2935: How Ahead is Unleashing the Power of Enterprise Automation and AI

[00:00:01] Are you ready to uncover how cutting-edge technology is reshaping the business landscape? Good, because today on Tech Talks Daily I'm joined by Will LaHouber and he is the CTO at AHEAD, a company at the forefront of enterprise automation, AI,

[00:00:19] cloud solutions and so much more. And Will brings a wealth of knowledge from his recent transition from CDI where he served as CTO before its acquisition by AHEAD. Now Will is based in New York City but he's traveling to Chicago today

[00:00:35] but he didn't call off the podcast, he still agreed to sit down and have a conversation with me. So Will and I are going to delve into how AHEAD is integrating automation across various sectors like IT, healthcare etc and also

[00:00:50] drastically enhancing speed, efficiency and consistency while focusing on high value work. I will also touch on the importance of security, embedding it into every layer of an organization and how the rapid adoption of AI has sparked both excitement and concern pushing the need for robust governance

[00:01:12] frameworks to ensure responsible deployment. And also if we've got time as cloud costs continue to balloon I also want to explore how AHEAD's FinOps strategy is ensuring efficiency without sacrificing performance. So buckle up and

[00:01:28] hold on tight as I beam your ears all the way to Chicago where we're gonna track down Will for a conversation about all this and much more. So a massive warm welcome to the show. Can you tell everyone listening a little

[00:01:43] about who you are and what you do? My name is Will Huber, I am part of the office of the CTO at AHEAD. I'm new to AHEAD, I just joined AHEAD by way of acquisition. Our prior company I was the CTO of a company called CDI based

[00:02:02] out of New York City and I've joined AHEAD as of February 1st so it's exciting to be here. Fantastic and I'm conscious there'll be a lot of people listening that maybe are hearing about AHEAD for the very first time and

[00:02:16] with the increasing emphasis on things like operational efficiency and productivity, how do you at AHEAD approach integrating automation into enterprise IT infrastructures and what kind of impacts have you observed in terms of things like performance and scalability? And if you can share around that just

[00:02:34] to set the scene for our conversation today. Yeah so I think you know enterprise automation I think we tend to think of it a lot in terms of IT. We actually think of automation extending far beyond IT so naturally however it is

[00:02:51] typically a common place for us to start just given the background and the nature of a lot of things that we do in the IT world but we've actually consulted with companies implementing automation in other departments outside

[00:03:06] of IT, things like HR, things like accounting, finance, back office operations those types of things. You know and I think you know and for that reason we don't actually have like a centralized and neither did CDI. We didn't have like

[00:03:22] a centralized automation practice right. It's just sort of an assumed thing in fact if you look at a lot of our external messaging that you might see on our website or that we communicate to customers, we sort of articulate the

[00:03:37] different types of platforms and and departments that we have from an organizational standpoint and then we actually intentionally wrap automation like in a visual manner. We have a circle around the whole thing that says we have to automate across all of these different perspectives and all of these

[00:03:54] different platforms. So I mean we've been in the automation business for quite a long time. In terms of the benefits I mean there's the obvious ones right you know speed to deployment when you're talking about systems. I mean we still

[00:04:06] today come across customers that you know it takes them months to deploy software or to deploy applications or full systems into production and automation can take that you know measurement of months down to you know maybe it's weeks, maybe it's days, maybe it's minutes right in certain scenarios

[00:04:27] we've actually seen those types of impacts and I think that has sort of downstream that has a scale implication allows you to do you know get to more things because your people aren't tied up you know doing manual tasks. There's

[00:04:40] cost benefit right because those people are spending less time doing those types of things and then I think there's there's other benefits that are you know maybe less tangible or maybe less you know maybe a little more difficult to understand. There's operational benefits right there's you

[00:04:57] know consider a case where you know you've deployed a hundred systems or a hundred servers in a manual fashion you know and a human may have done their best to make sure that they were all configured exactly the same way and

[00:05:10] three months, six months, twelve months from now there's some sort of operational problem or incident or issue with that system and it comes to you come to find out that it's because one of those 100 systems was configured

[00:05:23] slightly differently than the others and so there's benefits in that regard and I think maybe another one that's less tangible or difficult to see from the beginning is you know it provides your staff the ability to spend more time on

[00:05:37] more impactful and often more fulfilling work which gives your people career paths and you know growth opportunities and those types of things. Absolutely and in the context of digital transformation cyber security remains a paramount concern for businesses and on this podcast every day we always try and

[00:05:57] get tips and insights that would help business leaders listening so can you tell me a little bit more about the strategies that you suggest and recommend at AHEAD for enhancing integrated security measures and and how these adapt to evolving cyber threats as well?

