3108: How IBM Consulting is Driving Generative AI Innovation

[00:00:03] How is AI reshaping the consulting world? And what does it take to build a truly transformative

[00:00:10] approach? Today I'm joined by Mohamed Ali, Senior Vice President of IBM Consulting. And

[00:00:18] he has a remarkable background in cybersecurity, data and AI. But he's now spearheading a new

[00:00:25] era for IBM Consulting. But he's now spearheading a new era for IBM Consulting. One that blends

[00:00:32] innovation with real world application. So together we're going to explore how AI is unlocking

[00:00:39] enterprise opportunities, why an open ecosystem is critical, and what it means to upskill talent

[00:00:47] in the age of generative AI. But enough scene setting for me, let's get my guest onto the

[00:00:53] show right now. So a massive warm welcome to the show. Can you tell everyone listening

[00:00:59] a little about who you are and what you do?

[00:01:03] Yeah. Hi, Neil. So first of all, thank you for having me on the show. I'm Mohamed Ali.

[00:01:08] I'm head of IBM Consulting.

[00:01:10] Well, it's a pleasure to have you join me today. And I was reading before you came on the podcast

[00:01:14] that you've recently rejoined IBM after leading roles at IDG and Carbonite to name a few. But

[00:01:21] you're now bringing this fresh perspective to IBM Consulting. So I've got to ask, what changes

[00:01:27] are you implementing to maybe reshape the traditional IT consulting services industry? And how is your

[00:01:34] more software-driven mindset maybe influencing this transformation?

[00:01:39] Yeah, thanks for asking. I think you're right. You know, this whole consulting market requires a

[00:01:45] fresh perspective. And I did start my career, had a big part of my career at the beginning at IBM.

[00:01:52] And then I left for 14 years. I was CEO of these two companies that you mentioned,

[00:01:58] which are smaller. And so, of course, you can move faster and you can be much more nimble.

[00:02:03] And in some ways, you know, that's what I'm trying to bring to IBM Consulting. We're 160,000 people

[00:02:10] in IBM Consulting. So, of course, it's not quite as easy. Having said that, I think that our industry is

[00:02:19] going to be changing quite fast. As you know, our world is changing quite fast with Gen AI and other

[00:02:24] technologies. And for me, I see this as what I call our DVD to streaming moment. You know,

[00:02:31] those of the listeners who are familiar with Netflix, Netflix went from DVD to streaming and it transformed

[00:02:38] that company. And that is happening in our industry as consulting goes from labor only to labor plus

[00:02:45] AI powered software. And that combination is really changing our world. So, we've actually moved

[00:02:52] extraordinarily fast, probably one of the fastest times we've moved in IBM. And a couple of data

[00:02:58] points, we now have over $2 billion worth of book of business around Gen AI. And in order to do that,

[00:03:06] we actually had to build a software platform within consulting. We call it IBM Consulting Advantage.

[00:03:12] And we've now deployed that at scale. And it's probably one of the best platforms of its kind

[00:03:17] out there. So, you know, we've had to do a lot of this in the last 18 months. So,

[00:03:22] it's actually been kind of a remarkable change in the company at a very fast pace.

[00:03:29] And I've been going to a lot of tech conferences the last few years. And predictably,

[00:03:33] AI is the big talking point. It'll probably continue to do that next year as well. And

[00:03:38] it's changing so many different industries at the moment. But I'm curious, how are you seeing AI

[00:03:43] changing the consulting landscape? And in what ways are you at IBM Consulting also leveraging AI to

[00:03:50] transform things like client engagements? And how do you ultimately see the role of consultants

[00:03:57] and the role of consultants evolving with the rise of these generative AI technologies? I appreciate

[00:04:02] it's probably about five or six different questions in there. But what are you seeing?

