so for now I would like to introduce our next keynote speaker the CIO of servicenow for eight years running his role spans digital strategy customer experience analytics and AI cyber product vision service operations and customer advocacy please welcome to the stage Mr Chris Beatty [Applause] better late than never as they say um so again it's a privilege and honor to be here at defitic 2023 and uh thanks for having me so my title Chief digital oh I forgot my clicker now um I'm all like um at a kilter so let me try this okay my title Chief digital information officer so my title used to be CIO why did I add the digital I think it's a lot of things the under secretary was talking about a lot of things Mrs Goodwin was talking about which is as technologists we are driving so much change we have to embrace AI we have to embrace automation we have to make it easier for people that for things to get done when we have to own the transformation agenda at our Collective organizations I know I work for private sector you all in the Air Force and daf but it's the challenges are very very similar and servicenow if you don't know servicenow we are a platform company based out of the West Coast and simply put and there's a very very long marketing explanation I'll save you that this platform was built to automate any kind of work and make it easier for the average human to get things done and we do a lot of work in the private sector but one of the things I'm most proud of is the work that we do in the public sector with all the federal agencies I'm really proud to be a part of this and really proud in the way that we're serving not only I.T operations but HR operations as well as Mission operations so thank you again for being here I'm going to talk about the power of intelligent platforms and I think platforms are really the unlock to accelerating digital transformation as we know it today and I'm going to talk about three specific I'll use the Silicon Valley term hacks that can help us accelerate and that's along the lines of experience speed and AI but I'm going to get to those in a second first I want to talk about platforms and why do I think platforms are so important and let me start with platforms that we all use in our daily lives platforms to drive digital transformation across the Enterprise and you can see from this visual digital transformation is hard it's hard because there's so many siled apps it's hard because each mission in each department has their own agenda it's hard because getting everybody aligned to do something in a common way gets very very difficult but platforms help with that and platforms if we put all these capabilities in one spot we can help accelerate things and but it does require thinking and doing things differently than we have traditionally done them so let me start maybe on the personal side platforms we've all probably used um I think the slides are a little bit ahead of me sorry foreign okay either way um so so let me talk about the three vectors the three vectors are experiences speed and AI and I'm going to Deep dive into each one of those and how I think that they can apply to accelerate digital transformation um but on the platform side I was talking about Platforms in our consumer lives and why they matter let me talk about a few platforms that we all know and some of which we have already in our pockets the iPhone think about the iPhone it has messaging capabilities it has GPS capabilities that it's all these apps built in one and the more apps that we put on it the more powerful this platform gets but not all platforms are technology driven I think the U.S highway system is a great example of a platform with interconnected ins and outs and standards that we all use and leverage and let me unpack a technology platform that we've all probably used in our daily lives and that's YouTube so if we think about YouTube If you were to take a non-platform-based approach you would probably have one app to capture video content you would have another app to enable meta tagging and search on that content you'd have another app which was which would be a website on which one would search videos and I could go on and on and on and on but because they've put this all in one platform because they put all these capabilities in one spot they're able to capture our attention and they created a whole economy in and of itself so in our consumer lives we consume platforms all the time and we don't probably don't even think about it because of how intuitive they are to us but what does that mean inside the Enterprise and I thought a bit about what are the critical attributes of a platform that we need inside the Enterprise when I think about four or five key things one is omnichannel experiences how do we develop a how do we have a platform where you can you can have chat Bots and mobile and web all in once really deliver frictionless experiences to the person that lets them consume information in the manner in which they want it has to integrate with different parts of the ecosystem none of us are starting from scratch there's a lot of systems that have been implemented a lot of applications out there and any platform of relevance in the Enterprise has to interoperate with other parts of the ecosystem the third I would say is AI generative AI has caught the imagination of I'll say the public at large but all of you technologists know ai's been around for a long time whether you call it machine learning whether you call it RPA supervised unsupervised learning generative AI is the latest any platform of consequence has to have ai built into it and then I think about scale as you think about your scale I think it was 700 000 Airmen was what the under secretary said platforms have to scale to meet all all of your needs and then automation automation does not come in one form you need integration automation you need workflow automation you need document processing all kinds of Automation