00:00:06 - 00:02:18
Layla
Hello, everyone. Welcome to our Confessions Series webinar, Fueling Business Productivity with Next-Gen Automation session today. My name is Layla, and I'll be your host today. I see that we have some folks still coming in and joining the webinar, but we'll go ahead and kick it off with just a brief introduction. That way, we'll make sure that we have enough time for our speakers to share all of their insights today.
Then just some housekeeping items. This webinar is being recorded and we will share the recording after the webinar concludes. Keep an eye out on your emails for that recording. Then also, we will have a Q&A, and we will be using this platform called Pigeonhole. If you haven't used it before, feel free to grab your phone right now, and you can scan that QR code and follow the link, or I'll also go ahead and drop this link into the chat box in a moment for you to follow that way.
Once you scan the QR code or click on that link, you'll be redirected to the page where you can go ahead and drop in any and all of your questions that you have for our speakers. You'll also see that there are already a few questions in there, so you can feel free to upvote those questions, and we will make sure that we'll go through the questions based off of priority on which ones have the most upvotes. Definitely, make sure you go in there and drop your questions at any point throughout this session, and we'll make sure that we get to those at the end.
Without further ado, I am very excited to announce our speakers for today. We have Matthew, who is the CTO over at CAI, and we have Carter, who is our CIO here at Workato. With that, Matthew, Carter, very excited to hand it off to the both of you.
00:02:19 - 00:02:50
Carter Busse
Thank you, Layla. I got to tell you that, oh, you open up with that song. It's one of my favorite songs. I literally think about driving across the country with my parents sitting in the back seat when I think of that song. You had me daydreaming a bit before the session started, but hey, everybody, thank you for joining us. Confessions Series here. I love doing these. I think this is my 10th or 12th one. Super excited about this one with Matt Peters at CAI.
Matt, can we go in and make an introduction of yourself, what your company does, what your role is, and how big your team is, please?
00:02:51 - 00:04:09
Matthew Peters
Yes, absolutely. Thanks, I'm excited to be here, too. If I just try to summarize what CAI is and does, essentially, we're a global professional services organization. We have about 8,500 employees, and in the context of that, we do a lot of things that one might expect a lot of enterprise service management, application modernization, automation, RPA, and all the waterfront of technologies that go around that cybersecurity. As far as what CAI delivers to its customers, that's a big piece of it.
Then the things about us that are a little bit more unusual are mostly tied to the fact that within that size of an organization, we're still privately held. We can be responsive very quickly. We don't have to wade through a whole lot of bureaucracy to get things done. We tend to be able to be in the fortunate position to do a lot of experimentation with new technologies in that context. That's really what we do as an organization, what we deliver to our customers.
In the context of CAI, I'm our chief technology officer. At CAI, that's a little bit unusual by the traditional definition of a CTO. I like to tell people that my job mostly just means I'm responsible for everything that plugs into the wall. Whatever that is, that's what we get to do.
00:04:10 - 00:04:12
Carter
You explain to your parents and your kids, right?
00:04:13 - 00:05:36
Matthew
Yes, pretty much. Actually, it's all that my kids know about what I do. They don't bother to try to understand anything beyond that. The way that we're organized, my responsibilities are ultimately for the technical practices that we use to deliver a lot of the services to our customers. The consultants who specialize in enterprise service management, cybersecurity automation, those folks all report to me. That's part of what CAI provides to its customers.
Then I have the inside of the house side of it, which is all of our cybersecurity, all of our infrastructure, all of our applications, and that ecosystem. We consolidated all of that into one technology organization for the company, and we structure it so that the way that we're built, I effectively procure those services that the consulting arm provides for use inside CAI. That's the way that we're laid out. You can think of it as eating your own dog food or drinking your own champagne. We do it very, very heavily.
That's largely the scope of responsibilities that I get to have. Within that, it leaves me in the position of within CAI in terms of our executive leadership team, I have responsibility for all technology. That's where the buck stops, and if someone's in trouble, it has to be me.
00:05:37 - 00:05:40
Carter
Yes. You have both an internal and external facing role then, right?