[00:04:06] Right. Yeah. So, you know, we've actually developed a term for this now. We're calling

[00:04:11] it the science of consulting, where skills and expertise are coming together with science and

[00:04:17] technology in a way that it's never really, you know, come together before. And the way we

[00:04:24] implement that is by supercharging, that's a term we use, are 160,000 consultants with 1.6 million

[00:04:35] digital workers. What does this mean? You know, today, if you use an assistant,

[00:04:40] a Gen AI assistant, you can only use it one at a time, right? So it's, you know, so 160,000 consultants,

[00:04:46] you have 160,000 of these assistants. But we've recently introduced agents. And so you could

[00:04:51] actually launch an agent to work for you, and another one, and another one. So, you know,

[00:04:57] at some point, you'll be able to launch 10 of these things simultaneously. And so this is,

[00:05:02] you know, this is sort of the how we're implementing the science of consulting. And that's having,

[00:05:08] you know, already sort of remarkable effects on how we're delivering for our clients. And, you know,

[00:05:15] clients are actually almost demanding it now. There's a study that said that 86% of consulting buyers

[00:05:21] are actively looking for services that use Gen AI or some sort of technology asset. And so the clients

[00:05:28] are demanding it, and we're actually, you know, using it in our projects. And in some cases,

[00:05:35] we're seeing some significant productivity gains, sometimes up to 50%. But it's not just productivity,

[00:05:41] this allows us to go faster, it allows us the time to actually engage the client and have strategic

[00:05:48] discussions. And so one example of that is at Riyadh Air, where they're building a whole new airline from

[00:05:57] scratch to rival Emirates and those types of high-end aircraft, airlines. And what they're doing

[00:06:05] is instead of using sort of, you know, train ticket technology, which most of the airlines sort of

[00:06:11] use today, they're using a shopping cart experience like an Amazon. And it's a, you know, they're

[00:06:17] imagining everything. And that's just one example. And so because we're using this consulting advantage

[00:06:22] platform, we have about 70% of our engineers are working on this project, doing it on consulting

[00:06:28] advantage, they're able to do it faster. So, you know, they have more time, because in a project like

[00:06:33] this, that is brand new, and you're sort of constantly changing, it's important to have extra time for

[00:06:40] this project. So we're actually at a schedule, we're able to work with a client on some of these

[00:06:45] strategic things. And, you know, the outcome is actually quite a bit better. So, you know,

[00:06:51] to answer your question, there's actually a lot of change happening in the consulting industry very

[00:06:56] quickly.

[00:06:57] And something else that stands out for me is an open ecosystem approach has always been the focus

[00:07:04] for IBM. So why do you believe that is essential for businesses looking to fully unlock the potential

[00:07:11] of AI across the enterprise? And how do you think that is different from IBM's consulting strategy for

[00:07:17] more closed proprietary models? There are two opposite ends of the scale there, but

[00:07:21] why do you think it is so important?

[00:07:24] Yeah, Neil, I'm glad you asked that because, you know, there was a time in history when you got

[00:07:30] all your technology from one company. And IBM was one of those companies that deliver that, right?

[00:07:36] And I would say, you know, the last few decades, IBM's moved away from that to an open approach,

[00:07:42] because in order to deliver the best solutions now, you have to combine technologies from multiple

[00:07:50] vendors. And so in consulting, we have some very deep partnerships with Microsoft, AWS, SAP, Oracle,

[00:07:57] Salesforce, Adobe, Palo Alto, which is some of the leading ones that, you know, we have truly embraced

[00:08:04] and been bringing to market in order to build these great solutions for our clients. But with Gen AI,

[00:08:11] each one of these companies I just mentioned have brought Gen AI technologies. Of course, Microsoft has

[00:08:16] a large suite, AWS as well, SAP, Oracle, Salesforce has now Agent Force, Adobe has Firefly, Palo Alto has

[00:08:25] precision AI. And so what we've done is we've actually integrated these into our delivery platform,

[00:08:32] IBM Consulting Advantage, so that when our 160,000 consultants need to use Gen AI, they have Gen AI

[00:08:40] free integrated, they can move faster. When our clients want to use these technologies, they can

[00:08:45] move faster. So yeah, I really believe that this sort of open approach is extraordinarily powerful.

