AI Is Changing the Artifact of Work
AE001S2 · by Alexey Makarov — AI Strategist, Practitioner & Educator · Founder, AI Center of Excellence
AI doesn't just make work faster. Sometimes it changes the work completely.
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AI doesn't just make work faster. Sometimes it changes what the work actually is. For years, the standard way to present a project inside a company was a PowerPoint. You collect information, structure slides, present the idea. The artifact of work was always a slide deck. Something interesting is happening now. For certain types of projects, it may be faster and more convincing to generate a simple interactive prototype rather than actually building slides. So instead of presenting the idea, you are presenting the working thing. There is also another alternative which I personally use quite often.
Instead of presenting the final result of the analysis in PowerPoint or Google Slides, I more and more ask AI Assistant to generate me a simple HTML page, which I can present to various stakeholders. HTML is a native format for large language models because it's written using simple words, which LLMs understand really well. There is no need for AI to use Python or any other tool when working with HTML. It is not the case when you are working with PowerPoint or Word. AI there need to use Python to understand what is written in the document and also to communicate your changes, the things you require to change in the document inside this Word and PowerPoint.
The artifact of work is changing. And I think this is really important to understand to anyone who is doing any sort of AI enablement in their company. When the artifact changes, the workflow changes. And when the workflow changes, the role of the person doing the work begins to shift. This is why deploy the tool and train employees doesn't create transformation on its own. If you treat AI as a faster way to do the same thing, you miss what is actually changing. The work itself is changing.
And that requires a different kind of preparation than a standard training session. Thank you for watching, and I'll see you in the next video. Bye.
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