00:05:41 - 00:05:42
Matthew
Yes, very much [crosstalk]
00:05:42 - 00:06:13
Carter
I think that a lot of these roles in IT and technology is really it. I think we're being asked to do both these days. I have a very similar role as well. This is the Confessions Series, Matt, and the audience is usually who tends, says people who are younger in IT career. I always like to ask the leaders I talked to is like, what was your path to CTO at CAI? How did you get there, and what drove you to this role today?
00:06:14 - 00:06:20
Matthew
There are a lot of components to trying to answer that question. I like talking about CAI.
00:06:21 - 00:06:21
Carter
That's great.
00:06:21 - 00:06:22
Matthew
I'll try to be brief, but I'll let you coach me.
00:06:23 - 00:06:26
Carter
We have later questions, too, about CAI.
00:06:27 - 00:09:50
Matthew
I think the biggest thing for me is, if I look back a while ago, I thought I wanted to be a college professor. That was really what I wanted to do. I liked research, I liked data, and I liked technology. That was really the trajectory that I thought I was on, but for anybody that's been in academia and higher education long enough, it's not for everybody, and it wasn't for me.
The things that I liked about it, if I had a student who was having that deer in the headlights moment where they were trying to make an awful lot of critical life-affecting decisions all at once with very little information, I loved the satisfaction I got out of being able to work with them, find what they're good at, help guide them, and direct them a little bit. That was what I liked the most about academia.
I came to realize because while I was a graduate student, I was also doing consulting for different professional organizations. You can do that as a technology leader, too. I didn't need to stay in academia in order to get my favorite thing out of it. If you leave academia, everything tends to be able to happen faster. I like that, too.
If I think about myself and just what I get out of all the personality tests that I love to take, I love somebody else telling me more about me than I know about me. I take them a lot. I retake them a lot. The thing that most of them have in common is that I am identified as someone who really likes change. I'm impatient, and I like change. Then inherent in that, I think is the implication that I like to learn new things, which I think is true. Then the other thing that comes up in them a lot is I like helping people.
What I found was that as I was moving through the early days in my technology career, those were the things about myself that I needed to emphasize. I was an okay coder and all that, but so were a lot of people. That wasn't really what helped me to nudge forward in the organization. I like to think about technology, and I like to encourage everybody on my team to think about technology as something that we don't really do for ourselves.
If you think about technology, it's everywhere. It's pervasive. It's in every organization. You can't get away from it. We're a capability of competency that doesn't really do tech for the sake of tech. Everything we do is to make someone else more efficient, better, faster. Pick your descriptor. That really just means that you can think about all the work that we do, whatever it is, in the context of helping someone else. That was just as I wandered around to pick up new projects, do new things, that was how I thought about it.
It's, I think, just a different way to position empathy for the people that you work with. That I think is what helped me to, I'd like to think of it as made me promotable, and because of that, because I was fortunate to be at an organization that was growing and had a lot of opportunities in that arena, I kept getting repositioned across the organization to new roles where if I could transform a small part of the organization in my current role, well, now I'm going to be transitioned into a new role where I can do that to affect more of the org until I eventually ended up where I am, where it's the whole org now.
I get to play with every part of this company and technology-
00:09:51 - 00:09:56
Carter
Using technology. You're helping people internally. You're helping all your customers, too.
00:09:57 - 00:10:28
Matthew
Yes. It's great, too. I particularly like that component of it, because it's not simply that I know I have an idea for what my finance team needs or my HR team needs. I'm out working with all of our customers, too. Some of them have great ideas as well. Sometimes I'm bringing something back and saying, "I just found the way this other organization does this. Let's try it," or I get to go into another company, one of our customers, and say, "Hey, we struggled with this 3 years ago. Here's how we solved it. Let's try that. It's a lot of fun."
00:10:29 - 00:11:56
Carter
Yes, you have this passion of helping people. That's why you might be professor. I have a similar quick story, too. I wanted to be a doctor. I wanted to help people, and I couldn't make the cut in college and make the grades and end up liking technology. I found my way into IT because of the same reason I feel like I could help people in this role. So much story there. Let's talk about priorities. Let's dig into this now for 2023 and let's talk about priorities.
Quickly on mine, it's all about being efficient and optimizing what I have. The budgets are much smaller this year as opposed to 2021 where budgets were big and couldn't hire fast enough. Budgets are tough, and we're actually really embracing this whole enablement of the business with technology and actually leveraging them to do some IT projects internally. We practice this. We preach this a lot externally with our customers, but we're really, really embracing it this year and putting the guardrails and governance into an art product internally to enable the business.
