Powering AI Transformation Through Ecosystem Partnerships

How are strategic ecosystem partnerships driving successful AI transformation for enterprises worldwide? 🌍

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At The Six Five Summit, host Tiffani Bova is joined by IBM's Kareem Yusuf, Ph.D, SVP, Ecosystems, Strategic Partners & Initiatives for a conversation on Powering AI Transformation Through Ecosystem Partnerships. Kareem dives into the critical role of partners in driving AI success for enterprises, highlighting the importance of strategic collaborations for accelerating adoption and innovation in the AI sector.

Key takeaways include:

🔹Partners as AI Transformation Catalysts: Explore the increasing reliance on partners to bridge crucial AI readiness gaps and deliver tangible ROI for enterprises navigating the AI landscape.

🔹Defining and Measuring AI Success: Delve into the key metrics that truly define AI success in today's dynamic business environment, moving beyond mere implementation to measurable impact.

🔹Real-World Impact of Collaborative AI: Discover compelling, real-world examples that illustrate how strategic partnerships are effectively fueling AI innovation and driving significant breakthroughs for businesses.

🔹Seizing Untapped AI Ecosystem Opportunities: Gain foresight into the vast and significant opportunities that lie ahead within the burgeoning AI ecosystem, along with actionable insights on how partners can help enterprises seize these upcoming possibilities.

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Learn more at IBM.

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Watch the full video at Six Five Media, and be sure to subscribe to our YouTube channel, so you never miss an episode.

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Or listen to the audio here:

Tiffani Bova: Hi, everyone. Welcome to The Six Five Summit: AI Unleashed. For this Channel Ecosystem Spotlight, I'm joined by Dr. Kareem Yusuf, SVP ecosystems, strategic partnership, and initiatives at IBM on powering AI transformation through ecosystem partnerships. Welcome to the show, Kareem.

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Kareem Yusuf Ph.D: Thank you so much for having me.

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Tiffani Bova: I'm so excited to have this conversation because I think you've got such a unique perspective. Not only within obviously IBM's ecosystem, but just from your experience running and leading products at IBM as well. I'd love to just understand from you, at least from your perspective, what are the key drivers for enterprises turning to partners to implement all that AI is now bringing to bear, the solutions and the outcomes that you are developing at IBM?

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Kareem Yusuf Ph.D: Well, I think if you think about how AI gets consumed, there's what I would call two main vectors. There's the actual implementation of an AI project, typically embedded in some kind of business process that might lead one to then consider what I could call here AI platform tools. In our context, that would be something like Watsonx Orchestrate, and you're building agents and the like and embedding them and integrating them with business processes. Then the other vector is you're just consuming software or technology that in itself embeds AI. I'll just use another IBM product, just to give that context. Think about IBM Concert, which is all around application resiliency. It uses an AI engine to figure out what's going on with applications within the IT space. When you take those two vectors and you think about it from a partner perspective, we have partners, what I call service partners, who are doing work in implementation around these AI platform technologies. We also have partners who are building new solutions where they're embedding engines within them, such that that AI is powering new capabilities that a client is then consuming. That's really the two vectors in my mind of consumption, or at least the two major ones and how that manifests.

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Tiffani Bova: Yeah. I think there's gaps in AI readiness at the customer level or the end user level that partners are uniquely positioned to solve, especially as everyone is struggling with the fact that there isn't people out there with 10 years of agentic AI experience that they could go and hire. The investments IBM is making to help the ecosystem be ready for these AI transitions and capabilities because customers are a little bit light on the capabilities internally.

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Kareem Yusuf Ph.D: Yeah. I think of three primary threads you could pull there. When you think about AI projects, first of all, there's the base statement of skill. As you said, partners, the ecosystem, everybody getting skilled up and being able to provide skilled resources is important. When you think about AI in and of itself, a big conversation is around data and data readiness. There's a lot of focus with partners working on the data problem. Is it data cleansing, data quality, data aggregation within data lakes, that kind of stuff? That's obviously a big vector of work. Then of course, you've got the AI applications or solutions themselves. I think a particularly unique aspect to that that intrigues us a lot is all around being able to take partner-created content and flow that into the solution context itself. That's why in our world, we've announced as you well know, a couple of weeks ago, our what's next Agent Connect program where agents that partners are building can be carried within our Orchestrate catalog and linked into solutions. Yeah, you're right. That's just how partners find different ways to begin to engage and build through, always starting with skills.

