What If It Did Work?
What If It Did Work?
The Hidden Work Behind Every Workflow
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AI hype makes it sound like the future is a winner-take-all race between humans and machines. We take a different angle: AI is becoming a mirror that shows organizations the truth about how work gets done, including the messy, undocumented parts nobody puts in the handbook. When you connect AI to the tools where work actually lives (email, chat, meeting transcripts, spreadsheets, shared docs), you are not just adding productivity software. You are turning daily behavior into something that can be searched, summarized, and questioned. That can be liberating, and it can also be uncomfortable.
My guest, enterprise technologist and author David Dean, explains why the “inbox” is really a behavioral record and why the gap between the official process and the real process is where most companies get stuck. We dig into approval bottlenecks, meeting overload, and the quiet workarounds people build to keep things moving. Then we tackle the hard warning: if you automate a bad process, you do not get efficiency, you get faster dysfunction, and you pay for it at scale. AI can also create an illusion of productivity, producing polished outputs while goals stay unchanged, unless leaders and teams keep judgment and accountability where they belong.
We also talk about what AI reveals inside culture: missing decision ownership, uneven responsiveness, and the kind of behavioral analytics that forces authenticity from leaders. For employees, we explore a practical “step zero” approach to organizational self-discovery, plus why lived experience and lived consequence still matter even in a world of powerful models.
If you want a smarter, more realistic AI strategy for modern work, listen now, then subscribe, share this with a teammate, and leave a review with your biggest takeaway. What would AI uncover in your organization if you let it look at how work really happens?
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AI As A Mirror For Work
SPEAKER_01I never told no one that my whole life I've been holding back. Every time I lift my gun up, so fucking two for the stone to hear a voice like who do you think you want to do?
SPEAKER_02Alright, everybody, another day, another doll, another one of my favorite episodes of my favorite podcast, because I am biased. What if it did work? With me, what if AI isn't coming for your job? What if it's just coming for all the bad processes? The terrible communication, the unnecessary meetings that we all know about, the hidden workarounds, decisions nobody wants to take responsibility for. My guest today, David Dean, spent nearly two decades inside complex organizations watching how technology, the people, the processes, automation, everyday decision making actually collide. And that's important because there's the way a company says work will get done, and then there's the way work actually gets done. David, he's a technologist, enterprise practitioner, speaker, author of an inbox between us, AI and the reality of modern work. His argument is fascinating. AI isn't simply another productivity tool. It's becoming a mirror that can expose how an organization really operates. The undocumented work around the employee every day secretly depends on the approval process, everyone ignores, the decisions nobody really owns, the emails people are afraid to send, and the gap between what's written in the employee handbook and what happens Monday morning when you know what hits the fan. So today I don't want to have another conversation. I don't want to have another conversation about what chat GPT is going to be, and that's still everybody's quote unquote job. I want to talk about something much bigger. What happens when AI enters an organization that doesn't actually understand how it owns people work? How is it going, David? Welcome to the show, brother.
SPEAKER_00Uh it's going great. I really appreciate you having me. I'm excited for this conversation.
SPEAKER_02Yeah, I uh uh originally when you're published this, I'm like, oh my gosh. Or are are we gonna do the usual you know, discussions that it's a T it's a tool, it it's not Cyber9. It you know, we don't we don't need John Connor, but it it's it's more than a tool. Let's not do the the action figures or the Christmas cards with it and whatnot. Welcome, bro. Thank you.
SPEAKER_00Yeah,
Why The Inbox Is A Metaphor
SPEAKER_00absolutely.
SPEAKER_02So I I have to ask your book right off the bat what is an inbox between us about it's not really a book about email, is it?
