Why AI Adoption Is Missing This Critical Piece | IBM Partner Plus

#IBMPartner Generative AI is easy to try and hard to run safely. If you’ve ever watched a brilliant demo fall apart when it hits real data, real users, and real governance, this conversation is for you. 

We sit down with Brian Syring, Director of Sales at TechD, to get practical about what enterprise AI adoption actually demands and why trust becomes the deciding factor when GenAI still feels like a black box to many leaders. 

We cover: 

• Unpack what it means to be an IBM Gold business partner and how TechD works as an extension of IBM across pre-sales, delivery, and ongoing management. 
• Brian shares what he’s seeing in the market, especially the surge of interest in IBM Watsonx and the wider generative AI platform approach, where organisations want flexibility, security, and strong governance rather than a one-size-fits-all tool. 
• Aligning AI programmes to business outcomes such as time saved, cost reduced, and better decisions.
• Replacing spreadsheet-driven operations with secure, scalable systems to improve auditability and resilience.
• We also dig into the cultural shift: aligning senior stakeholders, defining the ROI, and ensuring employees truly adopt the new ways of working. 
• We finish with a look at what’s next on IBM’s roadmap, including orchestration capabilities and the longer-term excitement around quantum. 

The most actionable part is the reality check on why AI programmes stall: the data. Clean, secure, trustworthy data is the foundation for reliable outputs, and without it you get “garbage in, garbage out” at scale. 
 
If you found this useful, subscribe, share it with a colleague who owns AI delivery, and leave a review with the biggest blocker you’re facing in taking GenAI from pilot to production.

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Watch this on YouTube: https://youtu.be/NHZ4Bz9NZR0    

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Transcript

Welcome And Guest Introduction

SPEAKER_00 0:03

Hi, I'm Kieran Gilmury, author, board advisor, educator, chief AI officer, and digital transformation executive. I work with senior leaders, boards, global organizations, and beyond on AI strategy leadership and the practical adoption of disruptive digital technology. Today I'm joined by Brian Searing, Director of Sales at TechD, an IBM Gold business partner. Brian and the team have been helping companies and organizations optimize their IBM data analytics and data management systems, their hybrid cloud and security solutions, all the way back since 2019. Or is it 2019 or 209, Brian? 2009. Oh my goodness, it's even longer than I thought. Fantastic. You really have been there from the start. Brian, for those who don't know you, then sorry, I'm about to jump in and just start chatting away because we'll have a bit of fun here. For those that don't know you, would you mind giving us a little bit of an introduction to you?

SPEAKER_01 0:57

Yeah, sure. Um, so Brian Searing um with technology dynamics, we're often known as Tech D. Um, I've been with TechD about five years now. Prior to that, was with IBM um for about four to five years as well. All within the data analytics and big data, hybrid cloud space as it continues to evolve. So um been working with organizations and different customers and big blue for about 10 years now.

SPEAKER_00 1:23

Wow. Do you know what's always interesting for me to find the folks in the IBM ecosphere tend to stay, you know, in and around it. They really love the company, really admire uh the talent that's in the company as well, as well as solutions. So it's kind of exciting. I really do enjoy talking to folks who come from that environment. So uh just a quick live, we better get on with the interview, otherwise the audience will absolutely shout at me. Uh, tech D has been an IBM gold business partner since uh 2009, as you said. You've seen some of the big errors, therefore, of AI, you know, the big data, hybrid cloud changing, and now generative AI. So I'm assuming being an IBM partner is involved. So, what does it actually mean? What's a partner? How has it involved? And why did you choose to build your foundation so deeply in the IBM stack itself?

What An IBM Business Partner Does

SPEAKER_01 2:15

Yeah, sure. It's a great question. So um being a partner is is really an extension of the IBM team. So we come in as both pre-sales, post-sales, um, and experts as it relates to the general technology stack. Um, and one of the reasons we've really focused on IBM is because it's been around for as long as it has. I think just recently celebrated its 115th anniversary or birthday, if you will. Um, it's continued to evolve within as as big data, as data has evolved, as it's the overall ecosystem has evolved. And so by partnering with a company that's continued to evolve, it allows us to be you know front and center as everything's changing. And it's pretty exciting. Um, it allows us to work with some of the most intelligent people in the industry, as well as those that are um, you know, really making change at organizations. Um, and so that's that's why I think it it just helps us um really be a key provider for IBM and and vice versa for that.