and if they're all present across a number of different siled areas it gets really hard to build that one experience so the point is they're all additive and they all build on top of each other there's one element in the lower part of this that I didn't touch on which I think is super important especially given your mission which is security and again any platform of consequence and I think the under secretary as she was talking about Ai and models you know we have to make sure any industry solution that you use has the right guard rails around the data and right data protection so this is the way that I think about a platform of consequence that can accelerate digital transformation but the tech alone isn't enough it's a large part of it but it's not enough so let's dive into those three areas that I talked about around experiences speed and AI experiences so when I first started talking about experiences it felt really soft and fuzzy to me and it was like experiences who cares if the screens look good right let's make sure the capabilities are there let's make sure we automate but as I thought about it more it was experiences really matter because the right experience can actually change human behavior and get to the right behavioral outcome that we're looking for let me give you a quick example from my shop so we're a software company we want our Engineers to file patents and this is a story from a few years ago and when I looked at the engineers one filing patterns when I looked at the process for engineers to file patents it was one of those where it was fill out this form in triplicate then hand it off to a department and then do it all over again maybe four or five times later at the end of which if you make it through all the way through that Gauntlet as an engineer if you have the patience for it then we'll look at your patent application so nobody was doing it obviously so we reimagined that process and made it mobile first made it easy to do all that kind of stuff and when we did that the num the percentage of patent applications in our organization in six months went up by 46 percent and that was my aha moment saying the right experience can absolutely change our behavior and we experience this again all the time in our consumer lives right whether it's Netflix or Amazon or Uber or whatever they made things so easy that we want to do them and reduce the friction out of it and when I think about in the Enterprise I don't think there's anybody here who would say we've made it easy enough with the experience and so I think about this concept of multimodal experiences where a couple attributes of it yes we need web yes we need mobile yes we need chat Bots and all the other forms in which people are going to consume technology but there's a couple Keys one is they have to be continuous where you can start in one experience and continue in the other without having to redo everything and it could be true of moving from portal to mobile and it could be true for moving from an experience centered around one Department to another department the second I would say attribute of this is it has to change the flow of work most the times when people need to get something done they have to search through their inbox maybe go into application one find a piece of information go to application number two put some more information in get a report out of application too then go to application three the whole idea being the right experience reverses the flow of work how can we push information to the human as opposed to the human having to find work and then the last thing I'll say erotic experience is proactive and I'll touch on that a little bit later so if we know we have to create the right experiences and if we know that one of the biggest barriers to technology adoption is the user experience um and and the right experience by the way no one ever needed a training manual right if the experience is so intuitive then what's the barrier I think one of the barriers is actually getting people on the same page because there are very few processes I would say that only span one department so how do you get people aligned on making it easier and one of the hacks that I came up with through not I come up with I learned through a lot of calories burned is around this metric of self-service so when I think about self-service what does it mean so work I need to get something done I'm usually requesting that of another department that department needs to maybe consult the third department and get back to me self-service would imply that when I need to get something done the rest of the stuff just happens without another human involved and it's a it's a pretty simple metric but if you think about this concept of self-service it can apply across staff it can apply for multiple departments it can apply to one Department it can apply to one process so how much are we improving the self-service of that individual process Department Etc departments or whole organization and I would say as people look at self-service and improving it there's a couple things that I've learned which is it's almost impossible to improve that self-service metric without simplifying the process without automating a number of the manual steps and the third which I think is really really important re-looking at policy so share a real example another real example of mine which was um we have travel and expense cards at servicenow and we said well why can't that be self-service someone needs a new travel card maybe they lost it or whatever and go to a chat bot and get that done so we built the chatbot conversation I still remember I was getting a demo of it and there was one of our Junior Engineers pretty nervous given me a demo and we walked through the first couple steps in the process do you need a new card yes what's the reason there was a bunch of Reason codes and then we got a couple steps down and it said and the way that they built the