SPEAKER_00No, it's yeah, absolutely. No. Um, so one of the biggest things when it comes to this conversation around AI and for organizations, is you know, there's there's a lot of uh it's very volatile, you know, uh out there, and and and people are still ultimately trying to figure it out, you know, you know, despite everything that's going on and a lot of the opportunities that are out there, it it's you know, especially as you get to larger organizations and then people trying to get acclimated on what this means, you know, the there's still a lot of people like are trying to understand the story and this relationship with AI. And what um, you know, for me professionally, you know, I work as uh AI uh enterprise strategist working for large corporate companies or small businesses doesn't really matter to me. But I was trying to figure out how to explain this so that people get it, and and not just like at an executive level, but like frontline workers, um uh midline workers, you know, uh uh people leaders, all that kind of stuff with it. And uh and I've had the opportunity to build lots of solutions, you know, tens of thousands of solutions at this point in my career for a lot of uh business units within organizations and understanding how they behave and why they do the things that they do every day with this, and all of that lived experience, you know, around that gave me a certain lens around why people do the things that they do uh around it. And um, one of the things that I realized is, you know, AI uh is designed to mimic human behavior. And and I was like, maybe here's an angle that I can kind of uh learn about and kind of explain to relate to people and understand what this relationship of AI looks like. And uh and what I kind of latched on to as a starting point is like, well, everyone uses email every day, you know, with it, and uh and and it's a landing zone on how people are generally productive within in a workplace. And um, and when I started thinking about that terms, I was like, well, now AI is uh email is now accessible via AI. Well, what does that mean? What opportunity does that offer when I can start looking at communication and collaboration data utilizing AI from a self-service standpoint as a regular person with it? And then it allowed me to start exploring what that what that really actually means. And it and it created a level of discovery that people don't realize actually exists yet. There's in there's aspects that people are starting to incline around it, but I don't think people realize the bigger picture of what that really actually means. And so I'm like, I think I have something here that needs to be communicated and voiced out to people because it relates to how they behave every day. So um, so when I refer to the inbox, uh the inbox, it's a metaphor for what I call the behavioral record.
The Official Contract Vs Reality
SPEAKER_00And so there's two aspects of an organization there's the official contract, which is our job descriptions, how we deal with um, you know, how we present ourselves, you know, our official documentation, standard operating procedures, all those different types of things that are kind of published out and saying, this is how we run as a business and this is how we operate with it. Then there's the unwritten contract, which is how we actually behave, like how we actually get the job done. And that is all either up here in our heads, you know, um, and the way we think about things and how we handle things. And it's also recorded in our behavioral record, which is in all our communication and collaboration data. And so, what if I could um use this as an opportunity to discover how I behave, how my team behaves, and how my organization behaves, um uh, and utilize AI as an opportunity to self-discover and understand opportunities, challenges, issues uh by pointing AI at that dynamic and asking it questions. What does it mean? What opportunity does that mean? What it can offer to us around that? And then that's kind of what I explore a part uh as an aspect of the book, um, because there are there are good things about it, and there are there are things that are going to be challenges in the future around that dynamic. And that's really the lens that I was trying to create.
SPEAKER_02Now, David, there was a world before AI. You spent 20 years inside organizations. What did you learn about how work really gets done, quote unquote?
SPEAKER_00Yeah, so uh one of the things a lot of times uh that was being advertised out in this AI world is you know, the you know, people can be replaced, and and you know, a lot of people were concerned about it and and that kind of stuff. And um, and my opportunity for in all those 20 years is that I I looked at all of these behaviors, especially in the productivity spaces, because that's what I specialized in, is is productivity types of systems, is like, why do people use email? Why do people use spreadsheets? Why do people you know do uh utilize these these artifacts in order to manage their day-to-day, you know, with it? And and because I built so many solutions, I had the opportunity to ask questions over those many years of why does this exist, both good and bad, and and and you know, why do you put up with it? Why do you manage it? Why do you deal with all these business processes in these antiquated ways with it? And uh and a lot of it came down to uh when I talk about the official contract, is you know, when someone's hired into a position, you know, in their job description, you know, either hired for these job duties and doing X, Y, and Z, but a lot of times that's not what we hire people for. It's not what those official roles are duties, it's the last bullet. Other duties apply. We hire people because they have lived experience and lived consequence dealing with the ambiguity of what that role is going to play as with it. And an artifact of that ambiguity is all of these, you know, productivity types of artifacts and behaviors and dynamics with it. And um, and that's when I started putting things together. I'm like, I can discover this stuff. I know they're documenting all of these dynamics in here, and so what can I get out of it? And so I do did a whole bunch of exploration on what this is going to mean for organizations in the long run around it, because essentially, you know, everyone's connecting AI to their communication, collaboration, productivity. So, what does this tell me? What stories does this tell me around it? And and just because I was able to recognize that and put all those kinds of organizational, the goods and the bads together, it really helped me paint a picture on how to relate AI and what is real and what is not real in the long run, especially around change management and organizational adoption.
