In AI Pilot Mode? Learn How to Scale AI Securely Without Shadow IT
You’ve seen the demos. You’ve run the pilots. Maybe you even deployed something that works, but is it scaling? Are your users utilizing it on a daily basis, or as intended? Or is it quietly gathering dust next to the last three tools that were supposed to change everything?
Scaling AI the way most vendors describe it—connecting more tools and piping more data into more systems—doesn’t lead to progress or productivity. Rather, it results in additional risk.
More tools mean more places for data to hide. That leads to zero visibility. When visibility diminishes, compliance becomes untenable because data governance breaks. You end up cleaning up a six-month-old mess before you even knew there was a problem.
So you stay in pilot mode. It’s not because the tech isn’t ready. It’s because the approach is wrong.
In our recent webinar, Senior Solutions Engineer Kaitlyn Allen and SVP of Products Greg Neustetter tackled this challenge by sharing how we navigated our own internal rollout of AI initiatives. Read on for the highlights, or watch the complete discussion on-demand.
Key Takeaways From the Conversation
- Get more out of your AI initiatives, without moving data: Not every problem requires an agent. We’ll provide insights into how to enable teams to use AI securely, the way they want, without shadow IT.
- Strategies to build truly useful automation: From document reviews to compliance tagging, hear how organizations are solving these problems within a governed platform that holds up with real business context
- Our updated agent builder: Learn how our new agent builder makes it easy to create and manage AI agents in plain language—no developers needed, just full control and fast results.
Our SVP of Products is heavily involved in our internal rollout of AI, and he shared insights on how we manage that iterative process. One key takeaway is, there is no one-size-fits-all policy or program. This isn’t a technical issue, but a change management and process oriented challenge that requires special care to tackle.
The Real Reason AI Adoption Stalls
Most AI rollouts look great in a boardroom but falter in the real world. They fail the moment someone tries to do actual work with actual business data.
The standard playbook for scaling AI is to connect more tools and pipe more data into more systems. It sounds like progress, but it's actually the opposite—it's how you multiply risk.
Every new tool is another place for data to live, another place for it to hide, another gap in visibility. And once visibility goes, governance goes with it. Compliance becomes a guessing game. You're not managing your data anymore, you're cleaning up a mess you didn't know existed.
Meanwhile, the underlying problem never got solved. An estimated 80%-90% of enterprise data is unstructured. It’s scattered across drives, folders, and systems that weren’t built with AI in mind. When AI searches that data, it’s like looking for a needle in a dark mega-warehouse. The outputs are inconsistent and the search can be noisy. That impacts users’ interpretation of, and enthusiasm for, the AI solution.
Eventually, errors pile up, delays form, trust breaks down, and the pilot gets shelved. But, the executive team’s desire to maximize AI usage doesn’t go away. This describes the problem of trying to build off of an unstable foundation, something we tackle in our intelligent content extraction brief.
Scaling off of that can make the situation worse. Every time a team finds a tool that actually works, they move or connect the data to it. Now your data is outside your platform, your controls, and your oversight.
The use of personal accounts for business has been growing. That isn’t just a compliance failure. It’s teams finding the path of least resistance because the approved option fails them. As a result, users resort to Shadow IT to accomplish their business goals.
Strict policies can’t fix this alone. A better foundation can.
Watch the Session or Explore More
If you’re balancing the pressure to adopt more AI while automating more processes, and protecting against data exposure and Shadow IT, this session gives you a valuable plan from leaders who have deployed these solutions. You'll leave with actionable ways to expand AI adoption without expanding risk.
AI adoption isn’t slowing down. How you scale it determines whether it’s an asset or a liability.
