IBM Consulting and the Future of Generative AI

[00:00:03] How is AI reshaping the consulting world? And what does it take to build a truly transformative approach? Today I'm joined by Mohamed Ali, Senior Vice President of IBM Consulting. And he has a remarkable background in cybersecurity, data and AI. But he's now spearheading a new era for IBM Consulting. But he's now spearheading a new era for IBM Consulting.

[00:00:31] One that blends innovation with real world application. So together we're going to explore how AI is unlocking enterprise opportunities. Why an open ecosystem is critical. And what it means to upskill talent in the age of generative AI. But enough scene setting for me. Let's get my guest onto the show right now. So a massive warm welcome to the show.

[00:00:58] Can you tell everyone listening a little about who you are and what you do? Yeah. Hi, Neil. So first of all, thank you for having me on the show. I'm Mohamed Ali. I'm head of IBM Consulting. Well, it's a pleasure to have you join me today. And I was reading before you came on the podcast that you've recently rejoined IBM after leading roles at IDG and Carbonite to name a few. But you're now bringing this fresh perspective to IBM Consulting.

[00:01:25] So I've got to ask, what changes are you implementing to maybe reshape the traditional IT consulting services industry? And how is your more software-driven mindset maybe influencing this transformation? Yeah. Thanks for asking. I think you're right. You know, this whole consulting market requires a fresh perspective. And I did start my career, had a big part of my career at the beginning at IBM. And then I left for 14 years.

[00:01:54] I was CEO of these two companies that you mentioned, which are smaller. And so, of course, you can move faster. You can be much more nimble. And in some ways, you know, that's what I'm trying to bring to IBM Consulting. We're 160,000 people in IBM Consulting. So, of course, it's not quite as easy. Having said that, I think that our industry is going to be changing quite fast.

[00:02:20] As you know, our world is changing quite fast with Gen AI and other technologies. And for me, I see this as what I call our DVD to streaming moment. You know, those of the listeners who are familiar with Netflix, Netflix went from DVD to streaming and it transformed that company. And that is happening in our industry as consulting goes from labor only to labor plus AI-powered software. And that combination is really changing our world.

[00:02:50] So, we've actually moved extraordinarily fast. Probably one of the fastest times we've moved in IBM. And a couple of data points, we now have over $2 billion worth of business around Gen AI. And in order to do that, we actually had to build a software platform within consulting. We call it IBM Consulting Advantage. And we've now deployed that at scale. And it's probably one of the best platforms of its kind out there.

[00:03:18] So, you know, we've had to do a lot of this in the last 12 to 18 months. So, it's actually been kind of a remarkable change in the company at a, you know, very fast pace. And I've been going to a lot of tech conferences the last few years. And predictably, AI is the big talking point. It'll probably continue to do that next year as well. And it's changing so many different industries at the moment. But I'm curious, how are you seeing AI changing the consulting landscape?

[00:03:46] But in what ways are you at IBM Consulting also leveraging AI to transform things like client engagements? And how do you ultimately see the role of consultants and the role of consultants evolving with the rise of these generative AI technologies? I appreciate it's probably about five or six different questions in there. But what are you seeing? Right. Yeah. So, you know, we've actually developed a term for this now.

[00:04:10] We're calling it the science of consulting, where skills and expertise are coming together with science and technology in a way that it's never really come together before. And the way we implement that is by supercharging. That's a term we use. Our 160,000 consultants with 1.6 million digital workers. What does this mean?

[00:04:37] You know, today, if you use an assistant, a Gen AI assistant, you can only use it one at a time, right? So, it's, you know, so 160,000 consultants, you have 160,000 of these assistants. But we've recently introduced agents. And so, you could actually launch an agent to work for you. And another one and another one. So, you know, at some point, you'll be able to launch 10 of these things simultaneously. And so, this is sort of how we're implementing the science of consulting.