SPEAKER_02Now, David, in your intro, also in the book, you argue that organizations have two versions of themselves the official version and the version that actually quote unquote gets shit done and operates. Can you explain that to us, please?
SPEAKER_00Yeah, so as I was saying earlier, is that when you have a business process, you know, usually most business processes are documented in some way, you know, in order to get this primary function of our organization done, you know, you have step one, step two, step three, and a lot of times that's communicated out with it. What is not communicated out is all the things that are surrounding or behind the scenes of like maybe a part of step two. And so when in order to be able to accomplish step two, I have to go talk to someone else, and then that person has to go talk to another person, that person has to do X, Y, and Z, and then they have to do a bunch of other stuff, and then they're managing and tracking all this other things in this other area, and eventually it comes back to complete step two in that process. Well, where is that documented? You know, uh, and and how do I understand how how or why this is even done the way it's done with it? Well, that's only in people's heads, or it's in the artifacts that people are using in order to be able to get this, get this shit done essentially with it. Because that's what I came down to. It is when I interviewed all of these business units, frontline workers and that stuff. Like when I asked, like, why does this spreadsheet exist? Why does this shared mailbox manage this business process? It's because I didn't have anything else to use. There was no system, there was no tool in order for me to do my business process. And I was told, let's get shit done. I don't care how you do it, just get it done and make it happen. And then it just becomes institutionalized and then people own it, and that just becomes the process with it. Whether you know, top levels realize it or not, you know, that's what it is. And organizations, especially large organizations, have hundreds of thousands of these types of mini business process solutions that don't really get talked about or discovered because they're all behind the scenes. And then and what I always joke on like, you know, people say, Well, our official systems is our ERP and you know, uh, and you know, um our our uh CRM system or something like that with it. I'm like, no, it's not. Your official system is the spreadsheet because everyone's using it and everyone's managing some kind of downstream, upstream or downstream process around that. And that's how your business actually runs. And uh if you took away the spreadsheet or you took away email, your business would stop 100% with it. So recognizing that you have this and you have these behaviors, you know, is an opportunity for organizations to self-realize and take advantage and move into the next era of AI.
SPEAKER_02Now, speaking of all that, you're talking about getting shit done. Now, what's a typical workplace process that looks just amazing on paper, but
Approval Bottlenecks And Behavioral Clues
SPEAKER_02just completely different in reality?
SPEAKER_00Yeah, so um there's there's a lot of them. I'll try to generalize them uh to like ones that most people relate to. So the very first one, um, and usually everyone complains about it because it does exist, is just the approval process. So you a lot of organizations to get something approved, regardless of the business process, it goes through a chain of leadership and decisions around that, and it has to go through people uh to basically before it moves up to the final stop and says, yes, this is good. I'm I'm accepting risk and responsibility of what this says, yada yada yada, around it. Well, the problem with that is is you know, legally, some of those have to have you know approval processes, and some of them they just invent in order to kind of control process with it. But the biggest complaint is like, why is it taking so long for something to get approved? You know, that dynamic right there is extremely common. And uh, and and and a lot of times that's why certain things don't move forward, they get stuck, they just sit around with that, and that frustrates people around it. So I need to go buy a new tool, you know, out there. A lot of times people will say that, or I'm gonna use AI and and just solve this problem. And the reality is that if you take a step back and you look at your behavioral record and look at why that is, you know, why is it taking so long? Not just a single single time, but over time, you know, every single time this gets done, what is the pattern there? The pattern is, well, it's getting stopped on this one step, this one step right there. Why? And and the biggest thing is a lot of people don't know why, and uh and it takes a lot of effort to basically potentially figure that out. But if you start like looking at the behavioral record of what that actually means, it could mean, well, if you look at all the correspondence that's related to that approval, that person is basically saying they don't feel like they have the authority to make a decision based on these circumstances with it. That's why they get hung up. And in that standpoint, uh you as a leader said, like, well, I give you the authority to make this decision, you know, make the decision, you know, with it. I give you full approval. And so you don't need a process, you don't need a solution with it. You just need to go have a conversation with that person and work through that dynamic. And this is where that opportunity of looking at that lens and looking at that behavioral record that can uh change the way your company operates. And I know that's a really small-scale standpoint, but another example is this individual is in in meetings, you know, 30 to 40 hours a week. Do you expect them to ever look at something and improve something if they're in that many meetings regularly? No, I need to change the way our process works. I need to delegate or hand it off or do or change that person's workload in order to be able to get this done. And so this is what I talk about kind of organizational self-discovery is now is the opportunity. What if the frontier of AI is not tooling? It's as what I said, organizational self-discovery, step zero. And so, and that scales because I can look at these challenges for me as an individual employee. I can look at it as a team, as a collective, as a team, and then I can look at my entire organization and say, where is where are we having challenges, where we have opportunities, where can we overcome some of the things that we realized were not challenged, uh were were challenges and we didn't know, we didn't realize, we didn't understand as a part of that. And it will completely change the way your organizations will function. And I have proven this time and time again with uh the clients I've worked with is if you take that step and you focus on step zero, it's going to change the way the company uh operates because you have to slow down to speed up. And and in order to be able to do that, and AI is a tool to be able to make that happen.
