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The GenAI world is full of self-proclaimed experts who throw around fancy terms like LLMs, GLMs, and other buzzwords - it sounds like they're listing off their favorite candy bars, like M&Ms, Kit Kats and Snickers. But when it comes to actually using these technologies, they're eerily silent. It's like they're trying to hide their lack of practical experience behind a veil of technicalities.

These modern-day "experts" have mastered the art of regurgitating online course material, but when faced with actual business challenges, they're clueless.

Their LinkedIn posts are filled with empty buzzwords, a desperate attempt to sound smart. They rave about the latest GenAI breakthroughs, but can't explain how these advancements can actually drive business growth.

Meanwhile, business leaders are left scratching their heads, wondering how to turn this technical jargon into real-world results. They need answers to questions like:

  • How can GenAI increase revenue by X%?
  • How can GenAI increase profits by Y%?
  • How can GenAI improve client experience by Z%?

As someone who's worked extensively with GenAI, I've seen firsthand how it can be used to drive real results. Let me give you an example from the service desk.

GenAI-powered solutions like Client Assist and Agent Assist, which have transformed the way clients support their customers. Client Assist uses AI-driven chatbots to answer frequent queries and route tickets to the right agents, freeing up human agents to focus on more complex issues. Agent Assist provides human agents with real-time insights and suggestions to resolve issues faster and more accurately.

Top companies like Microsoft, IBM, Salesforce, and Zendesk are using solutions like theses to drive real results. For example:

  • Microsoft's Virtual Agent uses GenAI to handle over 10 million customer conversations per month, freeing up human agents to focus on more complex issues.
  • IBM's Watson Assistant provides AI-powered customer support and routes tickets to human agents.
  • Salesforce's Einstein gives human agents AI-driven insights and suggestions to resolve issues faster and more accurately.
  • Zendesk's Answer Bot uses GenAI to provide human agents with suggested responses to customer queries, improving response times and accuracy.

These solutions aren't just theoretical - they're tried and tested. There has been significant improvements in ticket resolution times, first-call resolution rates, and customer satisfaction scores. These companies have done it by focusing on practical application, not just technical hype.

It's time to shake the tree and demand more from our GenAI leaders. We need experts who can bridge the gap between technical theory and practical application. We need solutions, not just flashy terminology.

Let's cut through the noise and get down to business. Let's focus on creating real-world solutions that drive growth, improve efficiency, and solve complex problems. Anything less is just noise.

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