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Here’s a question most enterprise IT leaders aren’t asking out loud: what if the AI tools you added to increase productivity are actually making it worse? That’s the hidden cost of a fragmented stack — and why an llm agnostic platform is quickly becoming the smarter architecture choice for enterprise IT.
Not because the tools are bad.
Because you have too many of them, none of them share context, and your people are spending more time toggling between platforms than doing the work those platforms were supposed to accelerate.
The average enterprise knowledge worker switches between AI tools roughly 1,200 times a day. That’s not a workflow. That’s a treadmill. And it’s costing your organization north of four hours per person, per week — before you even factor in the cognitive recovery cost of each context switch.
The fix isn’t a better AI tool. It’s a different kind of infrastructure: an LLM-agnostic platform that puts a unified, governed access layer between your people and the proliferating model ecosystem underneath them.
That’s what this post is about — and why platforms like GPT Studio are increasingly relevant to CIOs trying to reduce AI sprawl without slowing innovation.
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