Peter McCrory

So early adopters use the chatbot to complete very sophisticated tasks through multi-turn interactions.

Businesses learn that there's immense economic value there should they be able to provide the right contextual information.

And then over time, that gets embedded in business workflows.

Yeah, I think that that's an interesting point.

observation, and I think it illustrates the fact that, I mean, so one implication of this report was the sort of uneven impact that across different sorts of jobs, and the fact that some jobs are likely to be fundamentally transformed and maybe even have greater risk of displacement.

So if you take into account task reliability, like what is Claude really good at doing?

And you look at what are the tasks that are very time intensive for certain types of workers.

You plug that into what data we actually see on our platform.

You get a nuanced picture of sort of who is exposed to AI.

One example here would be sort of data entry workers.

These are tasks where in our analysis, Claude is pretty reliable at extracting information in standardized ways from sort of natural language reports.

that's the most essential task in that job.

And I mean, maybe to your point, that's

where it might be more straightforward for businesses to figure out how to automate that specific workflow.

In our data in this report, we actually saw a jump in office and administrative usage as a total share of our API traffic, suggesting that businesses are broadening out beyond just coding related tasks in how they choose to sort of deploy the tool into these like back office administrative support

tasks.

It's not obvious.

I don't think that this means that your job will become sort of less meaningful or more meaningful.

but it may mean that your job fundamentally changes.

For data entry workers, maybe that type of role becomes more, and this is very speculative, so you can push back, but maybe someone needs to manage more the sort of relaying of information that Claude is providing.