SPEAKER_00 3:18

Yeah, it's funny. I've been around IBM myself for about 20 years, you know, uh customer partner, whatever else. I I love what you're saying there, you know, the the intellectual capability, the products, everything has really evolved. I don't think people realize at times how much the company has invented and reinvented itself over the year, over the years, sorry. But you you've integrated a lot of different IBM products, I'm assuming, across all of those practice areas, the analytics, the data management systems, the cloud and uh security solutions. What are you seeing today? Where's the most growth happening or the most client demand happening within that portfolio?

SPEAKER_01 3:55

Yeah, definitely over the last year or two, it's it's been exponentially more interested in the Watson X and the generative AI space. So clients just interested in what IBM has to offer, why are they offering, how are they going to market? How does that um how does that relate to their business? And it's a lot of it's been around that generative AI space.

SPEAKER_00 4:17

Okay. Uh why why are people looking at this tech? You know, because you've got IBM's data, you've got their portfolio. Why is it easier or better for clients to implement it or scale it compared to some of the other solutions or some of the other partners that uh tech D

Where Client Demand Is Rising

SPEAKER_00 4:35

could have actually, you know, joined up with in the market?

SPEAKER_01 4:38

Yeah, sure. I think there's a number of reasons. I think first and foremost is people trust IBM. I think that's what comes to mind a lot with the conversations is when you're talking about generative AI and it's not um it's still kind of a black box for a lot of folks. They trust IBM as it relates to security, to governance, and to doing the right thing. Um, and so they're interested in how they're leveraging now this this piece of tech to enhance their business. Um I think this is an interesting uh time because uh just about everybody has their hands on some type of generative AI. They use ChatGPT or cloud in their day-to-day, but implementing that at an organizational level or an enterprise level is uh significantly different. Um and so when they're looking to do that at the scale and the scope, they they trust IBM to do that. Um where I think it helps us us and IBM is you know, their generative AI is really a platform, right? So you can pick and choose and use some of the the best in breed, and you're not stuck into one piece of technology. And that's that's very powerful when you're looking to do real change at a at an organization.

SPEAKER_00 5:48

Yeah, so just so people are aware, like adopting a platform like IBM Watson, it's as much a you know a big cultural shift for any business as it as it is a technical shift. I think your company philosophy, you know, principles deliver. What does that mean?

Trust Governance And Platform Choice

SPEAKER_00 6:05

How do you how does this senior team, you know, guide like yourselves, guide clients through that big change? Um what are they seeing as part of their return on investment for the new technology, the new huge cultures that they're actually implementing around that?

SPEAKER_01 6:21

Yeah, I think I think first and foremost, it's approaching it like client first. What are they trying to get out of this tech? Um, it's not magic, although the technology is there and you can definitely utilize it. So we really, we really try to align with the key business decision makers at an organization. What is the real ROI that they're trying to get out of it? Is it human time? Is it save money? So then we can align to those objectives and really look to implement the solution and the path to implement that solution in the most effective way possible. Um, so I think that's where we come in is you know, having done a variety of these types of projects, you see where some of the pitfalls are, you see where you know organizations get hung up or where they have a lot of success. And so it's then leveraging that uh that history and that experience to kind of direct our new set of clients or prospects to say, hey guys, we may want to look at it from a different lens. Here's where we've had success, here's why we've had it. Can we do the same thing within your organization to adopt these tools, not only adopt them from a technology standpoint, but then from an employee standpoint, right? The the change side of things is is important too in making sure that all this work you put into make a product successful from a technology and implementation that you as an employee or as a consumer actually use it. Um, so that's where we really try and get to understand what they're trying to solve, why are they solving it, and then we back into the pieces of technology to get there.