[00:05:05] And that's having already sort of remarkable effects on how we're delivering for our clients. And, you know, clients are actually almost demanding it now. There's a study that said that 86% of consulting buyers are actively looking for services that use Gen AI or some sort of technology asset. And so, the clients are demanding it. And we're actually, you know, using it in our projects.

[00:05:35] And in some cases, we're seeing some significant productivity gains, sometimes up to 50%. But it's not just productivity. This allows us to go faster. It allows us the time to actually engage the client and have strategic discussions. And so, one example of that is at Riyadh Air, where they're building a whole new airline from scratch to rival Emirates and those types of high-end aircraft, airlines.

[00:06:03] And what they're doing is instead of using sort of, you know, train ticket technology, which most of the airlines sort of use today, they're using a shopping cart experience like an Amazon. And it's a, you know, they're imagining everything. And that's just one example. And so, because we're using this Consulting Advantage platform, we have about 70% of our engineers working on this project, doing it on Consulting Advantage.

[00:06:28] They're able to do it faster so, you know, they have more time because in a project like this that is brand new and you're sort of constantly changing, it's important to have extra time for this project. So, we're actually at a schedule. We're able to work with the client on some of these strategic things. And, you know, the outcome is actually quite a bit better. So, you know, to answer your question, there's actually a lot of change happening in the consulting industry very quickly.

[00:06:57] And something else that stands out for me is an open ecosystem approach has always been the focus for IBM. So, why do you believe that is essential for businesses looking to fully unlock the potential of AI across the enterprise? And how do you think that is different from IBM's consulting strategy for more closed proprietary models? There are two opposite ends of the scale there, but why do you think it is so important? Yeah.

[00:07:25] And Neil, I'm glad you asked that because, you know, there was a time in history when you got all your technology from one company. And IBM was one of those companies that deliver that, right? And I would say, you know, the last few decades, IBM's moved away from that to an open approach because in order to deliver the best solutions now, you have to combine technologies from multiple vendors.

[00:07:51] And so, in consulting, we have some very deep partnerships with Microsoft, AWS, SAP, Oracle, Salesforce, Adobe, Palo Alto. There's just some of the leading ones that, you know, we have truly embraced and been bringing to market in order to build these great solutions for our clients. But with Gen.ai, each one of these companies I just mentioned have brought Gen.ai technologies. Of course, Microsoft has a large suite. AWS as well.

[00:08:19] SAP, Oracle, Salesforce has now Agent Force. Adobe has Firefly. Palo Alto has Precision AI. And so, what we've done is we've actually integrated these into our delivery platform, IBM Consulting Advantage, so that when our 160,000 consultants need to use Gen.ai, they have Gen.ai pre-integrated, they can move faster. When our clients want to use these technologies, they can move faster.

[00:08:46] So, yeah, I really believe that this sort of open approach is extraordinarily powerful. I'll just give you two quick examples. Sure. At Valle, which is one of the world's largest mining metals company, you know, in order to secure the company, we started with Microsoft security technology. And then we added our AI power threat detection services and elements to that.

[00:09:13] And so, by having these things pre-integrated, we're able to move very fast. In our public group, which is an advertising company there, you know, they wanted to move from an x86 data center into the cloud. And since we already had a really great Oracle relationship with AWS, understood their technologies, we were able to take the SAP workload and move it to the cloud where they were able to see about 20% improvement in the performance.

[00:09:42] And in part because, you know, we're taking this sort of asset-based Gen.ai approach where things are pre-integrated so we can move quicker. And generative AI has captured widespread attention. But I've spoken to so many business leaders over the last few months that they're still trying to find the right use case for their business. And many are struggling to find ROI from some of those projects that began maybe with a tech-first rather than problem-first approach. You're right.

[00:10:12] Just to focus on this a little, are there any use cases that you're seeing across industries that you can share and how IBM Consulting is helping clients harness these innovations to solve these real-world business challenges and get that ROI? Yeah. And Neil, you're so right. I mean, all this new stuff comes to market and everybody wants to play with it, right? So you're right. It's tech-first.