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Tiffani Bova: Can you walk us through a real world AI use case where the collaboration between an ecosystem partner and a provider really led to some good, I don't want to say good, demonstrable ROI I should say?

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Kareem Yusuf Ph.D: A nice easy one to use, you'll hear us talk a lot about the realm of HR or the realm of procurement as great domains for looking for these kind of outcomes. But the way I would baseline it is often, what is the core outcome that folks are looking for? I would contend it's really all around productivity. It really is around efficiency in terms of execution of key processes. That speaks to how much work you can get done with how many people, so you can easily scale up and stuff. That's why you often find examples of AI projects sit in the realm of customer service, or HR, or procurement, because they all reflect critical business processes that could obviously benefit from this. But if I was to walk you through it, any one of these projects, stick in the realm of HR there, involves a couple of systems. 

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You've got the systems of engagement. Where is the actual work occurring from? Is it from a webpage, is it from your productivity tool of choice, your email inbox? You've got systems of record, read those as various HR systems. Whether it's employee systems, whether it's job hiring systems. And you've got what I would call the plethora of additional support and data sources and environments that might be relevant to the process. Think about hiring in HR and think about integrations with things like a LinkedIn, for example. When you think about these processes, and I always like to use the word processes because you're really talking about steps of execution that are required to do real work. All real work involves a number of tasks coming together with decision points being made as you move from task to task. 

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These tasks typically span, as I just illustrated, multiple systems. When you think about it from a partnering perspective, there's lot of integration points. There's the big partners who own some of these big endpoint systems. What are they doing around AI? What agents are they embedding within their systems? How might these agents interact with each other, interoperate? There's what data do you need to access, how do you connect to them. How do you bring and orchestrate this all within context? There's the clear understanding of the core professional themselves, the domain. What work are they trying to do? What brings value to that work? Sometimes it's aiding the decision points, sometimes it's rapidly automating a set of tasks so that they're done quicker and allow them to move onto the next, and the next. That is really how I think about it when I bring it to life. For some of those listening or watching at the moment, you'll find this kind of familiar. These are the discussions we had back in the days when we were talking about application integration, business process management, business process re-engineer, business process automation. These are all still the same context of doing work. That's why you hear us talk about putting AI to work, AI for business because it's really just taking these technologies and leveraging them to really allow us to evolve and advance key critical processes.

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Tiffani Bova: Because of that, do you think that there's an opportunity for a new, and I know you're a big proponent of this, a new partner type or persona because of what you just walked through? There's a little systems integration, ISV, professional service systems integrator. We could go on, and on, and on at the various ecosystem partners that you pay attention to from a persona standpoint. Do you feel like there is a new partner type that may potentially become an offshoot of a current persona, a combination of one or two of them? Or net new, think back to that born in the cloud partner that popped up. It wasn't someone who was a resale partner historically that now has moved to the cloud. It was someone who just started a business from scratch. A new partner who is agentic or AI-driven and born from, versus learning it, if you will, as part of their other business.

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Kareem Yusuf Ph.D: The traditionalist in me would actually quantify that as I see instantiation of new partners coming from new backgrounds and emerging from existing and merging, and creating new conglomerates. I don't know whether I really think about it as new partner types as in completely different archetypes. Because when you actually baseline it, the work becomes familiar and similar. But what I do think we're going to be seeing is the combination of these tasks within what might have been siloed partners. "Oh, I just do service systems integration." No, they're going to be actually acting as ISV partners or build partners as they generate these critical assets, these agents themselves, and try to repurpose and leverage these agents across multiple projects. Or encapsulate critical value that they can now begin to resell. I do see an emerging of the, if you like, ISV from many more quarters than how you would have traditionally thought about it. Yes, I do see the service partner going in that direction.

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I see the ISVs themselves beginning to really think much more deeply around what does an ecosystem look like? Especially when you're talking about an ecosystem of interacting applications, if you like. I'll use the word applications here to reflect agents.A typical sidebar conversation I was in this week. When you think about integrating and APIs, we have all these notions of, oh, we know how to call these various applications. We've got the data structures and the stuff that we use. The good old [inaudible 00:10:22] IT stuff. When you think about interoperability within agents, it's not quite the same. You actually probably talking to the agent more like you're talking a human being. Because think about interacting with an LLM, the notion of prompts. It's actually conversational set pieces. What does implementing that in today's world look like? What does that mean for the ecosystem you build, and as you said, the skills that make it up? How do we actually govern and ensure we understand what is happening in this kind of world where agents are speaking to other agents to leverage tools and trigger off? It's quite, I would say, heady stuff.