SPEAKER_00 7:53

Yeah, I love the way you're starting with that. You know, I see a lot of companies performing what I call AI theater. You know, they're doing stuff with AI, but you've gone right from business outcome all the way back from the tech because the foundations are the same, the people, the process, and the tech. If I push you a little bit though, Brian, have you got a

ROI Culture Change And Adoption

SPEAKER_00 8:10

you know, a real concrete example of where that technology, that partnership, you know, has been absolutely key? Has there been someone you know struggling a little bit maybe around you know the security, their architecture, their their AI? And you and IBM are really able to make that same?

SPEAKER_01 8:29

Yeah, I think I mean we have a couple different um examples, and and some around the generative AI space, some are just data analytics in general. But um, one is with a like a fintech organization that was looking to really automate their data pipeline flows that then get presented out to their organization or to their customers. Um, and this this spanned four or five different IBM products, Red Hat, as well as um different parts of the IBM portfolio. And so our team, along with the IBM folks, because of how the depth of different products that we're talking about and how they integrate with the organization, kind of came together to put an architecture in place that was leveraging um one of IBM's flagship products like Cloudpack for Data, running on Red Hat OpenShift across um multiple AWS environments with a backup and security plan in place to get that up and running. And then we helped fully manage that environment. So we couldn't have done that alone. We needed some of that expertise that IBM has across the different parts of the portfolio to make sure that we were successful in that. Um that's one. And then one that we see that we we recently um came across is it was an organization really running on spreadsheets. They had, I mean, they had their financial um technology, they had their CRM, they had a variety of different pieces, their databases. But the core part is the UI was Excel spreadsheets. So we came in and helped them kind of re-swizzle that Excel

Real Projects From Fintech To Excel

SPEAKER_01 10:05

spreadsheet into a um a different type of UI that allowed them still the same functionality, but with an underlying database that was secure, it was scalable, it was redundant. Um, and then to give them more visibility and flexibility in terms of how is my business performing today? How does it look for the future? And to really drive some of those business business outcomes. So that was leveraging IBM technology with our professional services to kind of take a look at current environment and put them into a future state.

SPEAKER_00 10:37

Yeah, I really like that. The bit that I think people miss sometimes, because I see what I call Excel fungi everywhere. You know, you get an Excel spreadsheet the way it goes. But now that redundancy bit, I've got the security, I've got the audibility, I've got the traceability, I've got an actual backup, I maybe have different, you know, uh rollback scenarios and everything else. And and it's that decision quality, Brian, I think shifts through the roof once you actually put you know a solid application in place. So I suppose about is that a great example of an organization that was struggling? Because sometimes this isn't easy. You know, let's be honest, you know, you're not walking in, here's a piece of deck, copy, paste, job done. And a lot of organizations are actually struggling to truly operationalize AI at any scale. What are you seeing? Why do you think that is the case? And then what's tech D and yourselves doing, you know, to simplify the adoption, you know, reduce the complexity, and most importantly, where we were a moment ago, you know, realize value more quickly than ever.

SPEAKER_01 11:42

Yeah. I I think what's interesting is it still comes down to the data. So everybody wants a nice, quick outcome, but if you don't have the data in place and it's not clean, it's not secure, it's not trustworthy, then you're going to struggle to get the outcomes that you're looking for and the trusted response from an AI standpoint. So when we're working with organizations, we try and call that out from the beginning and narrow in on the right type of data that's already in place within within the company that we have access to, with the stakeholders that have the ability to really make change. And we focus in on that. And so it's yeah, can we do something with a piece of tacky? Sure. But it's the it's garbage in, garbage out at the end of the day. So let's start from the beginning where everything is the foundation. Let's make sure we're all bought in on that piece of those pieces of data, that type of um use case that we want to solve.

Why AI Fails Without Good Data

SPEAKER_01 12:40

And then we we implement the technology from there. So I think that's where us from getting involved with this, yeah, AI can be complex. It could be challenging, but if we narrow in on where we know we've been successful, where we know we have the data and we have the buy-in, then that'll help the organization kind of start small and improve, and it'll help us prove that we know what we're doing and how we can go forward.