[00:06:14] Yeah I think it's obviously a very relevant topic and actually this is another example where you know we do have a security group within AHEAD. That said, security is sort of embedded throughout every other group like we

[00:06:32] can't you know we have to think about security we very much advocate for sort of zero trust principles where you know you sort of you know you verify explicitly you provide least privilege access and you assume breach and to do

[00:06:48] that properly I mean we have to think about security through every possible lens right it's not just about infrastructure it's not just about applications you have to think about data you have to think about networks you

[00:06:59] have to think about operations you have to think about people and so we've again you know we do have a centralized security group that focuses more on like strategy consulting but we train our people across the board we train our

[00:07:14] network people on how to build secure networks we train our data center people on how to build secure data centers we train our DevOps teams how to build security principles into the software development lifecycle so that we're

[00:07:26] building secure software along the way and not just building software that we try and secure after it's been built right so I think that sort of multifaceted approach is important to building a comprehensive security

[00:07:39] strategy and in terms of how we do that with customers I mean we have a we have a portfolio of you know we have a red team that does a lot of assessments they do things like penetration tests they do gap assessments vulnerability

[00:07:55] assessments maturity assessments and typically from those assessments we learn a lot about the security posture of our customers environments and then we provide them sort of a get well plan that either they can go and execute on

[00:08:08] their own right through a series of procuring maybe it's tools maybe it's investment in people maybe it's change in process or we also have engineering services that could sort of you know take components or all of that that get

[00:08:22] well plan and then in addition to that we also we actually have our own our own SOC service where we provide a 24 by 7 managed security service that's doing real-time monitoring and then also incident response services as well and

[00:08:39] of course outside of the security posture side of things there's also the mainstream adoption of all things AI right now there's a lot of excitement about it but as we as we mature in this field adopting AI lifecycle governance

[00:08:53] is actually crucial for deploying reliable and transparent AI systems again huge talking point right now so how do you ahead assist organizations in establishing government frameworks and ultimately ensure AI performance while maintaining those ethical standards because it's quite a tricky balance

[00:09:12] sometimes isn't it? It is, it's amazing I'm surprised we got 10 minutes into this call without without mentioning AI yet you know it's funny I think what I think about AI you know the adoption rate that we've seen it's really like almost like

[00:09:28] nothing we've seen before in terms of you know the hype and the excitement and the opportunity I think and but that said right I think sometimes people forget that you know we'll talk about chat GPT for a second I mean it's not

[00:09:44] even a year and a half old yet right and it's got hundreds of millions of users that are using this thing every day and it's sort of created this this craze like an AI rush almost and that said like when there's anything new right I

[00:09:59] mean I think back 15 years or so with like the cloud rush right people just rushed to go and experiment and do and you know a lot of times they went out and they saw some pretty cool things they got some cool outcomes and you know

[00:10:15] all of a sudden before you know it it spirals out of control right and so just like with cloud right I think there's this emerging need for governance and sort of I like to call them guardrails or bumper pads around how do we do this

[00:10:30] responsibly and so I think that you know if I think about like what is AI lifecycle governance I mean we're governance in general right it's really how do we control the implementation and the operation of these systems so that

[00:10:45] they're in accordance with internal policy with things like external compliance I think we're probably going to see the regulation in this space at some point in the near future you know and I think the way we're approaching

[00:11:01] this is we've developed some consulting services where we can deploy teams of consultants that can help customers establish this AI lifecycle policy and you know we talk about things like you know we'll have like ideation workshops

[00:11:15] to identify you know use cases for AI systems that's a popular one and then we sort of step through a process where we go through you know the building of and training of models the deployment of systems into production ultimately

[00:11:30] operating those systems and then eventually maybe retiring or augmenting those systems if you need to update a model or train a new model or etc etc so I think that you know it's an interesting space because and we don't

[00:11:44] have all the answers yet nobody does you know we're early innings here and learning we're learning more every day and another thing we don't talk about enough is efficiency in development because it is critical for this fast

[00:11:55] paced tech landscape that we're experiencing right now so are you able to shed any light on our ahead you leverage internal developer platforms to maybe enhance development efficiency and foster innovation within organizations we've seen so many examples of people that get it wrong but it'd be great to

[00:12:12] hear some of how you're getting that right yeah I think you know developer productivity is a big problem you know you know we've seen you know if you we've seen examples where you surveyed developer and you ask them you know hey

[00:12:25] how much time are you spending writing actually spending on coding projects like writing feature impacting code and sometimes the answer is two to three hours a day in fact more often than not it is and I think that they spend a lot

[00:12:39] of the rest of their time on integration problems troubleshooting deployments operational issues change control meetings like all kinds of stuff that we've been sort of troubled with over the years with with you know which comes with manual process and those types of things and you know if you're

[00:12:55] if you're an enterprise there's a hundred developers and you're paying those developers a hundred or a hundred and fifty thousand dollars a year or something like that which is not out of the norm you know that's a ten to fifteen