[00:08:52] I just give you two quick examples. Sure. At Valle, which is a one of the world's largest

[00:08:57] mining metals company, you know, in order to secure the company, we started with Microsoft security

[00:09:04] technology, and then we added our AI power threat detection services and elements to that. And so by

[00:09:15] having these things pre-integrated, we're able to move very fast. In our public group, which is an

[00:09:20] advertising company, they wanted to move from an x86 data center into the cloud. And since we already

[00:09:29] had a really great work relationship with AWS understood their technologies, we were able to

[00:09:34] take the SAP workload and move it to the cloud where they were able to see about 20% improvement in the

[00:09:41] performance. And in part, because we're taking this sort of asset-based Gen AI approach where things are

[00:09:49] pre-integrated so we can move quicker. And generative AI has captured widespread attention, but I've spoken

[00:09:57] to so many business leaders over the last few months that they're still trying to find the right use

[00:10:02] case for their business. And many are struggling to find ROI from some of those projects that began

[00:10:08] maybe with a tech first rather than problem first approach. Just to focus on this a little,

[00:10:15] are there any use cases that you're seeing across industries that you can share and how IBM consulting

[00:10:22] is helping clients harness these innovations to solve these real world business challenges and get

[00:10:28] that ROI? Yeah. And Neil, you're so right. I mean, all this new stuff comes to market and everybody

[00:10:35] wants to play with it, right? So it's all, you're right, it's tech first. But, you know, it took to

[00:10:40] really actually get the scale, it really needs to be sort of a use case first. And we're really seeing

[00:10:49] Gen AI being deployed in three big buckets and probably top of the list is customer service.

[00:10:55] Then the second is writing code, right? And doing application modernization, that sort of thing

[00:11:02] called general productivity. I'll give you a couple of examples. So, you know, customer service,

[00:11:08] it's maybe what you expect, right? You know, there's a healthcare company we're working with

[00:11:13] and we've been able to help them deflect about 30% of the calls that are coming in. They probably get

[00:11:21] about, you know, for a million calls or customer inquiries. And then you say, okay, well, if you're

[00:11:26] using technology to deflect calls or to handle calls, maybe the customer set goes down. It actually

[00:11:32] is the opposite. The customer set increased by 40%. Another kind of customer service that one of my

[00:11:40] favorites, then 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,

[00:11:55] we were able to get this hospital group to see 700 more patients per week with no additional doctors,

[00:12:04] no additional nurses, no additional staff, which is just optimizing and staying engaged on a kind of

[00:12:12] a customer service basis to make sure that, you know, people show up as schedules change,

[00:12:18] things get aligned. So it was a really, really great customer service example.

[00:12:22] So writing code, we've been able to, there's a beverage company we've worked with where we saw

[00:12:28] 95% reduction in the effort to write Ansible code. That's kind of an unusual case, but there are cases

[00:12:36] that are really significant like that. And then in general productivity, you know, we work with a

[00:12:41] company where their procurement department was able to process 98% of their spend through these

[00:12:49] automated system and they save $40 million. So I would say, yeah, those are sort of the three

[00:12:54] big buckets we're seeing customer service, writing code and general productivity.

[00:12:59] Some great examples there. I love your UK example. It is notoriously difficult to see a doctor or get a

[00:13:05] doctor's appointment.

[00:13:06] That's right. I mean, this is a big issue in the UK, right? All my UK friends say sometimes they have

[00:13:11] to wait a long time.