[00:10:39] But, you know, to really actually get the scale, it really needs to be sort of a use case first. And we're really seeing Gen.ai being deployed in three big buckets. And probably top of the list is customer service. Then the second is writing code, right, and doing application modernization, that sort of thing. Call it general productivity. I'll give you a couple of examples.

[00:11:06] So, you know, customer service, it's maybe what you expect, right? You know, there's a healthcare company we're working with, and we've been able to help them deflect about 30% of the calls that are coming in. They probably get about, you know, over a million calls or customer inquiries. And then you say, okay, well, if you're using technology to deflect calls or to handle calls, maybe the customer set goes down. It actually is the opposite. The customer set increased by 40%.

[00:11:35] Another kind of customer service that, one of my favorites, and it's actually in your country, Neil. There's a hospital group that we work with.

[00:11:46] And just by engaging the patients and ensuring that scheduling is correct and so forth, we were able to get this hospital group to see 700 more patients per week with no additional doctors, no additional nurses, no additional staff.

[00:12:07] But just optimizing and staying engaged on a customer service basis to make sure that, you know, people show up as schedules change, things get aligned. So, there's a really, really great customer service example. Writing code, we've been able to – there's a beverage company we've worked with where we saw 95% reduction in the effort to write Ansible code.

[00:12:33] That's kind of an unusual case, but there are cases that are really significant like that. And then in general productivity, you know, we work with a company where their procurement department was able to process 98% of their spend through these automated systems and they saved $40 million. So, I would say, yeah, those are sort of the three big buckets we're seeing. Customer service, writing code, and general productivity. Some great examples there. I love your UK example.

[00:13:02] It is notoriously difficult to see a doctor or get a doctor's appointment. That's right. I mean, this is a big issue in the UK, right? All my UK friends say sometimes they have to wait a long time. Yeah, yeah, if you're so right. There's a whole other podcast right there. But, I mean, one other topic is critically important right now is upskilling talent, especially when adopting AI at scale.

[00:13:25] And I think it's also important that AI enhances and complements human employees rather than replacing them. So, a big part of that is upskilling. So, how is IBM Consulting investing in upskilling in your own workforce? Do you have any advice for any other organizations or business leaders listening that may be wanting to prepare their teams for this age of AI, but a little bit unsure on where they start?

[00:14:20] Yeah. Because if the people don't trust the Gen AI, they're just not going to use it. And if they're not part of the reengineering of the processes, again, they're not going to adopt it, right? So, what we have done within IBM Consulting is first, we've trained everybody on how to use Gen AI. It's actually not that hard. And to be quite honest, a lot of people are using it all the time.

[00:14:49] But we've given them additional training. So, we have about 70,000 of the 160,000 that have a very high level of Gen AI certification. So, you train people. And then we put them at the center of reengineering our process. And we actually ran this hackathon with 158,000 people to get the team to help us figure out the processes they know. How can they improve them with Gen AI?

[00:15:16] And it worked remarkably well, right? I mean, there's really incredible embracement of the technology and putting it to usage, real ownership. And so, this change management is actually something that we have decided to make kind of a core competence of IBM Consulting as we work with clients.

[00:15:38] Because if you can't bring the people along and you can't do the change management, none of this is going to work, no matter how good the technology is. 100% with you there. And I think I should also highlight, because I was doing a little research on you, that your expertise spans across cybersecurity, data, and analytics, as well as AI. I don't want to get too carried away with just talking about AI.

[00:16:03] But I'm curious, from what you're seeing here, how do all these areas converge and intersect in your work at IBM Consulting? And why do you think it is important to approach AI implementation with a strong focus on data security, governance, and all those belts and braces approaches to IT that we were raising? Yeah, thank you for asking. You know, when I graduated from Stanford, I helped start a neural network company. And I remember my mother asking me, is that a real job?