chatbot conversation was what credit limit would you like and they built a pretty cool UI it was five thousand to fifty thousand dollars and I got irritated leadership lesson I should have got irritated at a younger engineer but I did and I said why the heck would you ask the person what credit limit why wouldn't you just don't we know that like don't we have a policy around it and he said um we don't use the word sir in private Enterprise but he said Chris um I just coded what was in the policy so in servicenow's policy document was we asked the person what credit limit they would like so you find out all kinds of I'll be careful of my words interesting things about your own policies when you when you digitize them and and so again those three things if you're improving self-service one it's an easy metric that can apply across departments so you get people on a Common Language but you have to automate you have to simplify you have to re-examine processes and we have seen that most people who Benchmark it typically start in the 16 or so percent but then very very quickly they're moving to 50 plus percent and I think three to four years ago this was probably really really hard it is absolutely attainable now I think the biggest constraint is actually between our own ears meaning the changing our thinking why can't we we have all this information resident in all the applications how do we bring that to life to serve the person better so machines and platforms are executing work on on behalf of the human so self-service is today I would say where we're headed to is actually proactive service and let me take a very easy example of somebody needs a new laptop I'll call it the old way self-service and proactive service the old way somebody's laptop is broken they're under duress they call a number or they fill out a form hey I need a new laptop and hopefully two weeks later they get a new laptop that would be reactive service self-service I think very attainable today is you go to a chat bot I need a new laptop it automatically checks in the background are you eligible for a new laptop how long have you had yours here's a model we support here's the most secure version etc etc and everything the Fulfillment behind is automated and you get your new laptop but I think that's probably was good enough for yesterday but probably not good enough for where we're headed which is why can't the platform say hey the median life of a laptop is 28 months and around the 26 month Mark the chat bot is going to wake up on your laptop or mobile phone and say hey I think you should get a new laptop is now a good time maybe you're on the road and you say no check back in a week but this is where things are going and as you digitize daf which is I know a very very tall order think about all of your efforts think about how you're leveraging technology to be proactive for the human and not just reactive but this was a lot of slides and a lot of theory about experience and self-service and chat Bots and continuous and this and that let's actually look at look at it in action so we are going to do a live demo we debated it live demos sometimes things go really really wrong we'll see what happens we had the mic incident hopefully all the bad jujus out of the way so with that let me welcome on stage Shawnee to drive a real live demo of what this looks like [Music] y'all can hear me right all right awesome thing number one complete um okay so I'm gonna kind of jump right into today you know as Chris said we want to talk about that engagement um that engagement layer and that experience that you initially have um when you know you're experiencing service now um so as you can see here this is really the engagement layer that we've created for our Airmen this portal is configurable to your organization and when we think about our end users we think about that single pane of glass that they're going to be able to have to manage all their work needs on the platform um as you can see I am logged in as myself and that's because servicenow is a role-based system so anything and everything I see right now is going to be because I'm authorized to do so but more importantly servicenow is really thinking about how those different experiences impact certain end users for instance when we think about you know our Millennial Workforce having a conversation with a chat bot can be so powerful for them so today we're going to be talking about our virtual agent our virtual agent is an AI capability on the now platform which allows for automated conversations uh to drive decision making perform common work tasks and really just manage information for that end user so I'm going to click into this and let me just go a little bit bigger for you all to see um our virtual agent now I'm going to set the scene let's say that I am an Airman working in a warehouse on Maxwell Air Force Base and this will be pretty important in August okay and my AC unit is not working so I'm just going to let the virtual agent know it's really hot in my office and even though I didn't really tell the virtual agent you know my AC unit is having issues she is still able to deduce using natural language understanding that I'm having HVAC issues more importantly we can also see that she realizes where I'm located and that's because my profile is storing that information in the platform so she recognizes I'm in the medical Logistics Warehouse so let her know yes that's exactly where I'm located and more importantly she's going to recognize there are four different AC units located in this Warehouse so which AC unit am I talking about so I'll go ahead and let her know I'm in the main office and that is the AC unit having issues she does something interesting here and that's because when we think about tier zero ticket deflection we want to have that capability built in to our virtual agent and that's because we don't want folks submitting tickets unnecessarily they can find that