SPEAKER_02Now, David,
Automating Dysfunction At Scale
SPEAKER_02what happens when you automate a bad process? Do you simply become dysfunctional faster or yeah?
SPEAKER_00So the um, you know, when I say you know, AI is here to mimic human behavior. Well, a motto of mine is when you're trying to solve a problem around and you think AI is going to solve it, well, you need to make it human. And the only way to make it human is you need to understand human behavior. And if you think AI is gonna step in and uh and let's take AI as an example, because AI, what AI does is it industrializes human behavior. And so if you think about like, well, I have a problem, I'm just gonna throw a bunch of money at it and hire a whole bunch of people, and that will solve the problem. That if you if your organization is has a lot of dysfunction, you know, and every organization has dysfunction no matter what with it, but if you think um that approach is going to solve a problem and you hire a whole bunch more people, well, if it's not planned, if it's not organized, if it's not well understood around what you're trying to accomplish, guess what's going to happen? You're gonna industrialize dysfunction. You're gonna just make it worse over time, and then you're burning through money. That's not any different when it comes to AI, especially in this new metered world, you know, where AI is being charged for every activity or task at this point with it. You know, you throw AI at it and you think it's going to solve your problem, you're just going to be industrializing, you know, dysfunction even more. And then you're burning through credits, you know, with this. And uh and and that that's not an optimal model. So you gotta understand and self-discover in order to truly capitalize on the opportunity that AI is going to offer you. And not all of that is tooling, but if you do use a tool, it should be designed properly with the best ROI possible so that you can have that financial success with it as an organization.
SPEAKER_02Now, David, can AI create the illusion of productivity?
SPEAKER_00Oh, yeah, 100%. You know, uh it it um you know, it's it can be do all kinds of things from a presentational aspect with it. Um, you know, I'm I'm accumulating information, I'm putting information together, I'm presenting it out with it, but am I actually getting stuff done? Or am I just really uh rehashing, you know, essentially something that, you know, I'm not really accomplishing any goals with it. And and that's one thing is like, and and the biggest issue with that is you have to understand where there's opportunity. And if you don't give people the opportunity to kind of self-discover and figure that out themselves, they're just you know, they're just gonna play it around, they're just gonna create, you know, simple presentations or simple, you know, things that may uh may look attractive, but it's not actually solving
The Illusion Of Productivity
SPEAKER_00any problems and it's not addressing anything with it. Because people, you know, especially when they're not acclimated, they don't understand what that really means and what real change looks like. And change is hard, you know, with it, no matter what. And and that's what I talk about. This relationship is that AI is figuring out you just as much as you are figuring out AI. And in the long run, it's gonna be a symbiotic relationship. But um, but if you if they truly don't have the opportunity to understand what this means, then you're you're not gonna get anywhere with it. You know, it it's just gonna be a bunch of um POC or fun little projects, you know, that uh proof of concept output, you're not actually creating real change.
SPEAKER_02Now in your book, an inbox between us David Sorry about that. You say AI isn't here to replace human judgment. It's going to expose where judgment is missing. What did you mean by that?