[00:16:33] I've never heard of a neural network. That was 30 years ago, and I guess now it's gone full circle. And in the interim, you know, about 20 years ago, I helped build IBM's data and analytics business before I left. And then one of the companies I was CEO of was a cybersecurity data protection company. But it all sort of comes together, right? Because AI is really dependent on data, and you can't really do AI without good data.

[00:16:59] And then you have to secure it all, and you have to provide, you know, you have to get policies that ensure privacy and trust and so forth. So I talk about that less about security specifically and more about governance, which includes that, right?

[00:17:17] So when I say governance, I really mean security, policy, PII protection, that's personal information, bias checking, intellectual property checking, et cetera. And so, you know, earlier I talked about these four foundational success factors, trust being the first of them. And so what we actually did in IBM Consulting was, as we were building IBM Consulting Advantage, we actually built a software layer to do that governance.

[00:17:46] And it's powered by WatsonX, and WatsonX has a component called WatsonX.governance. And with that layer that we built, it did the security, the policy, the personal information protection, the bias protection. Every single assistant or agent that calls an LLM has to go through this layer. And that is absolutely essential if you're going to have an AI system that's trustworthy, that you believe in, that your employees believe in, that the users believe in.

[00:18:18] And you can, you know, deploy at scale and get people to come along with it. So, yeah, I mean, I think the governance is extraordinarily important. And in some ways, it's why it's the first of the four foundational things that I talked about. And I will diplomatically say that I think the consulting industry has traditionally been seen as a more conservative area of the industry. So how are you bringing a more agile software-driven approach to IBM Consulting?

[00:18:47] And as a result of being more agile, what kind of impact do you expect this shift to have on the client relationships and project outcomes? Because those days of, I don't know, taking a year or two years to get a project over the line is not going to cut it anymore, is it? It needs to be more agile. No, it's not going to cut it anymore. I mean, it's not only the consulting industry that has to change or the consulting industry is changing. Our clients as well, right? And the world. You said it, right?

[00:19:16] The world is moving way faster than it was before. You know, 30 years ago, you know, things took years to happen. Now they take weeks to happen. And so our world is moving faster. Our clients also realize that if they don't adopt new technology, including Gen.AI, their competitors will, and they can put them out of business. So our clients are very eager. You know, we were just talking about governance, right? And this will give you a sense as to how eager the clients are.

[00:19:45] So 75% of CEOs surveyed said that trusted AI is impossible without good AI governance, right? Okay, fine. But 39% of them said that they don't have good AI governance, and yet they're going to go ahead with Gen.AI, right? And so you think about that, and all of a sudden you realize that these clients really feel the pressure to move fast because they are worried that their competitors,

[00:20:11] some competitors are going to move faster and impact them. So as a result, the consulting industry, I think, has to move fast in how we evolve. And that's part of why we built IBM Consulting Advantage, because doing this one at a time is very hard. And with IBM Consulting Advantage, we can enable, you know, 160,000 of our consultants to be able to, you know, bring solutions faster. And it's not just, you know, higher productivity, but it's, like I said, it's speed.

[00:20:41] And with speed, it gives you time to work with the clients, you know, to think more strategically about how you deliver this. So as I said at the beginning, I really do feel this is a DVD to Netflix moment in the consulting industry. And we all need to seize upon it. And looking ahead with 2025 on the horizon now, I'm not sure how much you can share here,

[00:21:04] but is there anything you can share about some of the strategic priorities of IBM Consulting over the next year and beyond? And also, how do you see the company evolving and the kind of role that AI could play in even further shaping the future of the consulting industry? Yeah, I mean, I would say that, you know, our priorities are an extension of what we've been doing over the last year,

[00:21:29] which is to grow that $2 billion of Jenny and I book a business even faster and, you know, larger to really supercharge our 160,000 consultants with the 1.6 million digital workers. As I mentioned, you know, today we're not at that scale. People use them one at a time. They use them, you know, at various rates of frequency.