[00:13:12] Yeah. Yeah. Yeah. If you're so right, there's a whole other podcast right there, but I mean,

[00:13:17] one other topic is critically important right now is upskilling talent, especially when adopting AI

[00:13:25] at scale. And I think it's also important that AI enhances and complements human employees rather

[00:13:32] than replacing them. So a big part of that is upskilling. So how is IBM consulting investing in

[00:13:39] upskilling in your own workforce? And do you have any advice for any other organizations or business

[00:13:44] leaders listening that may be wanting to prepare their teams for this age of AI, but a little bit

[00:13:50] unsure on where they start?

[00:13:52] Yeah. I actually think this is probably possibly the most important piece of this, right? Because

[00:13:59] a lot of people go out and they do these proof of concepts and they really struggle to get to scale.

[00:14:04] And one of these, we've now done over a thousand of these Gen.AI projects. And one of these that we've

[00:14:11] noticed is that there are probably four foundational factors for success. Trust, flexibility, openness,

[00:14:17] and people first, with people first probably being the most important. So how do you think,

[00:14:21] you know, because if the people don't trust the Gen.AI, they're just not going to use it. And if

[00:14:27] they're not part of the re-engineering of the processes, again, they're not going to adopt it,

[00:14:33] right? So what we have done within IBM consulting is first, we've trained everybody on how to use Gen.AI.

[00:14:41] It's actually not that hard, you know, and to be quite honest, like everybody, a lot of people are

[00:14:47] using it all the time, but we've given them additional training. So we have about 70,000

[00:14:53] of the 160,000 that have very high level of Gen.AI certification. So you train people.

[00:14:58] And then we put them at the center of re-engineering our process. And we actually ran this hackathon

[00:15:05] with 158,000 people to get the team to help us figure out the processes they know, how can they

[00:15:14] improve them with Gen.AI. And it worked remarkably well, right? I mean, there's really incredible

[00:15:21] embracement of the technology and putting it to usage, real ownership. And so this change management

[00:15:29] is actually something that we have decided to make the kind of a core competence of IBM consulting as we

[00:15:37] work with clients, because if you can't bring the people along and you can't do the change management,

[00:15:44] none of this is going to work, no matter how good the technology is.

[00:15:48] 100% with you there. And I think I should also highlight, because I was doing a little research

[00:15:53] on you, that your expertise spans across cybersecurity, data and analytics, as well as AI. I don't want to

[00:16:01] get too carried away with just talking about AI, but I'm curious from what you're seeing here,

[00:16:06] how do all these areas converge and intersect in your work at IBM consulting? And why do you think it is

[00:16:12] important to approach AI implementation with a strong focus on data security, governance, and all those

[00:16:18] bouts and braces approaches to IT that we were raising?

[00:16:23] Yeah, I know. Thank you for asking. You know, when I graduated from Stanford, I helped start a neural

[00:16:29] network company. And I remember my mother asking me, is that a real job? I've never heard of a neural

[00:16:34] network. Now it's 30 years ago, and I guess now it's gone full circle. And in the interim, you know,

[00:16:41] about 20 years ago, I helped build IBM's data and analytics business before I left. And then one of

[00:16:48] the companies I was CEO of was a cybersecurity data protection company. But it all sort of comes

[00:16:53] 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

[00:17:05] ensure privacy and trust and so forth. So I talk about that less about security specifically,

[00:17:14] and more about governance, which includes that, right? So when I say governance, I really mean

[00:17:20] security policy, PII protection, that's personal information, bias checking, intellectual property

[00:17:28] checking, etc. And, and so, you know, and earlier, I talked about these four foundational success

[00:17:36] factors, trust being the first of them. And so what we actually did in IBM consulting was,

[00:17:41] as we were building IBM consulting advantage, we actually built a software layer to do that

[00:17:45] governance. And it's powered by Watson X. And Watson X has a component called Watson X,

[00:17:51] that governance. And with, with that layer that we built, it did the security, the policy that

[00:17:57] the personal information protection, the bias protection, every single assistant or agent that

[00:18:02] calls an LLM has to go through this layer. And that is absolutely essential. If you're going to have

[00:18:08] an AI system that's trustworthy, that you believe in, that your, your employees believe in, that the users

[00:18:14] believe in, and, and, and, and, and you can, you know, deploy at scale and get people to come along with

[00:18:23] it. So yeah, I mean, I think the governance is extraordinarily important. And in some ways,

[00:18:27] it's why it's the first of the four foundational things that I talked about.