SPEAKER_00 13:05

Yeah, there are no harry potter shortcuts to smaller technology, don't we? Should we just unfortunately not? Yeah, yeah, I know, I know. I I did try and go to the Harry Potter shop and buy good data and buy good security and buy cloud solutions, but unfortunately, it must have been an off day for the shopkeeper. It wasn't that. So looking at IBM's current roadmap, what's the piece of technology or what's the upcoming capability that that you and your engineering teams are most excited about getting analysed on over the next 12 months, Mike?

SPEAKER_01 13:40

So where we we play is really on the data analytics side, I'd say is a broad scope. I think where they're going in quantum is going to be pretty exciting and something that you know we should probably spend more time getting involved with. Um, but where we sit today around just their generative AI capabilities, um, kind of as a broad sense, they have a product called Bob and Watson X Orchestrate. And what they're doing with that is actually implementing it across their broader set of technology. And I think that's going to continue to improve how organizations work with this type of tech and implement it, how it's going to make it easier and more effective. Um, we were having a conversation with a client the other day that you know sits in this part of the portfolio, and what kept coming up was the generative AI side and how IBM is now connecting all of these pieces of technology and making it more user-friendly, making it easier and really you know helping enhance the enterprise adoption of AI. Um so I think that's to me, that's what's most exciting, right? It's making it easier, more effective across their entire set of probably hundreds of tools.

SPEAKER_00 14:47

Yeah, I think that's exciting, but isn't it? Now you've got all the individual Legos that in themselves were great. Yeah. But now you start to build the hospital,

What TechD Is Watching Next

SPEAKER_00 14:55

the fire engine, the police station, or whatever it else using all of those and connecting them together. So we live in exciting times. And I have to say, I've been following the IBM quantum story for a couple of years. I was actually in London and Boston and seeing the quantum computer as well. So bit of a fanboy looking at that. You're going, wow, I've seen that in so many pictures. And I was sort of a couple of years ago going, I wonder if that will come to commercial scale based on the timelines that IBM were suggesting. And it is. Now you can imagine putting Gen AI plus AI plus you know, patentic AI plus quantum together, plus data, plus you know, that's a kind of exciting journey and one that you'd want to buy into. Brian, we we will run out of time, unfortunately. You and I've got a lot of fun talking about this tech because you're hitting all the key areas that I get excited about the data, the data management, the security, the portfolio, the cloud. You know, those are the key building blocks for anybody to build, you know, let's be honest, a proper, functioning, secure, agile, operational business that actually works at scale and is flexible enough to bend in yield with the market. Because let's be honest, the market is changing quicker than I've ever seen it in my 20 or 30 years, and buying into 20-year fixed, whatever you want to call it, ERPs or whatever, those days are maybe behind us. If people want to know a little bit more about you, a little bit more about tech D, some of the options, some of the experiences you've had, learn some about the case studies, have a conversation. Uh, where should they go?

SPEAKER_01 16:23

Yeah, I would start with our website, techd.com. Um, we're easily accessible. Our um senior management is easily accessible. We're happy to jump on calls just to further introduce, you know, better understand what someone's trying to accomplish and if there's an area we can assist. So I think that's probably the best spot. You can go through your IBM partner or IBM contact if uh you already have one. Um quick Google search and you know,

How To Reach TechD And Final Thoughts

SPEAKER_01 16:50

easily accessible that way.

SPEAKER_00 16:52

Fantastic. Thank you so much, Brian, for sharing the story. Folks, thank you so much indeed for listening in. I don't think we've ever lived in a time period that is more fruitful, more exciting than we're currently living in today. I think if you see problems, you will always see problems. The only thing I see at the moment is opportunity. Uh, Brian and the team are creating opportunities for their clients. Uh, you too could potentially be one of those. So please do take a moment to reach out to Brian and the team. I'm sure, as he has said, he is accessible. Uh, you can find him in lots of way. I'll include in the comments, I'll include in the links, links to Brian and the team and everything else. But I wish you every success, Brian. Uh, you and I will no doubt get talking soon. Everyone else, look, every success. The tooling and the technology is there. Now it's not the limit. The limit is your imagination and what you're willing to do with that tech. I wish you every success.

SPEAKER_01 17:45

Thank you. Thanks for your time.