For example, today, I got a request from our CFO to do some automation. If there's a person renewing on Workato, but there might be later on that invoice, can we automate some alerting and like, "Hey, Tom, you know what? Your team can do this. You can build that automation. Go ahead. We have the environment for you." We're starting to push back a bit, enabling the business. That's part of our optimization internally. What are your priorities, Matt, this year?
00:11:57 - 00:15:40
Matthew
Similarly, I think, optimization is a good way to characterize it. We've been talking about it internally as putting greater emphasis on the employee experience, which means a lot of enablement for them to self-service, for them to do a lot of their own guidance. We're in a slightly unique position as an organization, where if you think about traditional company, you get to set a lot of organizational standards because your company builds or does one focused thing, and that's the beat that everyone is marching to.
For us, we tend to be so tightly incorporated into our clients and their experience that for my organization, we need to be able to support all of our client standards, our own standards. We have to be able to integrate the two. That can be very challenging because it's not like serving one master. It's serving hundreds.
There are some inherent challenges on that, which is part of why we always want to push a lot more of that self-actualization, self-enablement out to the individual employees as best we can so that they can do their job in the somewhat bespoke way that they need to. We don't get the benefit of universal standards, but we also, at the same time a lot of that work that we do is with government agencies, which puts us in the blast radius of a lot of cyber attacks.
At the same time, I look at the priorities and the need to be able to introduce a lot of flexibility and self-service to individuals, that comes at a serious cost because it always brings risk with it. We're balancing those 2 things right now. The guidelines and the guiding principles that my team operates on are flexibility and security, where you are always balancing those 2 things every time you engage anybody in the business, any customer. That's our defining rod.
Within that part of that flexibility piece, we're really trying to put more emphasis on being faster and more responsive. I totally agree with your point that budgets aren't what they used to be, and when we're on top of economic factors, we're also looking at inflationary factors. Everything that we buy as an organization is significantly more expensive than it used to be. We're squeezing more out of those stones.
In part, that means we need to give as much flexibility to the business as we can that when you need to re-platform, we can support you and help you do that quickly, and when you need a complimentary or supplemental application to the one that you've already got, we can get that out the door very quickly. That's a big piece of the focus for us right now.
I think you could contextualize that as we're leaning in a lot harder on API ecosystem management as opposed to major applications. Five years ago, CAI started the journey of putting Workday in place, full suite financials, HR, absolutely everything. It is the only app for us, really, that is considered to be non-optional, and everything else, the organization has a lot of flexibility to do what they need to adapt how they need to adapt.
I don't want to see my team burning time on more and more direct integrations between all those applications that we support. I want to see more time going into manage that API ecosystem. Use Workato because we can spin up those integrations so quickly. Let's keep all the emphasis there so that when we rip something out, or we throw in something brand new, that's measured in days or weeks, not weeks or months. That's really a big piece of the emphasis for us this year.
00:15:41 - 00:15:51
Carter
You've embraced, the business is going to buy these applications. I can't stop them, but I can provide this API ecosystem to allow the data to flow across the business, right?
00:15:52 - 00:16:03
Matthew
Yes. As a consultant, I've had to interact with so much shadow IT. I get why it happens, yet it's horrible. I don't want to see that happen to us. This is the way that we are attempting to address it.
00:16:04 - 00:16:29
Carter
Honing from experience. I often get asked RPA, is Wokato RPA? You actually, as a business, work with both RPA and integration automation, like Workato. Can you help us understand your perspective, because you help implement both these tools, and both these tools have their use cases? Where is RPA and integration automation a tool like Workato, and where are we heading with those 2 products?
00:16:30 - 00:18:33
Matthew
I'll admit, I see those 2 things as very complimentary technologies. I think it probably depends a little bit on the organization. If you're a traditional company, you may benefit more greatly from one or the other, depending on where you are on your modernization journey. For us, I think the easiest way to talk about it is the way that we use it.
As I said, we service a lot of customers who are at very different points in their life and with respect to technology. In some cases, we have really modern organizations really heavily invested in SaaS, really heavily invested in the security management around API connections. In those cases, and in much of our own technology stack, that's where Workato has a really meaningful play. We use it all over the organization to help interconnect data between technologies.