[00:18:32] And I will diplomatically say that I think the consulting industry has traditionally been seen as

[00:18:37] a more conservative area of the industry. So how are you bringing a more agile software driven

[00:18:45] approach to IBM consulting? And as a result of being more agile, what kind of impact do you expect this

[00:18:51] shift to have on the client relationships and, and project outcomes? Because those days of, I don't

[00:18:56] know, taking a year or two years to get a project over the line is not going to cut it anymore,

[00:19:00] is it? It needs to be more agile.

[00:19:01] No, it's not going to cut it anymore. I mean, it's not only the consulting industry that has to change,

[00:19:07] but, or, or the consulting industry is changing our clients as well, right? So, and the world,

[00:19:14] you said it, right? The world is moving way faster than it was before. You know, 30 years ago,

[00:19:21] you know, things took, things took years to happen. Now they take weeks to happen. And so our world is

[00:19:27] moving faster. Our clients also realize that if they don't adopt new technology, including Gen AI,

[00:19:34] and their competitors will, and they can put them out of business. So our clients are very eager.

[00:19:39] You know, we were just talking about governance, right? And this will, this will give you a sense

[00:19:43] as to how eager the clients are. So 75% of CEO survey said that trusted AI is impossible without

[00:19:52] good AI governance, right? Okay, fine. But 39% of them said that they don't have good AI governance,

[00:20:00] and yet they're going to go ahead with Gen AI, right? And so you think about that and all of a sudden you

[00:20:05] realize that these clients really feel the pressure to move fast because they are worried that their

[00:20:11] competitors, some competitors are going to move faster and, and, and impact them. So as a result,

[00:20:16] the consulting industry, I think has to move fast in how, how we evolve. And that's part of why we

[00:20:22] built IBM Consulting Advantage because doing this one at a time, it's very hard. And with IBM

[00:20:28] Consulting Advantage, we can enable, you know, 160,000 of our consultants to be able to,

[00:20:34] you know, bring solutions faster. And it's not just, you know, higher productivity, but it's,

[00:20:40] like I said, it's speed and with speed, it gives you time to work with the clients, you know,

[00:20:45] to think more strategically about how you deliver this. So as I said at the beginning, I really do feel

[00:20:52] this is a DVD to Netflix moment in the consulting industry. And we all, we all need to seize upon it.

[00:20:58] And looking ahead with 2025 on the horizon now, I'm not sure how much you can share here, but is there

[00:21:05] anything you can share about some of the strategic priorities of IBM Consulting over the next year

[00:21:11] and beyond? And also, how do you see the company evolving and the kind of role that AI could play in

[00:21:17] even further shaping the future of the consulting industry?

[00:21:22] 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 I book a business even faster and, you know, larger

[00:21:37] to really supercharge our 160,000 consultants with the 1.6 million digital workers. As I mentioned, you know,

[00:21:47] today we're not at that scale. People use them one at a time. They use them, you know,

[00:21:53] at various rates of frequency and getting everyone to be able to productively use these tools is extraordinarily

[00:22:04] important. And then lastly, you know, we do this in order to deliver greater value to the clients,

[00:22:10] right? So if the clients aren't seeing greater value, of course, you know, we're not having the

[00:22:16] impact that we want. And that value really comes from the, you know, increased productivity,

[00:22:22] increased speed, and increased time with the clients to think strategically. And clients are expecting

[00:22:28] this, right? As I quoted before, 86% of clients are expecting consulting companies to come with these

[00:22:39] kinds of Gen AI tools, pre-built technology assets. You know, they're expecting this kind of

[00:22:49] efficiency speed in being able to get things done.