information in the knowledge base or you know within the portal itself then there's no need to submit a ticket however obviously I've done some troubleshooting there are no exterior doors open so I'm going to let the virtual agent know yes all of the exterior doors are closed next up the virtual agent does an API call directly to my thermostat she's going to make a determination on what the temperature actually is in my environment now we can see here she recognizes wow it's 81 degrees that is hot and she's going to look into my preventative maintenance tickets that were also worked and stored on the platform and see that they're all up to date so then from there she's going to use that same rest API call to go ahead and reboot that thermostat for me to see if we can get it working now once again she asked for another troubleshooting mechanism go ahead and you know see if you feel any cool air coming from those vents want to let her know no it's just not happening it's really hot in here and up next she's going to recognize hey we really do have an issue so let's go ahead and get a technician out to you now I'm not going to schedule the first available time slot it is August in Alabama I'm gonna get this scheduled as soon as I can so we're going to go ahead and schedule that first available time slot with the virtual agent and one of the last things I'll say about what she does is she opens that ticket on my behalf but more importantly she scheduled it in the next two hours and she's also making sure that proximity and skill set of my technician that's coming out to meet me is actually going to be able to perform the work that I need so you know as Chris mentioned this is just one of the capabilities that we have with AI today and how we're currently using AI on the servicenow platform back to you Chris that was awesome [Applause] super well done and I think that really highlights the power of experiences how easy it is to engage with that all you're saying is I'm hot and the Machine and the platform instantly understands that and also what I liked and um I don't know if I liked it but brought back a memory the chatbots kind of just said hey did you close the windows it reminds me of my parents at home um it's hot in here well close the windows the AC works better and I think this is just an a small example of how easy and intuitive and how we can remove the friction from the everyday processes we all experience in the Enterprise so there's a couple items and I'll just build this slide out that I've there's research been done on experience and how to make it better and a couple things pop out to me I mean the book is about this stick but one is nail the book ends so if any process and the research has shown if you can make the beginning of that process and the end of that process a lot better people will have a favorable impression of it and the the funny part is the person actually did research on root canals of all things and said if I could make the beginning of a root canal and the end of a root canal better people think it's a great root canal I've never heard the term great root canal but there you go that's what this research scientist did so nailing the book ends of the process really important the second is there's a lot of moments along the process where there is potential friction and it doesn't all get fixed overnight but again the research has shown if you can fix the worst moments the lowest of the low the thing that people actually hate the most they'll remember that versus taking a lot of medium moments and making them great and a lot of times in our roles fixing things and improving things the hardest thing is often where to start what do I do first second and third so again think about those worst moments in the process which are probably the hardest ones to fix too but if you can improve those again that's going to create a very different impression on the humans interacting with that and the third is around again the research has shown setting expectations so even if you have a process where somebody thinks it should take three days but your process is I don't know eight days if you can tell them up front hey this is going to take you eight days and you can show them a trail along the way about how far they are into the process again the research has shown people are far more accepting of it and I think the one company that comes to mind that did this really really well is Uber right even if your Uber is 20 25 minutes away the fact that you can see that little car and the second by second progress of where it is you're just a little bit more patient okay it's on its way I can see that it just took a right turn it was probably stuck at a light so again applying a lot of these Concepts into the Enterprise to make lives easier for in my case all my employees in your case the Airmen um I just thought that would be useful these are very useful for me as we have we started to practice these okay so that's experience I'm going to Pivot now to speed speed I believe is a competitive Advantage no matter what process it's in getting something done faster is always better and I live in a private sector sort of boring corporate world you all have Mission operations where speed really really matters and I think the vehicle to drive speed is automation you automate a lot of waste you automate a lot of manual steps the speed increases and I often think about it as how can I increase the clock speed of servicenow and again the vehicle there being Automation and the first question comes to mind is what should we automate and like like most organizations the process typically looks like a monthly operations review a quarterly operations view some sort of after action review where people are looking at data and saying that's not quite what we needed to be how do we fix it then there's a study that happens for three to four months where people go analyze the process they come up with a set of findings