[00:21:56] And getting everyone to be able to productively use these tools is extraordinarily important. And then lastly, you know, we do this in order to deliver greater value to the clients, right? So if the clients aren't seeing greater value, of course, you know, we're not having the impact that we want.

[00:22:17] And that value really comes from the, you know, increased productivity, increased speed, and increased time with the clients to think strategically. And clients are expecting this, right? As I quoted before, 86% of clients are expecting consulting companies to come with these kinds of Gen.AI tools, pre-built technology assets.

[00:22:47] You know, they're expecting this kind of efficiency speed in being able to get things done. And we've spoken a lot today about your work and also your vision for IBM consulting and indeed the pace of technological change and how it's only going to get faster and faster.

[00:23:08] And as somebody that's helping leading the way here, on behalf of every business leader, I've got to ask this real pressure that we all feel of being in a state of continuous learning. Where or how do you self-educate? How do you keep up to speed to enable you to lead the way? Any tips you can share there? Yeah, yeah. No, this is a really important question, right? Because, I mean, when I left college 30 years ago, there were neural networks. There are still neural networks today. But they're so different.

[00:23:36] And if you don't continuously learn, you know, you fall out of a step very quickly. So, you know, I mean, I do what a lot of people do, which is I read a lot. You know, I read nonfiction. Like right now, I'm reading The Geek Way. Of course, you know, publications. I try to also, you know, read fiction, right? So, I'm reading a science fiction book called The Rowan.

[00:24:02] And, you know, I also try to continuously learn on a hands-on basis. So, I use IBM Consulting Advantage, which is our platform, to learn how to build assistants and agents. And so, you know, I try to stay fresh. Of course, I don't go out and build these things for our clients. But knowing how to do it, having been a software engineer earlier in my career, is helpful.

[00:24:32] Like it keeps you fresh, right? It keeps you learning. It keeps you relevant. And so, I think this is just really, really important in this world that we're in, you know, to be able to continuously learn. 100% with you. And for anyone listening, maybe they want to find out more information about what we talked about today. I know IBM Consulting is a huge website. If there's anywhere in particular you'd like to point them there or how they can connect with you or your team. Anywhere you'd like to point everyone listening?

[00:25:03] Yeah. I think you can go to www.ibm.com slash consulting and find out all of that. Excellent. Well, I'll add a link to that to make it nice and easy for everyone listening. And we covered so much in our conversation today from how AI is changing the consulting industry, why an open ecosystem approach is so essential for businesses to unlock AI across the enterprises.

[00:25:30] I also love how you're brought to life with so many valuable real world stories of top generative AI use cases. Hopefully that will be valuable for people listening, still trying to navigate their way around this, but also really shining a light on the importance of upskilling talent in the age of AI to unlock access to opportunities. So many big talking points. Love to hear from everybody listening on what they're experiencing right now. But, Mohamed, just thank you for sharing your story today.

[00:25:58] Well, Neil, thank you so much for having me on the program. I think it's clear from the conversation we've enjoyed today that the consulting industry is undergoing somewhat of a profound transformation, one that's driven by AI, yes, but equally bold strategies. So if you'd like to learn more about IBM Consulting or connect with Mohamed's team, please visit ibmconsulting.com. But for you listening, what did you find most insightful from today's discussion?

[00:26:28] Show your thoughts with me. I'd love to hear from you. And you can email me, techblogwriteroutlook.com, LinkedIn, Instagram, X, just at Neil C. Hughes. Let me know your thoughts. We'll keep this conversation going. Other than that, I'll return again tomorrow with another guest, another topic about how technology is transforming our life, our work and even world. Meet you here, same time, same place tomorrow. But bye for now. Bye.

[00:27:00] Bye. Bye.