Where is this data stored, and who has access to it? Unsanctioned AI tools might be sending sensitive data to third-party servers you know nothing about.
• Access control: Who has access to these AI applications and the data they process? Are standard authentication and authorization protocols being followed? A rogue AI tool with broad access can be a nightmare scenario.
• Compliance: Many industries have strict compliance requirements. Are the AI tools being used compliant? Can you demonstrate that they are? A non-compliant AI application can lead to hefty fines and reputational damage.
• Bias and fairness: AI algorithms can inherit and amplify biases present in the data they are trained on. This can lead to discriminatory outcomes, creating legal and ethical risks.

Detecting the undetectable: Treating AI like shadow IT

The challenge with AI is that it often hides in plain sight. It’s not always a standalone application; it can be integrated into existing software, making it harder to detect. This requires a new approach to shadow IT detection.

Enhanced monitoring, user education, AI discovery tools, and established vendor management practices are all crucial for successfully finding AI in your tech stack. Manual methods of detection will not be enough.

You’ll want to look out for unusual data flows, API calls to unfamiliar services, and using a robust SaaS spend management tool to pick up on any new applications or unexpected price increases.

Making room in the software budget for AI

The rising tide of AI adoption is inevitably forcing organizations to re-evaluate their software budgets. The question isn’t if AI will require investment, but where that investment will come from. Simply put, if the need for AI solutions exists, budget adjustments will be necessary.

To effectively accommodate the integration of these innovative AI applications, a thorough review and optimization of existing software spend is crucial. Doing this manually is akin to driving through a busy intersection blindfolded – inefficient, risky, and likely to yield less-than-ideal results. The intelligent way involves leveraging a SaaS spend management platform like BetterCloud.

With a centralized, comprehensive view of your entire tech stack, BetterCloud offers unprecedented visibility into often-hidden software spending. This “single pane of glass” perspective empowers organizations to pinpoint redundancies and inefficiencies that might otherwise go unnoticed.

For example, BetterCloud can detect duplicate functionalities across different applications, allowing you to consolidate and eliminate unnecessary subscriptions.

Freeing up resources that are essentially going to waste allows you to make room for potential AI investments, ensuring that the organization is not only adopting cutting-edge technology but also doing so in a fiscally responsible and strategic manner.  By optimizing existing SaaS spend, organizations can pave the way for seamless AI integration without necessarily increasing their overall IT budget, maximizing the impact of both current and future technology investments.

IT’s winning strategy is proactive AI detection

By proactively addressing the challenges of AI in your tech stack, you can turn a potential vulnerability into a powerful asset. It’s time to bring AI out of the shadows and into the light, ensuring that innovation and security go hand in hand. This not only protects your organization but also positions IT as a strategic enabler of AI-driven transformation.

Looking to start freeing up software spend for AI? BetterCloud is here to help. Schedule a demo.