Using GenAI to replace cybersecurity vendor demos, insights from practical experiment.

I Tried Using GenAI to Replace Cybersecurity Vendor Demos: Here’s What I Learned

July 07, 20253 min read

By Yuda Saydun, President of CyVent

What if you could use GenAI to replace time-consuming cybersecurity vendor demos?

As a boutique cybersecurity consulting firm, we vet dozens of vendors every year. We look at everything: detection logic, roadmap alignment, SOC compatibility, and real-world performance.

That process is… long.

So I ran a test:

Could a generative AI tool handle the early stages of vendor evaluation?

Spoiler: GenAI helped - but it didn’t replace the human layer.

Here’s what worked, what didn’t, and where GenAI fits in the future of cybersecurity vendor selection.


Why We Ran the Experiment

Professional holding virtual dashboard explaining reasons behind AI experiment.

Cybersecurity leaders are flooded with AI-generated content, vendor whitepapers, and sales demos.

Our clients rely on us to cut through the noise.

That’s where generative AI technologies seemed promising. With the right prompts and training data, we wanted to see if GenAI tools - like large language models or foundation models - could:

  • Summarize vendor offerings

  • Compare key product features

  • Draft smart RFPs

  • Surface red flags

We used several AI tools, including ChatGPT and vendor-specific copilots trained on security-related data.


Where Generative AI Helped

Robot interacting with digital interface, illustrating successful AI integration.

With minimal setup, GenAI applications supported our team in the early-stage research phase:

  • Snapshot comparisons: GenAI synthesized product features across multiple vendors, helping us identify gaps and overlaps.

  • RFP prep: It auto-generated draft scoring matrices, based on our criteria.

  • Demo prep: Using AI-generated suggestions, we developed sharper technical questions ahead of time.

The result?
We trimmed days off the prep work. And we walked into demos more focused and informed.

This shows the benefits of generative AI - increased efficiency, better context, and faster execution.


Where GenAI Fell Short

Robot and human hand highlighting AI limitations in global digital transformation.

Despite its strengths, generative artificial intelligence models have clear limitations:

  • Hallucinations: Some responses sounded confident - but were factually incorrect or outdated. This is a common issue across large generative AI models trained on internet data.

  • Lack of context: The model couldn’t understand our client’s compliance requirements or business goals.

  • No judgment: Human trust-building, gut instinct, and vendor credibility are still impossible to replicate with any machine learning model.

In short: AI models can’t replace human intelligence. They can only enhance it.


Understanding the Limitations of Generative AI Models

Business team discussing limitations of generative AI in corporate strategy meeting.

At their core, generative AI models - including deep learning models, transformer models, and neural networks—are pattern recognizers.

They rely on training data sets to generate text, code, or summaries using techniques like text generation and natural language processing.

But vendor demos aren’t just about technical specs. They’re about alignment, vision, and adaptability. These are nuances that even the most advanced generative AI systems can’t capture without real-world data, experience, and context.


Why Trusted Advisors Still Matter

Businessman selecting trusted advisors in digital interface for expert guidance.

At CyVent, we’re constantly testing new AI applications and generative AI techniques. But the role of a trusted cybersecurity advisor hasn’t changed.

Vendor selection isn’t just a data analysis problem. It’s a critical thinking exercise.

That’s where CyVent adds value: Contact us to learn more.

  • We validate vendor claims against live use cases.

  • We assess fit based on your unique risk, compliance, and performance requirements.

  • We cut through marketing fluff to deliver actionable recommendations.

GenAI’s potential is huge. But it can’t replace deep expertise.


Final Thoughts

Final thoughts message on keyboard background for blog conclusion or key takeaways.

Would I use GenAI again in the vendor evaluation process? Absolutely.

But I’d never use it alone.

Because vendor relationships impact your security posture long after the contract is signed. And no AI tool - no matter how advanced - can evaluate culture, trust, and long-term fit the way a human can.

Use generative AI to speed up the process.
But don’t skip the conversations that matter.

P.S. Curious where GenAI fits into your cybersecurity stack - or which vendors are the best fit for your current needs? Book a free consultation. We’ll help you evaluate your options with clarity and confidence.






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