Patterns of Success | Michelle Lancaster from Microsoft & Mitch Ashley

Hey everyone, it's Alan Shimmel from Techstrong. Again, welcome to our next session in our recent Rum Techstrong sessions with our friends at Microsoft. Today's session is patterns of Success and IT features Michelle Lancaster, general manager and partner for GLO and Global Leader for business strategy and AI Business Solutions at Microsoft and Future's own Mitch Ashley software development life cycles.

Michelle is gonna unpack the patterns of success emerging from the most transformative customer engagements Microsoft has seen in this particular session. You're gonna see how organizations are successfully operationalizing AI through apps, agents in chat to drive measurable outcomes. It's not science fiction, it's not vaporware.

These are real live engagements that are with real outcomes and real metrics to look at. You can expect a strategic overview of what is really working, why it matters, what's not working, and why that matters. And you can use these insights to drive and scale business impact with intelligent apps.

Let's go to Michelle and Mitchell now. I hope you enjoy the session. Thanks Alan.

My name is Mitch Ashley and I am VP and practice lead of the software lifecycle engineering practice at the Futurum Group. And I'm Michelle Lancaster. I lead business strategy and our go-to-market team for Microsoft's AI business solutions team.

Michelle, I'm really excited to talk to you about this. The market is really energized around agentic business applications, AI agents, all of this. What's your experience about how customers are approaching and and reaching out to go after this to start to energize their businesses with these technologies?

We've seen in the past six months or so, a lot of the hype cycles start to turn into the tricycle and that is not a three-legged instrument here. It's really how do we go from thinking about AI and applications as something that people want to dabble in into something that is the future of their business. We're starting to see apps and agents and copilot come together, starting to see the power of taking automated applications powered with agents and humans and running copilot over top of it as their overall UX system.

We're starting to see people go from individual productivity to things like how can I change the way my business operates? And we're starting to see some really impressive results in terms of not just time savings, but real dollars saved as well across many industries. Yeah, I'd love to hear s some about the organizational patterns that are coming about that are helping enterprises, uh, successfully coordinate multi-agent orchestration across business functions to help 'em deliver an impact.

It's a big question. Maybe we'll try to take it bit by bit. Multi-agent orchestration gets at the forefront of where real transformation starts to happen.

Having individual agents improve efficiency is one thing. Um, multi-agent orchestration can actually drive that business transformation. That orchestration layer brings this back into the heart of what I think the Microsoft value proposition is, which is not just the agents and the automation intelligence, but back to the core of security and governance.

So you need to make sure that we have governance in place, we have rules in place, we have the group identities in place and we've cleanly defined those. It turns out that's also the secret sauce of the organizations starting to move forward. Finding the right use case and them starting with a foundation of security and a clear understanding of what the KPI is for that use case sounds relatively simple, but it is really the ticket to success of people going from lodging, individual agents seeing full scale business process transformation.

You know, Michelle, it seems like we're kinda moving beyond the technology as the variance are really how we approach implementing ai, whether it's as a productivity aid or marketing agents to do workforce or even autonomous type agents. Can you talk a little bit about that progression and how uh companies are approaching it? Yes.

We really see this as a concept that we've called the Frontier Firm. We see that evolution through three different stages. It really starts with humans using agents as assistant.

Think of co-pilot where you can summarize a team note or be reminded of the most important email in your box. Really a individual worker aid around productivity and we see lots of people experimenting in this space. We move into that second phase, which is humans working directly with agents, so more of an autonomous agent that is able to run a process but is human led.

The human is directing it to do work, seeing the recipients of that work and then continuing to move forward. People have started using researcher or analysts to summarize things, um, ahead of a a meeting though that agents really taking on that research work for you and delivering the final product with that prompt. What's really exciting is the number of companies we see shifting into the third stage of this, which is autonomous agents working with other agents and working with humans.

Some of the places we start to see that advancement happening is in industries like manufacturing where there are fairly complex processes where you are able to have multiple different types of agents working together to solve a problem. One of our customers has taken a look at supply chain management. They have an agent that's keeping track of the inventory inside all of their workplaces, um, and in the places where they need to ship products, they have a reasoning agent going over top of that and saying, based on these numbers, based on what we're seeing in the predictive workflows, where do we need to up, uh, increase or decrease the amount of changes?

How do we then communicate that to the agent who does order fulfillment? That used to be a human being looking across multiple different kinds of spreadsheets, multiple different systems. The agents are there to work together to bring some of the complexity out, improve the efficiency, and then give that back with a human who's overseeing that work.

And some of those gains there are really impressive. You know, we've started to see things like 30% increases in order fulfillment and at a 40% decrease in the overall sort of stack housing costs of extra inventory sitting on the shelves for too long. And that's our aspiration is to make sure that all companies are starting to work across that flow.

You'll see productivity gains, we will see um, ongoing transformation that true sort of transformation takes place when you have all three of those opportunities realized inside the firm. Yeah. Let's turn our focus to kinda the guidance that we can offer folks about how to successfully implement AI and agentic applications.