[00:22:56] And we've spoken a lot today about your work and also your vision for IBM consulting, and indeed,

[00:23:03] the pace of technological change and how it's only going to get faster and faster. And as somebody

[00:23:09] that's helping leading the way here, on behalf of every business leader, I've got to ask this real

[00:23:14] pressure that we all feel of being in a state of continuous learning. Where or how do you self-educate?

[00:23:20] How do you keep up to speed to enable you to lead the way? Any tips you can share there?

[00:23:25] Yeah, yeah. No, this is a really important question, right? Because when I left college

[00:23:30] 30 years ago, there were neural networks. There are still neural networks today,

[00:23:35] but they're so different. And if you don't continuously learn, you know, you fall out of

[00:23:40] a step very quickly. So, you know, I mean, I do what a lot of people do, which is I read a lot.

[00:23:47] You know, I read nonfiction. Like right now, I'm reading The Geek Way. Of course, you know,

[00:23:52] publications. I try to also, you know, read fiction, right? So, I'm reading a science fiction

[00:24:01] book called The Rowan. And, you know, I also try to continuously learn on a hands-on basis. So,

[00:24:08] I use IBM Consulting Advantage, which is our platform, to learn how to build assistants and agents.

[00:24:18] And so, you know, I try to stay fresh. Of course, I don't go out and build these things for our clients,

[00:24:25] but knowing how to do it, having been a software engineer earlier in my career,

[00:24:30] is helpful. Like it keeps you fresh, right? It keeps you learning. It keeps you relevant. And so,

[00:24:37] I think this is just really, really important in this world that we're in, you know, to be able to

[00:24:43] continuously learn. 100% with you. And for anyone listening, maybe they want to find out more

[00:24:49] information about what we talked about today. I know IBM Consulting is a huge website. If there's

[00:24:55] anywhere in particular you'd like to point them there or how they can connect with you or your team.

[00:25:00] Anywhere you'd like to point everyone listening?

[00:25:02] Yeah. I think you can go to www.ibm.com slash consulting and find out all of that.

[00:25:12] Excellent. Well, I'll add a link to that to make it nice and easy for everyone listening. And we

[00:25:18] covered so much in our conversation today from how AI is changing the consulting industry, why an open

[00:25:25] ecosystem approach is so essential for businesses to unlock AI across the enterprises. I also love how you

[00:25:31] brought to life with so many valuable real world stories of top generative AI use cases. Hopefully

[00:25:37] that will be valuable for people listening, still trying to navigate their way around this, but also

[00:25:42] really shining a light on the importance of upskilling talent in the age of AI to unlock access to

[00:25:48] opportunities. So many big talking points. Love to hear from everybody listening on what they're

[00:25:54] experiencing right now. But Mohamed, just thank you for sharing your story today.

[00:25:57] Well, Neil, thank you so much for having me on the program.

[00:26:01] I think it's clear from the conversation we've enjoyed today that the consulting industry is

[00:26:06] undergoing somewhat of a profound transformation, one that's driven by AI, yes, but equally bold

[00:26:13] strategies. So if you'd like to learn more about IBM consulting or connect with Mohamed's team,

[00:26:20] please visit ibmconsulting.com. But for you listening, what did you find most insightful from today's

[00:26:27] discussion? Show your thoughts with me. I'd love to hear from you. And you can email me,

[00:26:32] techblogwriteroutlook.com, LinkedIn, Instagram, X, just at Neil C. Hughes. Let me know your thoughts.

[00:26:39] We'll keep this conversation going. Other than that, I'll return again tomorrow with another guest,

[00:26:43] another topic about how technology is transforming our life, our work, and even world. Meet you here,

[00:26:51] same time, same place tomorrow. But bye for now.