Extract from Damir Kahvedžić’s article “Face to Face with GenAI Hype”
My wife came to me a couple of weeks ago needing to write a last-minute presentation for her work. She asked “Can we use CoPilot? I hear it can generate a presentation for me.” “Sure” I said “Your company has licensed it on your laptop. Enter a prompt and it will make slides in PowerPoint”. “Perfect!” she said. “Let’s do that”. We ran to the laptop, typed in our prompts and CoPilot dutifully created the presentation and content. It was immediate and impressive. It had the correct length, perfect formatting, a beginning middle and end and no typos. It was perfect.
My wife hated it. The content was generic, it was bland and not at all what she expected. “Where is the detail, it’s missing statistics!” She said. The reality hit her that CoPilot helped her get started but she as a subject matter expert had to finish it. She ran head-first into Amara’s Law[1].
“WE TEND TO OVERESTIMATE TECHNOLOGY IN THE SHORTTERM BUT UNDERESTIMATE THE EFFECT IN THE LONGTERM”
You can’t really blame her excitement though. This is where we were a few years ago. We were promised that we could type in our criteria and the LLMs will extract ALL privileged documents for us. It would speed up or even end review, lower costs, upend our workflows. But survey after survey has shown that even though the excitement for AI is palpable and that teams want to use it, there are lot of AI adoption challenges ahead. Costs, Data Governance, Hallucinations! Not to mention that we are still waiting for that killer app. How can we foster adoption? How can we bridge the gap between the expectations of end users, like my wife, to the reality that AI service providers like ProSearch can provide? Where in the adoption process are we?