First, could you share maybe an example of a customer who measured a meaningful business outcome from their AI implementation? I might give you two. Um, because the first one that always comes to mind for us is Microsoft, our, our own best customers.

We get tons and tons of calls from customers, from everything about Xbox logins to changing their Windows application to understanding why their surface laptop is not working. Um, we're able to quickly sift through all of those issues, but the game changer has been the existing platform been built on a power app. How are we able to sort of assistance for those call center folks?

We now have a set of agents that are able to classify exactly what type of issue it is, match it to the right human being. They're provided the latest information on any of the common outages challenges that we're facing in that space. They're able to get on the phone fully confident that they know exactly what is going on with it has really helped the efficiency of folks in those call centers that assistive technology was able to take an average person going from about a hundred calls a day to 300 calls a day.

That's pretty big increase in what a human being is able to do and that's because they're able to more easily dispatch and resolve those calls with uh, a happy customer. And that's the second thing which I get super excited about. Efficiency is what we should largely expect, um, from agents and ai.

You don't always think of human satisfaction, um, in the space, but we should are callers. They weren't waiting on the phone as long. They got more pertinent information, they were talking to somebody that was able to cut directly to the chase.

That is a really exciting sort of value. Flip to the other side, we have seen in that industrial IOT space, large scale manufacturers operating heavy industrial equipment, they have had sensors on them forever, but those sensors have typically fed into an application. There's lots of data, there's very little insight.

Introduce agents that can quickly make sense and build out the insights. And that customer was able to take that existing infrastructure, the work that they had already built on power platform to automate processes and have agents go through to start to make the predictive maintenance decisions. What they've seen is about, uh, $50 million, um, cost savings just in the first factory they implemented alone.

And they're also able to see quite a bit of, um, improvement in terms of efficiency in servicing those. No longer do you have a single person checking the spreadsheet or checking all of the sensors and you're able to precision, um, pinpoint. That's sort of the, the next frontier of that is when we're able to start to take human intelligence on those systems, combine it with an agent that's able to reason over data and to make a recommendation that is then able to be followed.

And we're talking about AI results, talking about the human element. What are the cultural or team structural changes that are effective or essential for scaling ai? Uh, this is probably the most critical question and that's an easy thing to say.

What we've seen is, uh, largely learned through what Microsoft has gone through. We know that for the culture to be in place, you have to create, you have to start with security and governance, really starting with understanding. You've got to make sure that people have a bit of psychological safety with the information being disclosed.

You also build psychological safety with the fact that there is a future for humans in all of these work streams. When we talk about the Frontier firm, there's not an instance where there is not a human being involved in those processes. It becomes a question of how can you build trust in the data that's being provided?

So you feel like it's assistive and additive. There are also organizational protocols that are really important. That also goes back to security, um, and governance, but it also goes to some level of explainability.

We talk a lot about evaluations, we talk a lot about benchmarks. Um, that's not just to make the products better, it's also to really make sure that if you're trusting an agent to run a part of your business, you want to see some type of performance report the same way that you wanna see that from an individual employee. Are they doing their job?

Are they learning over time? That's why we've put a lot of focus into things like uh, agent Observability, the ability to run that through the governance center and power Automate. We've had this as part of the core of that product for a long time, something that we've built in throughout.

So it really starts with, you know, trust from the individual trust in the process and then trust in making sure that you have, um, some uh, level of observability into that process to continue to make it better. Michelle, let's talk about power platform and the role that it plays in simplifying multi-age and orchestration across different modalities like chat apps, backend systems and and also how we interact with that because agents are a little different than how they have to be managed. It's a great question.

Um, it's one that I am really glad you asked because we are getting lots of questions about what is the future of power platform and apps and what is the future of agents and the answer is they are better together agents interacting with different applications inside the business, through the work that we've already done. Inside Power Platform tends to be the, the ticket to success. In fact, some of our biggest customers we have seen Power platform power users have become the fastest adopters of copilot Studio and Agent is because that DNA is already there.

We have built the Maker platform, the ability for observability as well as the data feeds. And so that's really the, the fast pass towards ai. The organizations that have already taken the time to organize data, secure the data fi figure out the right identities and have the right systems in place to manage across are gonna be the one the first.

Um, and certainly some of our biggest users have done this from oil and gas all the way to financial services, have used Power app and Power Platform as the jumping off point for their agents and they started with those agents attached directly to those apps as really uh, sort of the people that are at the forefront at that frontier firm curve. It's really intriguing the agent feed, tell us more about that and how that works. Agent feed is one of our secret weapons.

As AI adoption rolls out across the organization, what Agent Feed does is that it provides that level of observability into both the application and the agent interactions. So you're able to see agents, you're able to see the interaction of how that agent is interacting with all of your data sources as well as the interaction with the application. And that's super important because it is the way that we can continue to have the human element.

We're making sure those agents are making the right decisions that they're picking from the right data sources and we're able to continue to make sure they are getting better at their jobs. That is something we feed back into all the work inside our engineering teams. Part of both a continuous process loop's also something that the makers and the creators and the owners inside the business can take to make sure that we're working on the highest order problems, that they're finding the right solutions and moving really quickly, How does ENT automation reshape the way applications are designed, deployed, uh, even delivered, you know, built especially by end users Already?