those findings have to get dispositioned and remediated task team to go do it I'm running out of breath even talking about it and maybe nine months down the line something improves but I think we have the opportunity collectively to change the game on that and that is through something called process mining and process mining if you think about it we all have that pretty Visio chart or maybe we do maybe we don't how the process should work what process mining does is it analyzes your systems and reverse Engineers well here's how the process is actually working and these 30 percent of transactions took you know five times as long as the other you know 70 percent and I think it has a few and this is again my own data about how I ran it and those insights on the right of this chart I don't think if I asked my HR department they ever would have told me those insights not because they don't want to but it probably would have followed the standard Playbook of let me analyze it let me map it let me do this that and the other but I think there's a couple implications of this one it becomes Unthinkable to ask a human where are the inefficiencies in this process where are the bottlenecks the platform's going to figure it out faster than any human the second is and I'm going to date myself here I grew up with the old adage of never automate a bad process I actually think that goes away because now I believe automate the heck out of any bad process that you have because the machine will help us figure out how to optimize it faster again than any human and then the third I would say is there's new rules we are used to trying to figure out what we need to go improve and deliver in code and do all these things I think that's changed where there's new roles in the organizations where people need to say okay what is the platform telling me I should do it's a little bit discomforting for me too which is platforms telling humans what to do as opposed to the other way around but the insights are there and so I think the future is every process in any organization is underpinned by process mining the future is that we are in an always-on innovation re-engineering cycle re-engineering is not something you do every six to nine months it happens every day every minute every hour um and and it would be again I find it hard to believe we wouldn't have this running for literally everything over time now that time may vary by organization but I absolutely believe this is an unlock to accelerating digital transformation and automation and if you think about the average Enterprise today lots of different siled systems lots of different siled experiences someone says they need something someone has to log that request in the system maybe log into another system to because they use a different app somebody in the end of the day approves it it goes over to let's say in this case the it system then then acquisition has to get it done I'm not picking on acquisition it was just the example we picked and then from a governance standpoint someone has to log in that's a lot of steps that's a lot of breaks and silos in the information that's a lot of friction a lot of calories burned to get something done which could be as easy as what Shawnee just showed why can't a chatbot do all of it why can't a chatbot navigate all those systems and the funny thing about Legacy systems is I feel like Legacy is a bad word they're there for a reason they do valuable work and everybody likes to sort of bash on the Legacy systems I feel like until somebody says let's take it away and it's like no no no no no this thing does so many useful things so they're there for a reason but the whole idea is we have to get to a new paradigm and that new paradigm is an integrated experience across all of these Legacy systems that Paradigm is digital workflows which serve as an experience and automation layer on top and automation automation comes in a variety of forms there as I mentioned before there's RPA automation process mining I talked about integration automation workflow Automation and you don't have the luxury of picking the Legacy you're managing the Legacy so if a legacy platform requires RPA you need that but the power of having all these automation capabilities in one platform means you don't have to swivel chair between applications to get something done and you can actually combine these depending on the use case depending on the workload depending on the outcome that you're trying to drive and I think that's a pretty powerful out um Paradigm now automating typically required scripting and coding and pro code and then the industry came out with low Code and low code has its place it made things easier for people to get stuff done but for the really complex and hairy stuff it still requires code but I do think even that's about to change so generative AI you've probably well maybe you've all played with chat GPT maybe you haven't but applying that to a coding concept can we actually use that right where we can tell platforms to code themselves and rather than me talking about it more let's invite our star of the show Shawnee to show us how it operates in real life foreign all right I'm back so as we talked about before right we showed you all what we're currently doing with AI capabilities presently on our platform but what's coming what are we about to roll out with now um AI capabilities are changing all the time so you know servicenow is a low code no code platform but there are opportunities to utilize Pro code and as Chris said we're making that even easier for our citizen developers to do that today as you all can see I am in a dashboard View and this is allowing us to see some real-time reporting information we can also see I have the ability right from here to create a new business rule now business rules are simple instructions created to allow business logic to be put into play and enforced on our platform keep in mind you know business