um is let's say you wanted to build a field service agent that you want to interface into co-pilot uh all you got to do is give it a system prompt tell it that hey I want you to be a field service agent point it to a SharePoint site where there's a bunch of documents related to field service uh add to it even additional data sources in this case their Dynamics uh as the system of record for field service and you have an output which is essentially a field service agent which now you can talk to
uh and have a conversation with just like you would with any other regular co-pilot conversation right so that Simplicity it's kind of like back in the day we just created an Excel spreadsheet right it's no more mystical than that uh just like how you could create an Excel spreadsheet that was a forecast you can now create AI agents using a low code no code tool like co-pilot Studio put it into co-pilot uh you can even think of these as the new form of applications uh and that any one of us can create as see for
uh to make sense of it and then lastly you can feed it more context more memory uh so you put all these three things together you're building out a very rich AI or agentic world uh in which you are going to have these AIS or agents right there will be some AIS and agents that are personal agents uh there will be things that will work in the context of a team in the context of an organization or business process or even Cross organization so this Rich tapestry uh of AI agents that augment uh everything else
that we built right so that's the other part the entire digital infrastructure and tools that we today have get augmented in this agentic world uh with all these AI agents that we build using the scaling laws as the underlying Force coot is the UI for AI That's the simplest way I think about it uh we then have uh the co-pilot and AI stack so to be able to for you to build your own AIS and AI agents uh and co-pilots we have a full uh stack and then lastly this new set of devices which are
these co-pilot devices um and so I want to talk about each of these platforms starting with co-pilot now as I said if you start with this idea that this Rich agentic World ultimately does need to meet us and we need to meet it that means you need a UI interface right just like the PC or the phone was the user interface or the apps on a phone or a PC with the interface uh to essentially digital technology uh these co-pilots or and co-pilot is the UI for all of this AI right even in a world
where there are a lot of agents that are working autonomously uh they do need to raise exceptions get permissions uh from us and the question is how does that happen it happens through this new organizing layer for how in particular work gets done uh in fact work work artifact and work flow is going to change uh a great example of this is just a couple a month ago we launched something called Pages just like say back in the day in the '90s we launched Excel or you know word uh which to Art you know basically
editors to create new artifacts pages is the first I would say user experience to create new AI first artifacts right I can search the web or my work for retrieving information um and then I can put it into pages and it's a document for it's a document that I can then share across the organization and I can work with AI and humans in fact I sort of say the metaphor I use is I think with AI and work with my colleagues at work right that's the new workflow what was the previous workflow I thought on
my own I created artifacts and I shared it across the organization and collaborated but now I not only I have a cognitive amplifier effectively with AI uh where I do my work and then I create artifacts and I collaborate with my colleagues in order to get things done and so that's really the beginning of this co-pilot error uh where it's just not about a chat interface but it shows how chat is just one modality of being able to retrieve information but it does lead to more sophisticated workflows and collaboration now you extend so the other
thing is that this is not just about any particular artifact editor or workflow we created but you can extend co-pilot with any agent you build in fact co-pilot studio is a low code no code way for you to be able to build agents um and and these agents are really grounded in a rich set of data sources starting with in fact the most important database in most organizations is the database that contains all your office information right who works for whom who who are my colleagues on this project what documents are there uh related to
a particular team or a project uh what is the relationships between all of these documents and people and projects all of that and all the emails you've had teams conversations you've had that's all in fact in a first class database called the graph or the substrate that is now exposed through a graph in M365 you uh in fact a great simple uh example of this um is let's say you wanted to build a field service agent that you want to interface into co-pilot uh all you got to do is give it a system prompt tell
it that hey I want you to be a field service agent point it to a SharePoint site where there's a bunch of documents related to field service uh add to it even additional data sources in this case their Dynamics uh as the system of record for field service and you have an output which is essentially a field service agent which now you can talk to uh and have a conversation with just like you would with any other regular co-pilot conversation right so that Simplicity it's kind of like back in the day we just created an
Excel spreadsheet right it's no more mystical than that uh just like how you could create an Excel spreadsheet that was a forecast you can now create AI agents using a low code no code tool like co-pilot Studio put it into co-pilot uh you you can even think of these as the new form of applications uh and that any let's take a look it all starts with an incoming email from a prospective client much like you see on the screen right here now previously they had had people on the back end essentially receiving these emails parsing
through them and figuring out what to do next who should it be routed to what expertise did they have in The Firm but this is where the autonomous agent comes in now an email comes in and the agent Springs into action what you see here is that it will begin to parse out the email moving through the ambiguity of human language to for instance find out what the engagements about to check the engagement history to also map it to their industry standard terms and then finally to try and find the right person to take the
next step within the firm with all of this information in hand the agent then goes about writing an email that takes all of this information and summarizes it for the receiving partner and what you see on the screen is exactly that in comes a whole bunch of human written email the agent processes it summarizes it and sends it to the right partner in The Firm to take that very next step now it's worth pausing for just a moment here to reflect on what you're seeing it happens so fast you you might miss it but essentially
this agent has been given a loose set of instructions kind of like you would to a human and it deals with all of the messiness of human communication figuring out what the right next touch point is for the customer now this is Magic but it's only half of the magic because now we're going to go behind the scenes to see how easy it is to actually create an agent just like this for this we will move over into co-pilot Studio here you see that we have programmed up with McKenzie the agent but not using a
sophisticated programming language instead using natural language the same way that you would tell a colleague to get ready to do this task you also see that what makes this agent autonomous is that we can set what's called a trigger in this case the trigger is set to watch an email address and to react immediately when an email comes in but in fact you can set it to look for events across a whole wide range of systems sitting there working for you 24/7 waiting for an event to come that gets it going you also just like
a regular human colleague add knowledge here we see a Word documents a SharePoint site and a database about engagements but of course you can add additional knowledge sources that includes line of Business Systems like sap or service now or even databases and finally to finish up what you give this agent to do its work you give it a set of actions and we saw those in the flow these are actions that include things like pulling out the relevant information or summarizing what a human has written all of this together makes the agent powerful because it
can deal again with all of that ambiguity that a human throws at it now what we saw was one email coming in about one new client engagement but the exciting thing here is that this scales how does it scale well to see that we'll go over to the activity pane where we can look at the long list of engagements that it's working on zooming in up top for instance we can see that it's worked on over 1400 engagements and there are 33 in progress if we want more details we can go into the analytics tab
what this means is that this agent is always working on behalf of the firm and that's very exciting for us now from here we also see that although the agent's amazing it does sometimes need some human help so we're going to jump into a case the second from the top here where we will see that it gets a little bit stuck as you look it's gone through those steps that we saw previously but it's stuck here at that one where it's looking for the partner and if we zoom in we can see why here for
instance we see that it's picked the right partner but that partner has now left the firm it has an instruction that says if that's true it needs to escalate to a human manager to give it someone else to go to now to see what that looks like we're going to switch over to co-pilot and see that interface with that human manager here at the bottom right you will see that a notification pops up in co-pilot then the manager gets all the information he or she needs and can provide the right person to Route the email
to back at the ranch going back to our agent we can see that it takes that information and fills out what it needs to do now we're excited about this because of the business value it can drive McKenzie and its trials has shown that it can reduce lead time by 90% reducing o administrative overhead by 30% and as you look look at this list what we envision is an orchestration layer just a bunch of agents that can be out there helping individuals teams and entire functions to streamline and automate their processes no matter what industry
they're in they're so easy to make anyone can do it you design and set these co-pilots out to work in co-pilot Studio you interact for