We've seen a great adoption of power platform, but it's still been a relatively IT driven, um, activity. We have lots of different types of makers, but when it comes to an application that is widely used through an organization that is still largely more in the, the technical space, the intersection of these two trends though really start to open up the door for everyone. My background is a hundred percent in sales and marketing.

I've built three agents that are now working with one of the power applications we have on our dashboard. It has really changed the, the ability for folks to think about a problem, identify sort of what the parameters of that problem would need to be, identify some data sources and move pretty quickly to get that done. So in my case we are going from, you know, multiple meetings where you have multiple different ask, um, how do we synthesize those and how do an app is running and tracking our feedback.

I no longer have to send a bunch of emails out to the field telling them that's what's happening. The agents are collecting it, they're updating the information, the app is tracking. We've just given access to that.

I am just one example. We see many organizations with which we're working right now of where you have someone who is able to identify a problem that's common to the rest of the organization, find a solution and get it out pretty quick. And the beautiful thing about that interrelationship between power platform and that agent maker space is that it's not just someone, um, you know, off doing something that then gets stuck.

Uh, when you're using that defined identity group, you can go from a single maker to widespread uh, adoption and that's the curve that we see. Can everybody create and can everybody create a solution that is common to many and being used in a sort of exponential effect. You know, you talked about end user builders creating applications, we've been doing that right with technology, uh, platforms that we've had up to this point.

But you said something really interesting about going beyond what we're capable of doing today. Building agents, you know, never imagining that that was something to do. Talk about what that, what that looks like, what that future, what's possible for, for the end users in a world where they don't have to go to it for everything.

Yes, and I would be in big trouble if I cut my IT friends out. But I think there is a place where in the right sort of culture dimensions, you've already defined the identity groups, you define the problem and you've, I uh, been been able to put the parameters around security. So really being very clear about which information sources to pull from that part is also something that used to be a, a pretty complex task requiring a lot of negotiation when we do that now in this environment, we're able to either rely on existing identity groups and security protocols that are native in power platform or we're able to really quickly give that direction to an agent by saying please only pull from these types of things.

So for example, if you're using researcher, you can say please only pull from our internal work documents. As we think about widespread adoption, it is really shortening the curve to creation and then being able to demonstrate value. That is the key crux IT professionals usually care about system access and the system I identity pieces.

'cause that's what makes sure that nothing crashes. They also care about usage. You're making sure we start with security in mind and then we solve that most repeatable use case tends to be the thing that has, um, enabled makers to create and then it to love this stuff.

You know, when we talk about builders, you, you might imagine starting completely from scratch, but we're really not. We have a lot of things in place that it has put in place and also that are built into kind of the fabric of the tools, the capabilities. Talk about that a little bit, Michelle.

Yeah, and uh, when I talk about identity management, I'd be remiss if I didn't talk about entre and the many things that we have built in, um, to that. So when we think about defined identity, it's why starting with power platform is that shortcut In many cases we've defined through entra what the IDs are. We have also defined group identities.

We define roles for what those different groups can access, what they cannot access and at what times. And so it becomes very easy and it gives an extra level of trust. I'm really excited about the continuing investments that Microsoft is making here.

That core strength of what we've had in power platform is joined by things like purview at Agent 365. That is that control plane for agents. This is a great time to be in technology but be in business where we're able to le leverage ai.

Thanks for sharing your insights. You know, some of the learnings that you've had working with customers, even your own 'cause you're building agents, so we appreciate you sharing that with us. Thanks so much, Mitch.

Appreciate it. One of the things that's most interesting to me about AI is not only what we can do with it, but how it's changed about how we think we can solve problems and who can solve those problems. We've had citizen developers and tools for creating applications in business units and outside of it and situations where they still need to come to it to kinda get the harder parts done.

And it seems like we're passing that we're moving past some of those barriers into a world where some of the constraints around what we can do with technology are being lifted or, or lessened of a burden on the end users. And that's when things change. That's when systems fundamentally change, uh, because you remove constraints and now what's possible is actually even increased the space of what you can do.

It's really interesting to see how Microsoft has approached this of having an embedded basis of customers that are using the, you know, the current generation if you will, of technologies, but helping them move into the syngen future. And it's not a jump off the deep end, it's a process to move through that, but also helping customers understand what you can do and who can do that and how to leverage those tools while at the same time, security, guardrails, governance, the things that you need from a corporate or an enterprise standpoint. Uh, not our our checkpoints at the end, but also built in to the processes and tools that you have so you can start to leverage that as well.

It's really exciting to think about the future of agents and what they can do. As we moved into the, the second and third phases that Michelle talked about around agents, agents doing work for us and then working along, uh, agents. I can't think of it as not just humans in the loop, but humans leading the loop of agents that are doing those that work for us.

So it's an exciting future and I think we'll have a lot of opportunities to share our experiences along the way on this journey.