# Microsoft CEO Nadella on How AI Can Change Workflows

*Bloomberg Television* · https://www.youtube.com/watch?v=XDBLWU1kcCo

## Summary

Microsoft CEO Satya Nadella discusses how AI changes work, work artifacts and workflows, comparing it to the shift brought by the PC era. He describes how Copilot has inverted information flow inside Microsoft, flattening organizational structures. He argues that realizing AI's productivity gains requires a mindset change, new skills, and proper data context, and that results will vary by firm depending on leadership.

## Key points

- Nadella says the big challenge with new technologies is when work, work artifacts and workflows change, forcing firms to change how they work.
- He recalls the CEO of Generali describing how the PC replaced faxes and interoffice memos and changed entire work processes.
- Nadella now prepares for his roughly 50 bilateral meetings at Davos by asking Copilot for a brief instead of relying on his field team's notes workflow used since 1992.
- Copilot gives him a 360 view, capturing information about clients, investments and relationships, which he shares back with colleagues across functions.
- He says AI flattens information flow in organizations, inverting the classic model where information trickles up through departments.
- His formula for taking advantage of AI is mindset, skills, and the data set or context you feed the intelligence layer, which some call context engineering.
- He warns firms may not see immediate productivity results because they must do the hard work of organizational change, and differences will come down to leadership.
- He stresses that leaders must use AI to learn how to put guardrails in place to trust it, rather than being afraid of it.

## Notes

### AI and workflow change
- Satya Nadella frames the challenge of new technology as the moment when work, work artifacts and workflows change, which means firms have to change how they work.
- He recalls meeting the CEO of Generali, who joined the firm pre-PC era and described how faxes and interoffice memos with field agents were replaced by spreadsheets sent by email, changing the entire work process.
- He sees AI driving a similar kind of change in how work gets done.

### A personal example with Copilot
- Preparing for about 50 bilateral meetings at Davos used to follow a workflow unchanged since he joined Microsoft in 1992: his field team prepared notes, which were refined at HQ.
- Now he asks Copilot for a brief before meeting someone, and it gives him a 360 view, capturing information about the relationship as client, partner and investment.
- He shares that brief immediately with colleagues across all functions.

### Flattened information flow
- Nadella describes this as a complete inversion of how information flows in an organization, replacing the classic model where information trickles up through departments and specializations.
- Once information flows freely, the current structure may no longer make sense and firms have to redesign structurally.

### The formula: mindset, skills, data
- Mindset: leaders should think about changing the work and workflow with the technology.
- Skills: you have to use the tools to trust them and learn how to put guardrails in place, rather than being afraid of AI.
- Data: the intelligence layer is only as good as the context given to it, which people describe as context engineering; firms hold tacit knowledge and must give AI that context.

### Why productivity gains vary
- Firms may not see immediate productivity results because they have to do the hard work of change.
- There will be firmwide and sector-wide differences, but outcomes will fundamentally come down to leadership within the organization.

## Transcript

[00:00] The big challenges with all of these new technologies is when work, work artifact and workflow changes That means We as firms have to change how we work. In fact, I remember meeting the CEO of Generali, you know, a few years back, and he was describing he had joined the firm, you know, pre pc-era and and he was describing how, for example, they worked with their agents in the field with faxes, interoffice memos and and suddenly the PC showed up and people would then put a spreadsheet in an email and sent it around and the entire workflow and the work process changed. Right. So similarly, I think with a AI, you are going to start seeing actual change in how what happens. I mean, even in fact, for me coming to Davos, you

[00:57] know, what about 50 bilateral meetings I have preparing for those how to had a particular workflow, right, which is that has to be my field team would prepare notes that would come to my HQ and that would get further refined. And nothing had really changed right since I joined in 92 to essentially even a few years back. Whereas now, I just go to Copilot and say, Hey, I'm meeting Larry, please give me a brief and it comes back and use me. By the way, the one nice thing is it gives me a 360, right? It knows what we are doing with you as a client, what we are doing as a client of yours and everything, I mean, as an investment. It's so it captures event information unlike anything else. In fact, what I do is I take that and immediately share that back with all my

[01:43] colleagues across all the functions. I think about it. It's a complete inversion of how information is flowing in the organization. It's not like this classic. We have an organization, we have departments, we have these specializations and the information trickles up. No, no, no. It's actually it flattens the entire information flow. So once you start having that, you have to redesign structurally. So the current structure may not make sense because you want people to be able to work in a way that allows them to have this information flow freely. So what all this leads me to, if I have to sort of say, what's the formula? The formula, I think it starts with the mindset. So the mindset we as leaders should have is we need to think about changing the

[02:37] work, the workflow with the technology, then that needs skill set. So you can sort of talk about this in the abstract. You got to use it like, so if I'm not using that, you have to trust it, you have to trust it, you have to use it, you have to learn even how to put the guardrails to trust it, right? You can't again, you can't just be afraid of it. It's going to it's going to be diffuse. So the question is, as a firm, you have to use it to learn how to even put the guardrails that allow you to be able to trust it. So skills, so mindset, skills. The other big consideration really is how do you make sure you have the data set that you're feeding like context. It's kind of like you have a new intelligence layer, but the intelligence

[03:27] layer is only as good as the context you give it. So people describe it even as context engineering. But that is what firms do, right? If you think about what do firms do, it's all about the tacit knowledge we have by working as people in various departments and moving people and information. So the question is, how do you really have this AI also have that context? So these are sort of some of the new things that have to percolate throughout an organization to take advantage. In fact, that's why I think you're going to see that challenge of why am I not seeing immediate results in productivity? Because you have to do the hard work. In fact, that's why it's not going to be some you know, it's going to they're going to be firmwide differences.

[04:12] They're going to be they could be sector wide differences, but it's going to fundamentally be because of the leadership within an organization.