It's mutually updating to systems. It's keeping all of our data in sync. It's the mechanism that we use to cleanse and standardize a lot of data on its way into the data factory, rather than trying to do it in there. We like to do it closer to the source. That's how we leverage it, by and large. We have to touch a lot of very old legacy systems in a lot of the service delivery to a lot of our customers.
In many of those cases, that actually means we have Workato doing a piece of the workload and then invoking an automation and UiPath, which happens to be the RPA tool that we deployed for our own purposes. It lets us expand the scope of what we can automate and lets us take on more complicated workflows all through automation technologies, where I might be able to pick up a workflow and say, "All right, we're starting to synchronize data between Salesforce, ServiceNow, and Workday all on our side."
Out of that is going to come a big invoicing workflow, part of which Workato is also going to address for us, but it's going to kick back a thousand transactions that can't handle because it needs to touch legacy systems. That automaticaly--
00:18:34 - 00:18:38
Carter
Where there is no API, you need it enter data through UI.
00:18:39 - 00:18:58
Matthew
Yes. For that, we're just directly throwing that output as the input for automation in UIPath to reach out and use the surface-level UI automation technologies to manually just blast through those invoice submissions. That's one of many examples that follow that format for us, where we're using the 2 to invoke one another.
00:18:59 - 00:19:25
Carter
Using two. Using something like Workato for the modern cloud architecture, but there's a legacy system doesn't have an API maybe sitting on legacy Windows or mainframe even. That's where that RPA comes in. That's interesting, you actually use Workato to kick off an RPA. I usually hear it the other way around, an RPA kicks off integration automation or Workato automation instead. I didn't think about that use case.
00:19:26 - 00:19:34
Matthew
We have use cases that follow both directions. I'd say, the bigger ones that we get the higher value out of, the major transactional ones, Workato is usually the initiation point for us.
00:19:35 - 00:20:01
Carter
Oh, wow. I always tell you, I learn something new every time I do this. CIA, you're very passionate about certain topic. This is a topic, the word I've never heard of until I met you, Matt. The term is neurodiversity. CIA is very passionate about neurodiversity, especially what you do as a company. Can you talk about that a bit and how that's given you, and the culture within CAI, please?
00:20:02 - 00:20:07
Matthew
I would love to. I'd start with just a little bit of definitional work around what that term means because it's not just [crosstalk]
00:20:08 - 00:20:11
Carter
I wouldn't do it justice.
00:20:12 - 00:24:05
Matthew
It's new to a lot of people. If I just take neurodiversity all by itself, it basically casts a very wide net around individuals who have any kind of neurological scenario that makes some elements of the work that they do or their navigation through life a little bit more challenging or a little bit different. The way that we historically thought about neurodiversity was a little bit more focused, and it was really on people who were neuroatypical or had autism spectrum disorder.
That's really, if you go back a few years, that was the population that we talked about the most. At CAI, what we're trying to do is say that's all still fair and accurate, but individuals with attention deficit hyperactivity disorder, other neurological diagnoses are also in play when we talk about neurodiversity within the workplace.
What CAI is focused on in that context is creating technical career opportunities that have a life-sustaining income for those individuals and really working with organizations, with ourself, with our clients to help them understand what accommodations or adjustments need to be made in order to be able to enable an audience like that. Also, how to choose particular workloads, work elements that they're ideally suited for, where they can excel compared to what we would identify as a neurotypical counterpart in many jobs and many workloads.
If you're an on-spectrum individual, for example, you might be better at a number of data analysis responsibilities, quality assurance, and testing responsibilities than a neurotypical counterpart, just because you think in the context of very prescriptive, must follow the rules a format of how you approach everything. If you're managing your way through a test case, managing your way through a data analysis responsibility, those things tend to be ideal workloads for those individuals.
Then within that, for me in particular, that also means that it's an ideal situation for automation, widely speaking. When we think about, at a reasonably granular level of detail, what are we doing when we automate something, we are prescribing how a workflow is to behave and how the applications in it have to act. Building out the code around that prescription is very directed, very purposive, very step-wise work in most cases. It's ideal for one of those individuals. They excel at it. They are faster than a lot of their peers, and the quality of their output is extremely high.