rules while they are excellent and they are something on servicenow that we use really any system that you're using you're using business rules to enforce that logic so let's go ahead and create a business rule right from here so when I drill into this business rule we see I have the ability to name it I can tie a certain table in the back end to it I can also make a determination on when do I run this Rule and what are the conditions around that role that I'm adding and then we can also recognize hey what action do I want this business rule to take and while there are many many actions that surface now allows you to perform the more actions that you add to a business rule the higher likelihood it is that you're going to need to code now codeine for me is not something that sounds very exciting um I'm not a professional coder I'm a citizen developer like you but as Chris mentioned how are we making it easier for our citizen developers to do just that you know have script available to them at their fingertips so when I type something simple here like search all incidents created last month and I go ahead and press Ctrl enter using generative AI it's going to go out into the servicenow platform and find all of those different incidents for me but not only that it's also going to go ahead and create that code for me or that script so I no longer have to do it so we can see here it's already gone ahead and taken that Glide record or that incident table and pulled it in for me I also created conditions right I created a condition around this I said I need the incidents from last month and we can also see that right here in our script as well so by using generative AI on the servicenow platform we're able to create code from literally the human language take that chat GPT thanks back to you Chris [Applause] and by the way this is not future this is here and now my team uses this all the time but I think about again accelerating the pace of change how quick was that and it works for for even like really complex things as well so if you can if a developer can if an analyst can simply express what they want the machine to do the machine will now code it so think about that for a second think about project timelines think about how much time is spent writing requirements docs and things like that maybe there's a shortcut let me just tell the machine and let me look at the output again the cycles of innovation dramatically shortening and the the ability to try stuff out and experiment and see what it would look like without the elongated cycles of development I think is huge for our industry lastly I'm going to talk very quickly about AI it's obviously caught the attention of the industry with generative AI machine learning Etc you can just make sure I click that and why does AI matter I'm going to unpack that for a second I think three things if you think about a process which is automated with AI I use the term infinite scalability why is that because if you can do it once and it's automated once the cost of adding a million more of those types of transactions is minimal marginal cost near zero so if you think about that for a second that allows scale without cost right so the automating with AI gives you the opportunity to scale things almost infinitely the second thing is in any organization could be an organization as big as daf could be a smaller one like ours as the organization size increases the number of departments increase the number of people increases processes increase checkpoints increase all that kind of stuff but most organizations that would mean things slow down and we've seen that prove out in private and public sector but with AI these platforms actually get smarter with scale they can do things faster and faster um which which is which again is a game changer so with scale speed increases it reminds me of a fintech organization they're actually in business where their their requirement was two minutes to fill out a loan application but the loan approval is one second literally one second because of all the AI training data they have on all of us that's a different topic around data privacy but but I'm not going to get into that um and then the third part I'd say about AI is interconnected systems as these AI systems can connect to different other parts of AI systems The Innovation Loop the learning Loop just starts to increase so I think AI is very very powerful I would say we're very much in the early Innings of this and I'll contrast it I know where I live we're good about coming up with very buzzwordy technology but I'll contrast it a little bit with things like the metaverse and blockchain where I felt like those were Technologies in search of a use case generative Ai and AI feels like the exact opposite because the use cases are actually jumping off the page and let me show you what I mean I'm going to take the two things I talked about one is around experience and one is around speed what is an AI driven experience mean let me talk about natural language understanding again think about a form that's being developed in any corner of your organization maybe there's 12 fields on it maybe 13 because we have to capture this field for routing this field for categorization whatever why can't it be one field a natural language understanding takes care of the rest the technology is there think about most of the reports we have are about let me find out if anything bad happened in an Ops review why can't platforms tell you in advance that hey something bad might happen my machine learning algorithm thinks that these things probably aren't going to finish on time and you really want them to finish on time generative AI search to help us make use of the vast amount of information that we have in our Enterprises that are like trapped in different content stores and knowledge bases and people you know get frustrated trying to find their information what if you could just ask a question in very