SPEAKER_00So when I talk about the behavioral record and uh with this, and and one of the one of the biggest things that come out from a self-discovery standpoint, and when you look at that self-discovery and you start revealing um what that really actually is doing, you are discovering organizational dynamics
Missing Judgment And Forced Authenticity
SPEAKER_00and how your organization behaves, whether it's isolated to you or it's ice you know or it's out there. And that is now available to every single person has access, you know, access to AI, and it's connected to their behavioral record and everything that they have access to with it. And and theoretically, all this information has existed for years with it. It just was really hard to start putting puzzle pieces together with it. But I could do that. And there are companies that actually do this. I don't think people realize uh if you are ever actually sued, you know, as an organization and and you have an investigation, one of the very first things that has happened is legal hold in like emails and that kind of stuff, because they have to download all these emails and they have to look through and build that story so they can understand what's what was going on, what was happening. That's essentially what self-service AI is. You point Claude, you point whatever, whatever tool you have, you connect um email, uh, instant messages, meeting transcripts, you know, any other documentation, and then you start asking questions, it's gonna build stories. Stories that things that you know that allow you to self-discover an opportunity, but it's also gonna reveal certain things that organizations are not gonna be comfortable with out there. It's gonna start revealing some of the dynamics that they need to work through with it. And and so one of the biggest things when it comes to leadership around this is I think one of the biggest skills moving in over the next five years is authenticity. Is that as a leader, AI has now uh now reveals and exposes the dynamics of how you work and how you operate. So now you need to stand by your principles, principles and be as authentic as you are because you can't hide your dynamics anymore. Anybody can discover these dynamics, they can ask these questions and look at it. And I'll give you kind of an example from a people leader standpoint. I can actually use AI to identify that as a regular user that you actually respond to 20% of my emails, but 90% of emails to another another person in which I'm copied on with it. That's showing behavioral analytics out there. So that's showing favoritism because you're only responded 20%, and we're generally sending the same amount of emails, but you respond 90% of the time with it. What does that dynamic look like? You know, with it. That's the one thing organizations are not ready for, but people are doing it today. I can guarantee people are doing these analyses today with it, and you can't stop it because in order to be able to stop it, you'll throttle the rest of the large language model on how to discover you know these dynamics and these issues and these problems. So it's gonna force companies to be more authentic in their messaging and communications and how they act and behave, including even individual contributors. So that's one thing that they're not ready for. And I saw that right away when I was doing this exploration. I'm like, man, companies aren't ready for this, they're not ready to have to a certain extent their secrets because that's what they are, you know, hiding that ambiguity around it, whether it's conscious or on purpose or not, they're not ready to have some of these things revealed, but you can't really stop it, you know, with it. So I need to educate people and say, hey, you need to be aware, you need to be prepared for this because it's
Prompting Without Thinking And Accountability
SPEAKER_00gonna happen and it's already happening.
SPEAKER_02Now, David, are we in danger of creating a generation of employees who know how to prompt AI but don't know how to actually think?
SPEAKER_00Um we are, to a certain extent, uh with it, and it comes down to trying to educate what this relationship looks like. And and this is one of the messages that I try to communicate to everybody and all individual contributors and executive leaders. So the here's the important thing uh about why we hire people is because we hire people about lived experience and lived consequence. Like that's why we hire people into that position. And that center around that is where judgment and accountability comes into play with it. And the idea is that while we may be conductors of certain types of things, I still need to understand what that means. I still need to understand what decisions I'm making if I'm gonna let AI augment or enhance certain types of behaviors with it. Because um AI will never understand lived experience or lived consequence with it. And if you trust it to be that way, you that that's only gonna lead down to dysfunction. You are still making a decision. So no matter what AI produces for you, you are still accountable and responsible for taking action on anything it says out there, and and especially from an autonomous standpoint, you you are also accepting that. You're just accepting that on a more grander scale with it. So you have to decide where are you going to step in, what what decisions are worth um allowing to the release of that accountability, and what decisions are not with it. And and only really you know this because of what you do every day and how you behave and what things you should trust and not trust, because it all comes down to something's gonna happen downstream. And and if you repeat a behavior over and over, then it's gonna cause downstream consequences. And so I'll give you an example of probably one of the biggest risks to companies right now that is the it's not about um uh it's about giving the ability to an executive leader who's been uh mesmerized by the opportunity of AI, and rightfully so, but they have downloaded business data out of whatever official system that they work out of, a CRM or whatever. I download into Excel and I throw it into Copilot, Chat GPT, or whatever, and I make an executive decision based on the questions I've asked from that. That only has limited experience and limited knowledge relating to that. And and while you have your lived experience and lived judgment on it, by trusting that instead of going through the process to curate the most accurate data possible, those little decisions will add up, you know, and and some of these may be big decisions. And what if that's wrong? What if what you just did is the incorrect answer, and you just blindly trust AI for that? What kind of consequence is gonna happen downstream? Because honestly, when it comes down to it, and you're sitting in front of a board of directors and you say, Well, that's what AI told me, that's not gonna be a good excuse, you know, for it because you still own the accountability. Now that's a you know, uh that's a very common behavior, but those types of behaviors happen, you know, frontline workers, midline, you know, managers around that. When you start throwing AI into the equation, you start asking questions around it, you still own it. You are still accountable. And and if you don't understand why, then you shouldn't be making a decision from it until you understand why.