Likewise, if I think about it in the machine learning space, everybody's deploying more and more ML tech, AI tech, a lot of that brings MLOps responsibilities into the organization that we're starting to talk more about. Again, that's just something that I see as continuing to curate that data set, continuing to train against that data set. That's perfect work for one of these individuals. If they have the right disposition, and an organization understands how do you work with them correctly, it's so mutually advantageous.
I see that in the folks that we hire and the folks on my team. I see it in my own daughter who is also on spectrum and who is brilliant, gifted, can do an incredible number of things but needs a little bit of extra help or a little bit different structure at certain points along the way in order to thrive. That's the kind of thinking that we're trying to bring into a professional workplace as well. The more educated everyone is on the topic, the easier it is for everyone to work together, and the more we are ultimately getting done.
00:24:06 - 00:25:00
Carter
As we've talked maybe 3 or 4 times, you bring up the topic, and I've really thought about, I learned something new there. We have this book coming out called The New Automation Mindset. It's all about a growth mindset and really thinking about data first in this automation journey, not really the manual steps you need to get to the process, especially what data needs to go through to get reach the end goal. It feels like we could actually capture maybe a bit of the story into that automation mindset.
You mentioned, too, that AI and ML we're experimenting with it too internally and trying to automate our employee experience with AI and our chatbots within Slack and the kickoff automation. You're right, we need someone to train that engine constantly with different questions that are asked. We can make that model smarter and smarter. I get it. It'd be a great type of resource to help train that model.
00:25:01 - 00:26:32
Matthew
I'm really hopeful that it's going to open up as a big career opportunity for a lot of these individuals because there are so many more neurodivergent individuals in the US alone than we would expect. That's a product of we're getting better at identifying them. We're getting better at helping put structure in place that helps parents identify their kids correctly at an early age.
We're seeing more individuals that are able to fall into that category. I think that the impetus is now on us to understand what does that mean for their future for them to be able to support themself going forward. Personally, I feel great about the work that doing in that space. It's great for us, too, because we change everything with respect to narrative or solutions and how we recruit, how we interview, how we onboard. All that's different. Every individual requires a slightly different version of what we're doing for them.
It falls a really bespoke path for everybody. It also means that, in many cases, I get to meet the whole family because a lot of these kids, they're coming right out of college. This is going to be a first job. Mom and Dad are involved in every aspect of their life because they need to be. It's great, but the feeling of just being able to see and hear from not only our new employee but their whole family of what a difference it made is enormous. It's really satisfying.
00:26:33 - 00:26:49
Carter
That's neat. That's what this kind of series is about to bring out some of these personal stories, these confession stories. I got to ask the question. We went there a bit before we go into questions. Give us a good use case for how you're using AI internally. Give us a practical use case.
00:26:50 - 00:26:54
Matthew
Oh, boy. I got to make sure I'm data cleansing in the moment, so I'm not giving my [crosstalk]
00:26:55 - 00:26:59
Carter
I know this is going off [crosstalk]. Give us that one practical use case.
00:27:00 - 00:28:42
Matthew
Actually, we're using it all over the place. Actually, just a few, I don't know, month or 2 ago, our president authorized a dedicated team to AI solutions and to further enabling CAI through AI. A lot of what we're doing right now is we have to do a lot of proposals. We work in the public sector space, so there's a lot of RFP responses that go out. AI as a quality control tool, as a contributor in those things, it's got a powerful role to play there.
We're using it in very, very contained scenarios for code generation and code quality assurance. That one's tough because a lot of the models that we have access to that we want to use, they're open, and whatever you provide to them, I'm just going to take this as another form where I can say it again because I can't say it enough.
When you provide something to ChatGPT, as an example, that is content. When it becomes content, it's theirs, not yours anymore. You got to be really, really careful with what you do and what you share, but within some safety parameters, we're deploying a lot. We're starting to use it in the recruitment space. We've got it all over.
What we're starting to focus on now is really trying to enable a larger population of our employees to be leveraging it themselves. We're running boot camps on understanding AI, how it works, what are the differences between models, generative, and then allowing them to opt-in with specific use cases and get access to a wide variety of models. We're doing it with a lot of guardrails.
