Future of learning: AI demands a new 'idea economy' mindset

Welcome to the Built by People podcast, where we share the stories and insights of the world's top HR leaders. Join us as we dive deep into the minds of HR executives, uncovering their strategies, challenges, and triumphs in shaping today's workforce.

I'm excited to welcome Sean to the Built by People podcast. Sean, thank you so much for joining us. And as a starting question, I always love to ask if you could share a little bit more about your career journey.

Sure thing. I tend to break my career journey around 4 different phases, but at least a crux or a central sort of theme throughout it. But 4 phases, 4 verbs would be build, manage, consult, and lead. And my build phase is as an instructional designer, cut my teeth and learned the craft and a teacher. And during the manage phase, understood what scale meant and operationally how to basically solve problems at scale there. And at consult, I helped understand market problems and being able to solve within the industry, large organizations, understanding where they were headed and where the pain points there and certainly the challenges and opportunities in that. In that arena. And then finally, in the lead phase where I am right now, it is just understanding the operations and the organizational impacts of learning and development as it pertains to any size company, any size industry, even from academia straight up into corporate. So that phase, the owning the P&L, et cetera, et cetera. And so it's sort of around the area of being a lover of learning. So I call myself a self-proclaimed philematist.

Sean, can you tell us about a time where you leveraged technology to solve a significant challenge in talent development or L&D? What was the impact?

Yeah, sure. Lots of different ones you could go into, but the one that comes top of mind was a great opportunity at PwC to really dive in deep to their cybersecurity, their cybersecurity consulting practice. One of the challenges they had was just making sure that learning was specific to them, was personalized to them, or even use the word customized to them. And what was the biggest challenge was that if you're familiar with cybersecurity, it depends on a lot of certification. You have to prove that you know what you're doing before someone will give you the reins to their cybersecurity systems, access points, et cetera. You have to prove that you know that before you will win some business. So what we did was we put together a learning technology platform that aggregated both the external, internal certifications from various vendors, as well as added our own internal learning and development pieces to create customized playlists for each level and each milestone that a person in that practice would have to go through. Ultimately, it resulted in a large amount of RFPs that we were able to respond to because we were able to prove exactly who had which certification. At what point in time, and also it provides just a lens into someone's career journey where they could go to and a streamline point. So I, I always end on this point is that if anybody out there wants to solve a problem and wants to spin up a startup, one of the cool areas here is be a center node for Assert Central because it is definitely a challenge that hasn't been solved. We, we did a great job inside of PwC, but there are companies out there willing to pay for that type of solutions.

Sean, how do you incorporate human-centered design into training programs? And when you did that, what were some of the key takeaways from that experience?

Yeah, human-centered design is a fun place to play in, but the best places to go to with this is that always keeping the, both the learner and the business at the center. So you should always be falling in love with the question, what business metric am I moving with this? This learning problem, learning challenge, and then prototype carelessly, measure ruthlessly, and then share the credit generously. So in terms of human-centered design, always start with that sort of problem, asking the 5 whys, getting down to first principles, understanding that. So that's how you incorporate it. And in terms of what, like, human-centered design across the L&D spectrum, it can be broadly applied. Glad to give you specific examples, but that's from, to answer your question, on a general perspective, that's how we go at it.

Sean, can you tell us about a specific case where you successfully implemented a learning design strategy that improved engagement and performance?

Yeah, I think the best example I would have was my time at Accenture. And if you can think of it, this is before the days of LinkedIn Learning and when Skillsoft's content library was out there and when Lynda.com was there prior to its acquisition to LinkedIn. What we tried to do at Accenture Academy in the same business model, but in hyper-focused competency areas, capability areas like supply chain training and finance training and sustainability training and digital transformation training, basically a catalog of those content. But where the design principles came in and strategy came in was being able to apply a broad level of a mix of design systems into that business model and those products. So In other words, what does it look like when instructional design meets visual media design meets technology and UI/UX design and then wrapper around that human-centered design? What does that look, what does that feel like? And could we create a brand around Accenture Strat— Accenture Academy, excuse me, that would not only be recognizable, but also deliver. And so with the design strategy in mind, we were able to apply that to at least 500 assets that we had, learning products, learning solutions, and across various different forms. And with that in mind, we were able to move the needle not only from a, let's say, a product sales standpoint, but also from a capability and competency development standpoint, with each one of those things being aligned directly to a specific role and competency/skill at a specific level.

Sean, can you talk to us about a time when you leveraged technology to enhance the learning experience for employees?

Oh yeah. Recently in a former role, and this leads into the AI conversation even more, is that we were able to provide a foundation for what we thought was simple, just file management, file storage moving. But if you think about how the knowledge worker actually works today, it's through information captured in files, whether that's Microsoft 365, whether that's Google Workplace, et cetera, et cetera. But everything that we know or everything that we are referring to the job also is captured in those documents that we refer to on constant basis. Who has these pieces of information? How do I do my job? Where is this thing located? What's a template or example that I can use to keep on going? What's the process or procedure, et cetera? So what I'm getting at is this, is that by moving things to the cloud, what was once network drive, shared drives, now moving to the cloud, which is more like SharePoint, Google Drives. But what we can do now and was the accidental understanding of if you create a well-formed information graph or knowledge graph around knowledge management and you have a strategy there, now it becomes, instead of a knowledge management strategy, it becomes an intelligence management strategy where AI layers can be placed upon it. So what we discovered, a wonderful discovery, was less about how do we find the right information at the right time, but rather what types of questions are answered with that information. And with AI, let's call it LLMs layered on top of it. And you're, whether it's Gemini with Google or whether it's OpenAI as something that is a layer on top of it, or whether it's using a tool like Glean, which can basically pick your flavor of LLM applied to all of your information knowledge graph, it allows learning real time for assistance to be created so that learning can happen real time across all of that. So instead of people looking for the right file that captures the information that they're looking for, they actually just ask the question, where, what is the answer to this? How do I do this thing? What is this policy all about? If I put this policy together with this thing that I have to do in my job, what would it be? What's the best way to do something? How am I being measured? All these questions can be answered for an assistant now layered on top of somebody's information or knowledge graph. So I think that was one of the coolest things we have done from a technology standpoint across a broader learning strategy.

