Enterprise Wide Search 38: Mariana Hebborn - Enterprise AI in Practice in Pharma

Yes, they're thinking about projects and I think the most important, they turn to initiatives.

This is always an indicator for me that something that started as an idea and then moved to an MVP and a project and then continues as an initiative is maybe something that you're asking for as the most important one.

We have a Vera, you know, that for HR, everyday AI is important.

So creating content and checking documents and so on, that's nice to have.

But moving to this enterprise, AI, it's the most valuable part.

And for HR, which is a function where a lot of processes are coming again and again, and everyone is impacted in the organization, taking time off, updating master data and so on.

Virtual Enterprise Assistant is a project that it started as an idea where we brainstormed with our GHIL team and then interned to a project.

And it became so important and so complex to be set up.

that now it became an initiative.

It became an initiative and it's also a lighthouse.

I think this is something that we are very proud of.

It's not only me, but we are very proud as an HR function in such a big company to start such an AI project automation and to set it up as a lighthouse for other functions like procurement, finance and so on where they can join and we can extend that.

This is something very important.

It's nothing but talking to an assistant and the assistant is doing the work for you when you want to set up commitments to, as I mentioned, to change your address and all the different and complex HR processes that employees are dealing with where you need to click 10, 5, 5, 10, 20 times, wait for loading up documents and so on.

This is something and another project that we started working on together with my team is that AI readiness.

And this is more on this triangle mindset, technology and use cases to prepare the organization for AI.

And here we have, it's also, it started as an idea to pick up the pain points.

around HR, what are the pain points around data and analytics, not AI, based on different roles in the company, HRBPs, ISPs, experts.

And then with what we have, because in work we have a lot of up-to-date, very progressive technology and to start applying.

And the data catalog was also a part of it.

Sometimes people just need, they're complaining about not finding the report about headcount maybe because the name is not consistent.

And in a data catalog, you can see the different names of headcount, and you can search based on this definition in the analytics system for that.

You can flag it, and then it's just a click.

So this was the AI readiness, where the first part was a three-layered AI readiness, where the first part was mitigating pain points in data analytics.

The second one was grabbing the demand and creating agents.