Information retrieval chatbots: the cost of playing it safe

I've been reflecting and talking with my peers across different companies, and here's what I'm seeing: Everywhere I look, enterprises are building the same thing - their own version of ChatGPT for internal data.

Yes, I'm part of this trend. For the past few months, I've been implementing these conversational AI chatbots across various use cases within our company, and I genuinely enjoy it. We take pride in building sophisticated solutions that retrieve data from multiple sources, maintain role-based access controls, and ensure proper governance and security. This work is important, helpful, and practical.

But here's the paradox: In our race to implement AI, we've taken perhaps humanity's greatest technical achievement and turned it into a glorified filing clerk. Imagine giving Leonardo da Vinci a set of crayons and asking him to stay within the lines.

I imagine an AI that sits in our meetings like a phantom maestro, orchestrating the best from each participant while staying behind the curtains - and this isn't science fiction. With Microsoft Teams integration, speech recognition, and a simple prompt like "Monitor this conversation for cognitive biases and SWOT elements, suggest relevant business frameworks when the discussion stalls," we could have an AI that actively enhances team collaboration. The frontier models already know these frameworks better than most humans - we just need to let it use them.

I dream of AI copilots for negotiations that don't just assist, but transform the process. Picture this: an agent analyzing meeting transcripts in real-time, comparing proposed terms against your historical deals, highlighting potential leverage points, and suggesting proven negotiation techniques from Harvard's Program on Negotiation. The basic prompt could be as straightforward as "Monitor for negotiation tactics, flag manipulative language, and suggest counter-strategies based on BATNA principles."

The technology isn't a distant dream. Microsoft Copilot Studio already has the building blocks: real-time speech processing, Teams integration, document analysis, and custom GPT model deployment. Combined with Power Automate for workflow automation and Power BI for visualization, we can build these solutions today - often with surprisingly little coding effort.

Instead, we build digital bureaucrats. Rigid assistants asking "How may I help you today?" with all the warmth of an automated phone system.

The appeal of another document retrieval bot is clear: easy to measure, easy to optimize, easy to justify. But playing it safe means missing the revolutionary potential of human-AI collaboration.

And here lies the irony: In our attempt to make AI practical and safe, we're creating a convenient mediocrity at the speed of light. I believe we can do better.

The immediate threat for enterprise isn't AI replacing jobs - it's the cost of lost opportunity of playing it safe. While we're perfecting our retrieval chatbots, someone else is reimagining what's possible.

We can ship AI solutions fast. Now comes the harder part: inspiring organizations to dream bigger. To see beyond the obvious use cases. To build something worth building. And to educate broad audience on what is possible with modern frontier GenAI models.

The technology is ready. The blueprints exist. The AI labs know how to build incredible models - BUT they don't know how to transform enterprises. That's our challenge. What we need now is the courage to push beyond the familiar.

Because if not us, who will?

#EnterpriseAI #Innovation #DigitalTransformation