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Tiffani Bova: Yeah. I get all excited about it because I feel like, for the ecosystem partners primarily, I always try to inspire them, if you will, or nudge them along to become client zero on their own. How are they going to deploy agentic and some of these capabilities you were just outlining in their own business? So that they can learn where those handoffs happen and the opportunities for them to maximize the return, the ROI. Then even potentially, what KPIs that they're using in their own business to say, "Are we doing better because of this? Have we over-complicated things? Is it allowing us to scale faster?" Which I know you're a huge fan of the term scale. If a partner is listening to this and is like, "Yeah, I'm all in," where do you think you would suggest they start maybe on their own internal client zero journey, so that they can start to become more familiar to how do they apply this to customer?

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Kareem Yusuf Ph.D: I think it's really important to emphasize that point you just made. I fundamentally believe that you cannot participate meaningfully in the world of agentic AI without being a user of agentic AI yourself. It's not like the other days where you could master a tool, but never really had to implement the tool within your own enterprise, or company, or environment. It's just not the case. You're going to have to be a user. Back to your point of where do people start or partners start, I think there's some obvious entry points. Clearly in the world of software development or writing code, we're seeing a lot of adoption of AI assistants, code assistants of various ilks and forms. As a productivity boost ... Which by the way, I will be honest with you, when this journey began, I thought developers would be the ones to first push back and go, "Oh, no, I'm crafting this code. What do you mean LLM or AI can help me with that?" But they actually are some of the biggest adopters and embracers of the technology, especially in terms of the way it helps them take away some of what I would call the mundane and allow them to really fixate on the creativity that they're trying to do. Clearly developers using AI tools to improve their productivity and efficiency is key and central. That's a great starting point. Many a partner, I would always encourage them, if they've got IT staff, that's an obvious one. 

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The other one I would add into then is back to your what I call self-help. There's a reason why you hear people talk about "ask HR." Employee self-service, as an example, is one of the what I would call lowest hanging fruits for leveraging AI to have a meaningful impact and benefit. I may have used this example with you before, but let me just pick on one very basic illustration of what kind of value can be given, for which I have personally experienced as an employee. The good old favorite employee verification, salary verification. Now in truth, I personally have not had to do salary verification for a very long time until my son, college age, needed to rent an apartment and I'm cosigning on an apartment. I'm like, "Oh, I have to verify my employment and my salary. How do I even do this?" Because of what we've implemented on our technology in IBM, I literally just logged into the website, typed "need my employee verification." It asked me for who needed it, where else might I need it. It eventually generated the whole document, shipped it off to the realtor, put a copy in my own inbox. I'm talking about two minutes and make that two minutes me typing. This is a kind of productivity unlocked where you just totally changed how employees interact. I just picked two there, how your developers work with code assistants, looking at employee service, self-service. Great places to start and engaged with that technology.

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Tiffani Bova: Yeah. If I were to start a partner ... Well, let me say that differently. If you were going to start a partner company today, and then I'll tell you what I would do. But if you were going to start a partner company today, knowing all you know. If you're like Kareem's Magical Partner Company, what would that look like?

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Kareem Yusuf Ph.D: Well, I was going to gest and say it would all be built on AI. Obviously, we all have our bias. My company would probably be going down the world of building and deploying agents that interoperate with each other. I'm a product guy at my core. The notion of these agents and how they can interoperate and do meaningful work always sits close to my heart. I'd probably be working on creating agentic content. I'd be signing up for the what's next Agent Connect partner program. I would be building agents on Orchestrate and I would be getting out there to embed them in business processes. That would probably be the direction I, Kareem, would go.

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Tiffani Bova: Yeah. I would say sign me up. I agree because there's the next 100 million, or 50 million, or five million partner company one person. Not 100 or not 50. I don't want people hearing me say, "Oh, it's not about people." No, it's about humans and technology, not human alone, not technology. It's how can you maximize individual productivity and impact using all we now have at our disposal. I remember 15 years ago, I stood in front of, back then, IBM still had much more hardware than it does today. But if I was standing in a room full of hardware partners I'd be like, "If you were going to start a business today, how many of you would resell hardware?" It was interesting, not many hands went up. But yet, they were knee-deep in it.