natural language and get a very human-like answer um RPA different automation Technologies so AI driven experiences I think we have to lean into it we have the opportunity to really help people interact with technology in a very very different way and then speed speed and automation how do we get AI driven speed inside the Enterprise so I talked about process mining as a game changer but I also think about things like automation Discovery where platforms are finding out what it can go automate and there's a simple hack that I came up with which is because often teams struggle with will work where should I apply machine learning supervisor unsupervised if any process has a rating ranking or recommendation it's a candidate for machine learning anything which has a rating ranking or recommendation it could be your prioritizing something it could be you're putting a risk rating on something it could be you're routing something all of those are very very simple machine learning algorithms I shouldn't say simple they're simplified if they're all in one platform in the same platform has Ai and automation has experiences all in one so on AI I think we're in early Innings it's up to us to embrace it the platforms have have the capabilities now for us to leverage them I think it's on us to figure out how we apply these when we apply these and get rid of a lot of the old constraints and I really do think There's an opportunity with AI to LeapFrog I I showed that progression from reactive to self-service to proactive skip that whole step in the middle of self-service you can go from reactive all the way to proactive leveraging AI so my my takeaways from this um one I think platforms are a force multiplier especially platforms which have experience baked in which have automation baked in which have integration baked in which has security and scale built in it means you can leverage all those capabilities no matter what the use case and you don't have to innovate on all of those things at once the second speed creates Advantage I'm probably preaching to the choir but the vehicle to creating more speed is Automation and we have to automate more and more and more and the platforms can actually tell us where and how to automate and then the last one I'm going to say is we have to think AI first it's very tempting to say well I'm going to do it the regular way then I'll think about that AI thing after I would encourage you all to think about it in the opposite order how do I leverage AI first because maybe you don't need to do any of the traditional steps that you've done before so that's a bit of my point of view hopefully notwithstanding the mic at the beginning you enjoyed that including the live demos thank you for your time and I think I'm going to take some questions now appreciate it [Applause] Mr Beatty in this new age of generative AI please expand on do you have any predictions on what could change um any predictions on what will change with generative AI I think in the very short term the biggest one I see is the calories that we all burn on coding new applications and digitizing new things the ability for code to get automatically generated means that we can accelerate digital transformation I also think that in the short term we will start to see generative AI I'll just say unlock all the value trapped in this various content repositories that we all have could be knowledge based articles could be just a Content store on SharePoint or something like that but generative AI allows us humans to now ask it natural questions and for it to evolve and if I had to say a third area is I think the user experience uis user interfaces as we know it are going to dramatically change where generative AI are just going to be inserted at various points and I'll give you a quick example and I'll pick maybe a very routine example of an I.T issue it's an i an I.T issue starts with me it moves to my friend Steve Walters then it moves to Tim Tim gets it he might have to review five pages of notes to get up to speed with what's gone on with this incident instead what if Tim could just say hey Jen AI could you summarize what's happened in this ticket for the last two weeks and it summarizes it for him and then you can get on with actually helping the person out so those three things I would say coding content and the uis As We Know It are going to change but I would say anybody who knows exactly what's going to change with Gen AI probably has a little bit too big of an opinion themselves that's being honest sorry um but that's my view for the next six months six to 12 months thank you sir this will be our last question so if the platform already knows it's 81 F in the warehouse why not skip using the Airmen as the problem sensor so that's a great question and it's almost like you were having the conversation with me and Shawnee as we were getting ready for this presentation so I think that's a perfect example of going from self-service to proactive service and I think it's a journey that the private sector and public sector is on the tech is there because you could very easily in that demo say hey it already knew it was 81 it kind of remotely rebooted it so if it knew that why didn't it try to remotely reboot it automatically so I think it's a great call out um and it's just part of the journey that we're all on which does require different thinking the tech is there in the platforms but I appreciate the call out foreign [Applause] how about that I'll take your mic thank you thank you Miss Beatty on behalf of our Airmen and Guardians here let's give you a token of our appreciation from the office of the cios thank you industry within ethics don't worry okay thank you for the insights as the chosen platform for our wave one um provider we look forward to the insights and you've definitely piqued our interest on how we can maximize the use of our platform so thank you another round of applause please it's an honor to be here