00:28:43 - 00:29:22
Carter
I'd say, we're in the middle of our-- we have a yearly hackathon here called Automation April, and it's [unintelligible 00:28:49] ChatGPT was the big one. People were eager to hook. We have a connector to it, but we had to put some do's and don'ts to not send customer information into chatGPT, please. We definitely had to put some guardrails around that. This is wrapping up on the questions here for me and you. Thank you.
Again, thank you for the personal stories, especially on neurodiversity, and sharing some of your personal stories, too. Let's go into the Pigeonhole questions. Layla, if you want to bring those up.
00:29:23 - 00:29:52
Layla
Awesome. Thank you both. We've been getting a lot of great questions coming in from the audience, so let's just go ahead and dive right in. We'll go ahead and start taking them from left to right, highest vote to least. We'll start with this one. Advice for legacy corporations just starting this journey.
00:29:53 - 00:30:02
Carter
Matt, I'm going to let you take that because you do work with government and large companies. Why don't you take this? I think the journey is really around carbon automation journey.
00:30:03 - 00:32:22
Matthew
Yes, I would assume that's the question as well. If it's about automation, I'd say, if your legacy organization just starting to go down this path, one of the earliest things that organizations need to do and often forget about is set some measurable and achievable success criteria for the campaign. You're not going to get funded for anything forever if you're not showing results.
A lot of organizations don't really think about it that way, or in my experience, they think about it in a very one-sided view, which is just, well, this means headcount reduction, so we will measure our success in the headcount that we reduce. For years, that has not been realized as the major value driver behind automation. That's not what it's about. The approach to qualifying automation really needs to be around, in my opinion, a matrix approach that brings a lot of different value drivers to it, how much faster and more accurately can we get this work done?
If you can realize some savings through headcount reduction, that's great, but realistically, you may just find that there's more work that those folks need to be doing that's higher value to your own customers, and that's where they need to be reallocated. A plan for that in order to move forward is a really big part of being able to start this process in a healthy way.
I think when I've gone into organizations that are trying to get started with automation, and they're struggling, I've never run in the door and ultimately just come to the conclusion right away that you've got the wrong tool, and that's what's been wrong all this time. It's always been, there's an expectation management issue that we need to reset, and we need to understand what this is and is not and start setting some priorities and moving forward based on a better understanding of the path that you're ultimately on.
From that, then you really get into the fun of, what are the right tools to do this. There isn't one grand platform that solves all your problems. It's going to be several platforms interconnecting to each other and getting this work done, so starting to move down that path and priority order becomes a follow-on objective after you've really reset some healthy expectations for automation.
00:32:23 - 00:33:06
Carter
I got 2 pieces of advice that I talk to our customers a lot about is, start out automation journey. It's not just IT. It really work with the business and partner with the business and allow them to really help ITs to really know to automate because they know where the pain is, They know where some of these manual processes are. They have all the ideas they do. IT does not. Really partner with the business. Bring them in. Iterate with them.
Start small is my second piece, start small, and just iterate constantly with the business, and then actually, if you can get to it remember where we talked about in the beginning, it really enabled the business to do their own automation. Start small, and partner with the business. That's my advice.
00:33:07 - 00:33:18
Layla
Awesome. We have trends in 2023. What are the biggest areas of improvement?
00:33:19 - 00:33:24
Carter
Well, trends, is it-- I'm just glad we're not talking about Meta anymore. [laughs] Metaverse.
00:33:25 - 00:33:27
Matthew
[unintelligible]
00:33:28 - 00:33:59
Carter
Trends, we talked about it. It's AI, and how do we incorporate that. That's a huge tranche. It's AI with, like we talked about, optimizing our environments. I think it was the biggest AI improvement. We've talked about it. They've been especially around focus on employee experience. I really want to use some of this new technology and these generative AI models and to really improve the employee experience, make our employees a lot more efficient internally. That's per my see.
00:34:00 - 00:35:06
Matthew
I agree. I think 2023 is going to be an incredible year, thanks to AI. I have not seen an explosion in useful utilization like this in a long time. I think what we're going to see from ChatGPT is just pushing the bigger portfolio of generative AI, and we're going to get the adoption and the transformation that we thought blockchain was going to bring us, but we're really going to get it this time. That's how it feels to me.