So talking about AI, how do you see it shaping the world of learning and development? And do you have any specific thoughts on what that future's going to look like in the next couple of years in the context of your work?

Yes, that's the short answer. I think I'll try to be as succinct as possible when creating a framework to— in understanding how to answer this question. So number one, what I always say is that artificial intelligence right now is a GPT, and most people understand that as ChatGPT, but it's not that GPT that I'm talking about. I'm talking about a general platform technology. So much like the internet was,, and then cloud layered on top of the internet and then mobile layered or orthogonally connected to cloud. It's going to change everything, how we do everything. And from just as the internet or the, or cloud has changed everything we do from how we bank, from how we communicate, from how we date, from how we connect to people or don't connect to people, right? This will change patterns of lifestyles. So why am I saying that? Because I think fundamentally how we learn. I just had a conversation with somebody else the other day. We're talking about our common parents and how they may not have had the best financial acumen to prepare us as children. When in reality, now we have this knowledge, we can just type in what is a 401k? What's the difference between an IRA or a Roth IRA? We have answers to these questions and how to set these things up simply because knowledge is now a commodity. I will say that in the future, understanding and application may be a commodity and how, what we're able to do. So it's going to be more of an idea economy. So What I'm getting at is that learning, much as it shifted in terms of understanding how it shifted with the web and the internet and cloud, will shift just as much, if not more, for artificial intelligence. So it's going to affect how we learn. Therefore, it's going to affect the L&D department from a corporate standpoint. What does that look like? Right now, you're starting to see pieces of it as people start to, from a skeuomorphic perspective, start to apply AI to make things better, faster, cheaper. Productivity enhancements, efficiency enhancements, different business models, but around the same economy, what you're going to see is profound effects as we rethink the world and what that means. And I don't have the answers to what that looks like yet, but I think the opportunities now are how do we prepare for a world like that? And for me, from an L&D perspective, it is lean into what's going on to right— what's going on right now. There's going to be productivity and efficiency. Gains based on using AI and in the next 2 or 3 years, agentic AI, but right now reasoning AI to just make things quicker, make things faster, make things better than what you're doing right now, but be prepared and start building out what I referred to earlier, that information or knowledge graph on how it graph on how you are doing things so that you're prepared for an intelligence layer to be upon that so that when the revolution does come. You're ready to take advantage of the intelligence that can be layered on top of what you do instead of it being sound. Okay, I have to document everything because I need this thing to tell me how to do it or how to do something different. Also, I think the final thing will be is that what's being called as like the accomplishment era, instead of being measured on the knowledge, you're going to be measured on the things that you do because it'll be— because accomplishing things will become so much easier, building something. It becomes so much easier. I think you look at that and where that's headed, and then you think about what, how do we measure that? It's going to be fundamentally different. So L&D folks will know things like SCORM and learning management system and AICC and LRS and LMS, excuse me, LXP. These are all things that are technologies and systems and rails that we are currently built on for corporate learning right now. And all of the rails will have to be rethought about how we measure and how we present, because AI will have the ability to basically be human enough, be smart enough on a specific domain, and also apply learning methodology to adapt to every single personal learner. So it's going to change it profoundly. So it's just a matter of readiness, I think, at this stage.

Sean, what parting advice would you like to share with our community?

Oh man, I love to be at the intersection. I said it was a final math at the very beginning of that. And the 3 things that I find that get me up in the morning are where I can play in the intersection of design, technology, and learning. And that what I would say, number 1 was that what I've discovered is that elegant design dies without technology, to be honest with you, in this day and age, you can have the beautiful thing, but if it doesn't do anything and it doesn't provide any affordances or provide a a better way or a capability for me as a person, it just dies. So elegant design dies without tech. I would also say that the coolest tech is completely pointless without design. So the two are symbiotic in nature. And so where I like to play is not only have great design, but have meaningful technology, but use learning as the linchpin, the sort of pivot point that makes sure that you are balancing the two. Is it— are you targeting a person's ability to do something better? That they haven't done before, making humans super. And then finally, I think that would be number 1. And number 2, what I've learned is that in the world tomorrow, if you can be T-shaped, in other words, be very deep in one domain of knowledge or one system, that is the most effective way to prepare yourself for the future because you are able to leverage the technology and leverage tools and leverage the intelligence that's going to broadly allow you to be not only productive, but more effective in the world that we live. So be very T-shaped and go deep in one domain, but at the same time, go wide in curiosity and learning so that you're constantly wondering how things are connected outside of your domain and things that you're open to change your life.

Sean, thanks so much for joining us today on the Built by People podcast. It was a pleasure to have you involved.

Yeah, thank you very much for having me. Have a wonderful day.