Leadingagile Blog The Nonobvious Line Between Business Agility and AI Readiness

What if we told you that the things that enable business agility in your organization, are the same things that enable you to deploy AI in a way that actually leads to better business results.Video TranscriptEric Flecher: That's what we're doing at la. We're making AI accessible, right? Because we are addressing the core fundamental first principle problems that have to be solved to bring these outcomes and these solutions into your scaled business operations.How We Help Our Clients Achieve AI ReadinessMike Cottmeyer: If you were at a conference and you said, Hey, I work at Leading Agile and I'm the AI data practice lead for Mike, and they said, oh, tell me more. How would you talk about, you have two minutes or something like that, or maybe it's even pier than that. How might you describe what we're doing for companies in the AI space?Eric Flecher: We're making AI accessible, much like those, that mobile experience I shared when I was doing a lot of mobile work for enterprises, we would get called in, Hey, a lot of excitement at this business layer, the leadership layer, the individuals that are deciding these strategies and purchasing and bringing teams in to help. And then there would very quickly be a false summit because then they realize the second they get to the spreadsheet of the really cool things they want to do, they realize they can't get to those things because of technical debt, because of organizational structure, because of compliance burdens, whatever it may be. And there's this, it's kind of that trough of disillusionment that we see in these hype curves. And what I would say is that's what we're doing at la. We're making AI accessible because we are addressing the core fundamental first principle problems that have to be solved to bring these outcomes and these solutions into your scaled business operations.And then we're making it so that you have a cycle, a feedback loop, so that you can size and focus on the things that matter. Going back to that two by two that we referenced earlier, there's a lot of things an organization can do with AI and data, but there's also a lot of things on that list they shouldn't do. They have unique data sets that might be proprietary to them. They have unique knowledge that might be proprietary to them, and they have a marketplace that they've carved out where they've created a business. We need to go through a reductive exercise to figure out what you don't do and where do you focus so that you could utilize the best of these tools to put you in a position that is unique in the market that is defensible, and you don't want to invest work in areas where when the next model comes out or the next SaaS platform comes out where all that work evaporates because somebody else can just do it better because they found that niche and they exploited that niche better.Mike Cottmeyer: One of the ways that I took leading Agile to Market, it was kind of around this idea of why Agile fails and what you could do about it. And so what I could do when I walked up to somebody is I could say something to the effect of, tell me what your experience with Agile is or something and they would say, oh, it's going well, or it's doing this and whatever, and we're making progress. And I go and I just knew all the problems that they have. I knew the pain that they were experiencing. They were doing process first transformation. They were doing culture first transformation. I knew in my bones that the problems they were having were teaming strategies. I knew they were having problems with technology encapsulation. I knew they were having problems with over orchestration and lack of clarity and all the cognitive load that we talked about. And so if you put that in the AI lens and you walk up to somebody, what's the pain they're experiencing? How would they experience that pain? How could you connect to that pain, just pain they have? How are they experiencing the pain of not doing this the right way maybe is what I'm hunting for?Eric Flecher: Well, chances are they've probably experienced similar pain, but in a smaller, let's say dose with their previous technology initiatives when they're trying to create some sort of new product or system, there was probably an opportunity or there was probably an experience where they asked for X but they didn't get X, they got something different or they got less than that.The Challenges of Technology Extraction and Process ModernizationMike Cottmeyer: So one of the things I've characterized leading Agile as over the last couple years as we've really refined our methodologies for doing enterprise transformation is we're really a technology and process change management organization. The idea is to be able to make these changes quickly and systematically, predictably in a way that is connected to business value. So a lot of our methodologies really come into a generalized change management framework for technology extraction and business process optimization. What are the barriers that you see in companies to introducing this kind of change?Eric Flecher: The barriers, some obvious barriers that come out first of all would be around making sure that when you set up a team to work on a set of initiatives that are focused around business outcomes, that is the interesting intersection where the opportunity lies. Because what you're actually asking of your organization is to be able to operate with a lot of polyglots, someone who's a business matter expert, who understands that industry better than folks outside the organization, but wells inside the organization, these folks that have the intuition and the knowledge of how that industry works and how to create value within it. You're intersecting that with all these other technical disciplines. Now you're basically saying that person also has to understand the raw materials that go into that and how you deliver through technology. Because every business out there, whether they say it or not, needs to have technology into it to how they deliver.But you're bringing now those technology concerns up into the business layer where there used to be a separation where you say those folks are over in IT making sure my database is up and running and my APIs are available. You're now bringing those people and those decisions, strategy, technology, prioritization much closer to the business problem, which is what we want. We don't want distance between these things, but to do that requires right now individuals, leaders, managers, product managers, analysts to be able to understand these other spaces that they were traditionally walled off from and make decisions at these intersections to be able to prioritize work at these intersections and to not create additional debt, whether it be a business debt, bad decision on a strategy or a technology debt, bad decision on how you architect or organize your data For examples. These things all need to be done in unison kind of as an orchestra. All the instruments need to be playing together now conducted by a orchestration strategy around these business domains and domain division design.Mike Cottmeyer: A partner of ours said about a year and a half ago to me, and it really stuck in my head, is that this move to AI is going to force digital transformation to become real. And what I think he was really saying in that is there was a lot of space for technology leaders to move to the cloud or do other modernization initiatives and claim victory and say, yeah, we're digital, but this next wave of digital transformation is really about we have to get these systems optimized and aligned so that they're solving business problems in a much more rapid way. I don't know any thoughts on that comment?Eric Flecher: Yeah, I think we can look at the history, some history, some near term history and learn from that. So back to the mobile example. So when the first set of enterprise mobile apps came out, there were mostly marketing driven, flashy, interesting, and fun. Then the next phase of these apps came out where you started connecting them or seeing them connected to different business processes. Maybe I can go online and buy something on my mobile app, but I couldn't do that on the website or I couldn't carry my cart from my mobile app to my website in a journey that omnichannel journey. So if you look at retail 10 years ago, they had to go through this realization and start to rethink their organization in terms of how you deliver value using technology through the surface and the channel of technology. So they do, they started building different types of channels, both crafted for the internal employee, the backstage operations, as well as the front stage operations that interfaced with customers, but they ran the constraints, the inventory of how you manage your stores.If I am a retail organization, selling TVs might be different than the inventory management systems that's running my e-commerce system. And if I have a mobile app and a website that needs to have access to each of these things and I want to go buy something and just get it delivered to my house, how do I do that? So they started interfacing and creating open API infrastructure. Then they started making continuous experiences across these because now you have APIs set up and I have access to data. Now I can start to build craft experiences that are forced around business functions and outcomes. Well, even those became transactional because now the business realized you can do these things and there's a lot of value in delivering these solutions. But the question came about, wait a minute. Well, if I have an e-commerce solution and a warehouse in the middle of the country and I have individuals buying products that are located on the other side of the country or that e-commerce warehouse, why don't I just deliver from the stores?So now I have to unify inventory management and I have to figure out how to reconcile thos