I'd say, on the flip side, while that's going to open up a lot of doors and a lot of new possibilities for us and all kinds of fun to explore, it's also going to be used against us, and we're going to find that all of us are going to be chasing SecOps in this particular arena all year long. For all the ways that we're discovering that generative AI can contribute to our own businesses, I am unable to believe that bad actors are not able to find 4 times as many ways to use it to hurt us, and we're just not seeing all of it yet.
00:35:07 - 00:35:51
Carter
Yes, that's it. I agree with that. There's definitely a security issue here. There's biggest AI improvement, too, I think this really enables underserved, underprivileged countries, communities to really grasp technology. It's not just for developers, but it really brings technology down to earth a bit with these generative models. Like you said, generating code, we're expanding with Copilot within Workato to actually build an integration-- build a recipe within Workato with a Copilot, right?
00:35:52 - 00:35:55
Matthew
Yes, I'm hoping we're [crosstalk] Copilots everywhere.
00:35:56 - 00:36:04
Carter
I think that the biggest AI improvement, too, is actually a further, quicker adoption of automation and building new products within IT and just [unintelligible 00:36:05].
00:36:05 - 00:36:29
Matthew
I hope that's able to continue to be true from an accessibility standpoint as well. I think that was the other fascinating thing that OpenAI did with ChatGPT was just, we're giving it to everybody, and we're, I guess, just going to ignore the compute costs behind this behemoth that everybody's leveraging. I know they are not covering their costs with the $ 20 a month that they're getting out of me for the premium edition.
00:36:30 - 00:36:33
Carter
Like Microsoft, that's why they did the big, what, $10 billion investment.
00:36:34 - 00:36:38
Matthew
Yes, but they'll burn through that, this year, just an Azure cost.
00:36:39 - 00:36:40
Carter
Yes, no kidding.
00:36:41 - 00:36:43
Matthew
Yes.
00:36:44 - 00:36:49
Layla
Awesome. We have time for one more question. I'll ask you.
00:36:50 - 00:37:12
Carter
I think we did that first one, the biggest priority for next year. I think we talked about that extensively. Again, for me, it's optimization, efficiency, and leveraging this new technology is my biggest priority. Enabling the business, really enabling the business with this technology.
00:37:13 - 00:37:23
Matthew
Likewise, using this technology to be as flexible with the business as we can possibly be. Fast, flexible, and responsive.
00:37:24 - 00:39:37
Layla
Awesome. With that, this is all the time that we have for Q&A, and we are nearing the end of the session. Real fast, before we conclude this webinar, I just wanted to share a couple of upcoming events real fast for attendees here.
I'm going to launch a poll real quick, so go ahead and hit Yes if you'd like to be automatically registered for this webinar or any of these events. If you would not like to be registered, go ahead and hit No, or just feel free to ignore the polls, and we'll be sure not to add you. First up, we have our automation pro-training happening tomorrow at 9:00 AM Pacific.
Pretty much from here, you'll learn how to build Workato automation recipes, you'll build your very own first recipe, and you'll earn your automation pro-one certificate with the assistance of an expert instructor and so much more, so definitely, register for that if you are interested. Finally, we have this webinar called Market Trends in Integration and Automation. The session is going to be on Wednesday, April 19 at 10:00 AM Pacific. We're going to have Keith Guttridge VP Analyst over at Gartner.
He'll essentially be talking about analyzing market data and customer buyer journeys and just identifying trends between integration and automation technologies. Again, go ahead and register for that as well if you are interested. With that, that concludes the session today. I just wanted to give a huge thank you, Matthew, for joining us today and, Carter, for helping and moderating this session as well. This was really great. We learned a lot.
00:39:38 - 00:39:39
Carter
Yes, thank you, Matt.
00:39:40 - 00:39:41
Matthew
Thanks so much for having me. It was great.
00:39:42 - 00:39:44
Carter
We can thank you everybody for joining us. Look forward to the next Confessions.
00:39:45 - 00:39:55
Layla
Awesome. Thanks, everyone for joining the session today and reminder, just keep an eye out for your emails for that recording link after. Thanks, everyone. Have a great rest of your day.
00:39:56
Carter
Bye.
00:39:56
Matthew
Thanks.
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