AI and Excel

I'm only a student so apologies if I'm way off the mark but I reckon expressing intent about what you want to do on Excel and AI doing it can't be too far off at all. Wouldn't be surprised if this becomes very common among smaller firms as they don't have as much bureaucracy as bigger ones. They will probably adopt this sort of stuff quite quickly if it saves them a couple hours  -- within 12-24 months probably. Wouldn't be out of the question to make a pretty reliable industry grade wrapper for Excel given what's already here. 

My opinion is that AI is similar to a calculator - it needs someone competent to operate in order for it to produce the right output. AI will be disruptive tech, but I doubt it will be more impactful than the assembly line, the wheel, the airplane personal computer, calculators or even excel for that matter.

I bet a ton of errors (logic, calculations, data) already exist in the average model. My guess is Claude already makes less errors than a human, we just continue to make errors in prompting and Claude is getting better at recognizing our intent even when direction is poor. Claude is only as smart as the direction given and it’s leaning to manage up.

These are the most obvious retarded AI written posts I have ever seen. 

My firm has started rolling out Claude and it's definitely a big productivity boost. It can create pretty nice-looking dashboards and cuts of data that would've otherwise taken me hours to do on my own. That said, my predictions for the AI world are the following:

1. It'll be like Excel was back in the day. It'll eliminate a lot of low-level work, but will also create a demand for deeper analysis faster from the productivity gains. So instead of my work/value-add in RX CO being creating a dozen different cuts of data to tell a story (i.e. revenue by segment, region, customer, customer-segment, etc.), I can now do that quickly with Claude, which will demand deeper analysis or allow my firm and I to help more companies in the same time frame.
2. Understanding stats/what data means will be critical. To further my analogy on the dozens of data cuts, the onus will now be on my team and I to figure out what the data is telling us and what the implications are. For example, on my current project, we spoke with management about historical win rates for projects and what the data showed is that one business segment was magnitudes above the other. So, the blended win rate Management quoted was skewed by this part of the business that was much smaller in revenue/scale and the legacy business was struggling. Now, we have to decide if we divest the legacy businesses that are underperforming, keep the smaller segment and only have management focus on bidding mid-sized work, where they're doing better, etc. AI can be a great thought partner for this, but the ultimate call will still come down to humans and often times qualitative factors
3. Domain knowledge will be really important. I think what AI will morph from these tools like Claude, that are general purpose, to domain-specific tools. At a high-level, there will likely be LLMs that are specifically designed for financial-analysis in Excel. There might also be LLMs that are designed for certain industries, etc. I have a feeling the days of being a generalist and being able to tell simple stories and analysis from cranking out various cuts of data will fade away.
4. Soft skills and presentation will matter even more. If everyone has AI, effectively nobody has AI, or it's at least not a point of differentiation. What will matter more is getting buy-in and presenting ideas and data in a clear, digestible manner to get deals/initiatives across the finish line.