[00:13:05] million dollar problem and like when you look at those inefficiencies you can start to see the magnitude of that issue and why it's important to implement process and tooling and procedures that will increase that two

[00:13:18] to three hours a day to five to six hours a day right or seven or more hours a day right so the bigger the number the better and so the way we address this is is with our developer platform or we refer to it as our platform engineering

[00:13:32] portfolio platform engineering is sort of emerging as a well-respected and common term in the enterprise and really what it is is a collection of portfolio capabilities that we that we implement to help our customers put in systems that can simplify and automate the development experience and the

[00:13:53] development process through the ICD pipeline repositories infrastructure pipelines those types of things and we sort of break it into four categories we have will be called developer experience modernization platform engineering modernization so how do we help customers to release apps faster with

[00:14:10] standard pipelines developer portals so I think a lot of times you've got customers who maybe to have disparate development teams that are working on different features or different products and maybe they're using different tools maybe they're using there's no standards or methods or

[00:14:27] patterns that they use or libraries that they use so a lot of these these developer portals help to sort of standardize that and get everybody access to the same building blocks that they need to build their apps and then

[00:14:40] infrastructure automation which we've talked about already you know it's sort of part of this capability which is utilizing things like infrastructure as code and common repeatable patterns to build you know solid foundational infrastructure blocks to deploy these apps to and then integrating sort of

[00:14:57] that application developer experience to the infrastructure experience to give you an end-to-end view or an end-to-end experience to build and deploy and operate apps is what we're after with this group. And we were talking about AI a

[00:15:09] few moments ago and we've seen the impacts of AI across so many different industries and I'd love to zoom in on one in particular just and try and bring that to life and the transformative power of AI in health care for example is

[00:15:23] undeniable so from your perspective what are the most significant changes AI is bringing to health care and how is it impacting things like patient care research and operational efficiency because I think we often get bogged down with the the hype cycle and everything but we're solving real-world problems

[00:15:40] here with this technology too right? Yeah for sure it's a very timely question I'm actually in Chicago right now for we're hosting an enterprise health care summit where we have I think it's eight eight to ten CIOs from our top health

[00:15:56] care customers so health care is a big focus of the heads and you can imagine that one of the big topics on the agenda for the summit it's a two-day summit one of the big topics is AI. So we've seen a lot of things in health

[00:16:09] care we've seen things like administrative tasks you know think of things like appointment scheduling you know automating back office things you know billing we've seen things like case summarization and like post visit follow-up generation as you know with with generative AI use cases and then

[00:16:27] we've also seen things like imagine you know a radiologist you know goes into the office in the morning and has a hundred cases to review and maybe the AI can provide a report to that radiologist and says hey there's a hundred things you

[00:16:41] have to review but these are the these are the five that are the most critical right these are the ones that are you probably want to pay attention to and then get to the others when you do right so you want to get to the things that

[00:16:52] are the most severe first and then on the flip side of that maybe there's a scenario where the radiologist reviews a series of images but what if they missed something that the AI may have detected could be an issue so it can you

[00:17:07] know sort of bring that back to the attention to provide you know a more thorough investigation and perhaps a diagnosis of that imaging. So we've seen things like that. We've also seen you know things like predictive use cases

[00:17:22] where maybe machine learning algorithms can look at things like patient data combine that or correlate that with with genetic information about that patient maybe lifestyle factors those types of things and can make predictive you know predictions on maybe future diagnoses so you can intervene early. What else we've

[00:17:46] seen in like the real-time monitoring so let's say you have a patient in the hospital right who is you know connected to a bunch of machines that are doing monitoring of different different things and we've seen actually seen some of the

[00:18:00] EMR companies have developed some AI capabilities to evaluate in real time the metrics and the telemetry that's coming from from those machines and can actually algorithmically predict when a patient's status is deteriorating so that they can then alert a care team to go and intervene proactively versus waiting

[00:18:22] for a nurse or a doctor or PA or somebody to go make like a scheduled round right so you know that that's what that has a significant impact on you know in some cases that could save somebody's life right so I think the the use cases in

[00:18:38] healthcare are and it's early again like that there's there's going to be so much more that we see but already we've seen some pretty awesome results of the use of AI in health care. Incredibly cool and of course things are not all AI you

[00:18:53] mentioned 15 years ago everyone rushed into the cloud cloud is still a huge huge of importance to businesses but I think that the problems have changed there over the years and now it's managing cloud cost effectively has become essential for organizations that want to maximize their cloud

[00:19:09] investment so what's your approach ahead for creating budgets and alerts for cloud workloads and ultimately ensuring cost-effectiveness without compromising on performance again another tricky balance but what are you seeing here? Yeah it's funny you know I feel like we operate in a bit of a cyclical world

[00:19:32] right we see you know new technology when cloud came out there was this big rush to go to the cloud and I think a lot of a lot of customers and this isn't a this isn't a negative thing right a lot of customers implemented cloud in a way