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Kareem Yusuf Ph.D: But you know what they might do, they might focus on solutions that integrated hardware. My other favorite phrase at the moment is I call it storage with a purpose. You think about storage boxes, they don't just go hang out to store stuff. They're doing it with a purpose. Is it backup and restore? Is it an AI workload environment? Is it to support a data lake? You can begin to think, for example, of our hardware vendor could evolve themselves by just thinking about the purpose of some of that hardware to be more of a solution vendor. But I do want to double-click on your point about humans. Because as someone who has been steeped in technology for a long time, and in particular in AI in all its forms, I actually walk away with always in awe of how amazing the human mind is. Because people seem to forget that the creativity that, one, enables this stuff and then exploits this AI is actually human. When you think about any major technology shift that has occurred in society, go back whether you want the steam revolution, first time we did fire, industrial revolution, it's all given us the ability to be more creative. And bring new and interesting value to the market. I actually think that this is about to unlock a next level change in what we can do as individuals as we leverage, and embrace, and collaborate with these technologies. Which, by the way, we create. They're not creating themselves.

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Tiffani Bova: Absolutely. If you could do anything, that beginner's mind if you will, not the expert's mind of we've been here before, like you said. This is not just a replication of what we've seen in transitions, maybe to the cloud from on-prem. This is not a normal transition, most definitely in my opinion anyway, on the acceleration, how quickly things are happening. We saw each other four weeks ago. What we talked about is almost not even relevant because it's moved so fast.

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Kareem Yusuf Ph.D: The models that were top of the leader boards four weeks ago and are not the models today. Yes, you're right.

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Tiffani Bova: Right. So much partners can take advantage of. If someone's listening and going, "Well, I have reservations." Or I'm a little hesitant, or maybe I'm a little nervous or afraid of what this transition means to me, and my people, and my teams, and my organization. Leaning in, I always say, start with the customer. To your point, what is the purpose? What is their outcome and what they trying to solve for? How can you do that in a more efficient way, leveraging now all that AI and technology brings to bear?

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Kareem Yusuf Ph.D: I would agree with you. Look, I think there's a reason why we've both been picking on that word efficient or productive. It's one vector. Are there others? Probably. But it's a very tangible vector. It's a good way to get focused on driving towards meaningful outcomes. There is absolutely nothing to be afraid of in my mind, there really isn't. But lack of fear or addressing your fear comes with familiarity. Get stuck in. Play around with these tools. Figure out how to use them collaboratively. To benefit, as you say, your own work and then the work of what you're going to deliver for others. I think that's just core and essential to it. These things often, in my mind, reduce themselves back to some pretty basic patterns. I would echo your words. This is really an exciting and fast-moving time. I don't think we've actually figured out all the ways we're going to leverage this stuff for real meaningful advantage. We're really at the early innings.

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Tiffani Bova: Well said. Look, as we wrap up our time together, I'm going to end on two rapid-fire ones, if you don't mind. The first one is what's one misperception about AI ROI that you'd love to bust?

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Kareem Yusuf Ph.D: AI ROI I'd like to bust? Misconception. Oh, jeez, you caught me off guard on that one.

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Tiffani Bova: Oh.

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Kareem Yusuf Ph.D: I don't know whether I'd call this a misconception. I think the thing that people do not understand about AI ROI is that it actually boils down to very meaningful, simple metrics. Can you do something faster, better, quicker than you could before? I think the misconception, in my mind, is people over-complicate AI ROI. They really do, they over-complicate it and they shouldn't.

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Tiffani Bova: All right. The last one. In one sentence, this might be hard, but in one sentence, what makes a great AI partner?

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Kareem Yusuf Ph.D: Knowledge, skill, domain, and understanding.

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Tiffani Bova: That is just, I think that's great. Not a sentence, but three great words. I love that, Kareem. Well, thank you so much for joining us for this Channel Ecosystem Spotlight at The Six Five Summit. Stay connected with us on social and explore more conversations at sixfivemedia.com/summit. More insights coming up next.

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Disclaimer: The Six Five Summit is for information and entertainment purposes only. Over the course of this webcast, we may talk about companies that are publicly traded and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors, and we ask that you do not treat us as such.

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