[00:19:46] that maybe wasn't optimal right you know they did what they knew at the time it was new technology maybe they didn't know better you know there's a lot of reasons why that may or may not have happened but I use like the classic

[00:19:59] lift-and-shift example right a lot of customers took their on-premises state and they mirrored it in the cloud right well in the on-premises world you know maybe that maybe that system was configured with more resources than it

[00:20:15] needed but nobody really cared because they had all this excess capacity and their virtualized infrastructure and nobody knew any different there was there was no you know water meter or electric meter running and and running

[00:20:29] up a bill right in the cloud different story right so I think a lot of customers at the beginning didn't really pay much attention to the cost implications of cloud and not only until they reached a critical mass you know at

[00:20:47] some point the bill starts to grow so big it gets to somebody's desk and that person starts asking questions well what's going on here and so you know I think you know we've been helping customers to you know FinOps has sort of

[00:21:01] become this this common common terminology in the world is how do I how do I manage the financial sort of elements of class of IT really it's not just cloud right we have a FinOps consulting or financial consulting division that provides consulting services to help customers establish

[00:21:22] budgets you know do our lie analysis those types of things but in the context of your question you know we have a service that helps customers we can establish and we provide this as a service but then also we can do it as a

[00:21:38] like as a managed service we can also do it as a consulting service where the customer sort of manages steady state going forward but we work with various different FinOps platforms that allow you to implement cloud budgets that could be applied to applications environments teams divisions you name

[00:21:57] it where you can set spending limits for different user populations or different use cases which helps you to avoid unexpected outages right and there's other benefits like with those platforms you can tie alerts to those spending

[00:22:11] limits which allow you the opportunity to go in monitor consumption you can look at spending you can do better forecasting you know future budgeting and then you can set you know spending thresholds you can do you can look at

[00:22:25] resource utilization you can find idle resources that might be running that you didn't know about that are incurring charges that you might want to just turn off or potentially delete entirely you can look at anomalies to identify spikes

[00:22:40] or unusual patterns to sort of get ahead of future cost issues in the future so we've seen a lot of success with that group and I think you know that business is growing because again a lot of organizations now are hitting that

[00:22:55] critical mass where the bills are getting big and they need to do something about it and this is a way to help them do it. Fantastic well I cannot thank you enough for taking the time to come on here and share your insights

[00:23:07] with everyone listening all around the world today but before I let you go I always ask my guests to leave everyone listening with one final gift and that can be either a book that means something to you or you'd recommend that

[00:23:19] we can add to our Amazon wish list or a song that we can add to our Spotify playlist that means something to you. I don't care what it is guilty pleasures are allowed but what would you like to leave everyone listening with? You know

[00:23:31] it's funny I'll leave folks with a gift that I've received in my life we use the leadership coach at CDI his name is Jim Riviello so Jim has written a couple books you can find his books on Amazon we call him RIV for short he

[00:23:47] actually has a company that he that he runs it's called Leadership X University and he develops he's got all kinds of you know professional development programs and I have the great opportunity to meet with him

[00:24:00] frequently he's he's had a profound impact on me and many of my peers and so you can find him his website it's LXU.training is the website so go go check him out I promise you to be worth your time. Awesome well I'll

[00:24:18] get a link added to that so people can find it nice and easily and for anyone listening just wants to find out more information about AHEAD and the work that you're doing the topics we explored today contact you or your team what's

[00:24:29] the best starting point for everything? Well I would I would say everyone can visit our website at the AHEAD.com very simple and you can find us on all the major social channels we're on LinkedIn is probably the biggest one but but

[00:24:44] others you know Facebook Twitter YouTube all that kind of stuff. Brilliant I'll get those added to the show notes too and we've covered a lot today from how you focus on propelling organizational transformation in I think it's about six different key areas cloud platforms digital engineering data analytics

[00:25:03] next-gen data center enterprise automation and integrated security but yes we did manage to get AI in there today as well but I know you're in Chicago at the moment you're incredibly busy on the road but thank you so much

[00:25:17] for just taking the time out to sit down and share your insights with me today thanks again. You got it thank you very much for having me I appreciate it. So as we wrap up our conversation think about the technological transformations in

[00:25:29] your own field how does technology drive efficiency in your daily operations what steps does your organization take to ensure the ethical use of AI I'd love to hear your thoughts so please share them with me in the comments or

[00:25:44] tweet me directly or slide into the DMS on LinkedIn Twitter Instagram just at Neil C Hughes my emails tech blog writer at outlook.com love to hear from you on how the integration of technologies like AI and like cloud computing and

[00:25:58] can further revolutionize industries so let's keep this conversation going. Other than that I'll be back bright and early tomorrow with another guest so thank you for listening today though and until next time don't be a stranger