How Jobs Change Without Mass Replacement
SPEAKER_02Now, David, what's gonna happen to all the entry-level employees of all these companies with AI?
SPEAKER_00So the the biggest thing is uh I get you know the allure of AI out there, but but the I think where where you hear a lot of things where they think they're gonna replace a whole bunch of people, yes, it's gonna replace a whole bunch of people and a whole bunch of jobs, um, but not right away. It's gonna it's gonna take time to cultivate because if you gut all that lived experience and lived consequence, AI is not gonna be able to deal with that. So when you have when shit hits the fan, AI is not gonna self-recover, it's not gonna deal with that situation. You still have to have someone step in and like, how are we gonna deal with this? It's like, well, you didn't plan for it. You've let go everyone go who actually had the institutional knowledge on how to manage and deal with all this ambiguity that comes up. So um, so ultimately it's a transition. So certain behaviors and certain tasks, absolutely, that's where like augmentation uh with it, but I think it's more going to be the changing job. I think jobs are just gonna naturally change over time, and AI is just gonna be a part of that, and the jobs will look different with it. And and the employees that understand that and recognize that, and they're given that opportunity with that change, um, what it that will transition to it. Now, are there certain positions that may eventually go away? Yes, but there are risks with that, you know. Uh I don't know about anybody else, but call centers happen all the time, you know, on on with this. But when you try to call someone and it's fully automated and you have a weird issue or a complicated problem, and you are getting in this, you know, loop on this. We've we've all been there, all in there with it. And I'm like, I hate this company, I never want to do business with this company ever again because that is not a good customer experience for me. I'm gonna go to the competitor that has a human opportunity for me. I get it that there's maybe some initial iterations. I still want to talk to somebody, you know, with it. I need to talk to somebody, you know, because that's what humans do really well deal with the ambiguous. And I think that was one of the important messages around all these what I call AI survivalists, because that's the people that I talk about. Is they're not against AI, they're not necessarily for AI. It's a tool, they're just doing their jobs every day. It'll be a part of something, but they're still not understanding what that relationship is with it. And and my message to you is your job's gonna change over time, but change takes time. It's a relationship, and it's and and you will have time to eventually figure it out. Um, and and I hope the companies give the opportunity to be able to figure it out with it. But by the time it's really kind of get acclimated, because it's still volatile in the AI world right now, you know, uh around it, where is it going to land? And by the time it lands, the position's already gonna change because every five years, that position really never existed, you know, five years ago with it. There may be behaviors and patterns, but that's really is so no one's really ever gonna be in that in that position where they're really being eliminated because a lot of times if they try to do that and then dealing with that ambiguity, they're gonna end up getting hired back in some way or some capacity, and then there's gonna be a bunch of mud at the company. You hear about that for a lot of different companies where they just oh, we laid off and we AI automated people, like AI is not ready to deal with that lived experience or lived consequence, and it may never will be. So we need to rethink our strategy and our approach on this, and we need to understand how people behave before we make a critical decision that could gut our company with this. So it's more about I don't need to hire more people. That's really the change. Like, so we're dealing with all this stuff and we're overloaded. Well, let's bring AI to help unload that stuff so we don't have to hire more people for these types of positions. That's more of the real change that's out there with when it comes to AI and the opportunity.
SPEAKER_02Now, David, in your book and in Box Between Us, you talk about
The Invisible Workers Who Keep It Running
SPEAKER_02undocumented work. Who are these invisible people inside the organizations that are quietly just keeping everything running?
SPEAKER_00Yeah, so they uh they're what I call the AI survivalist out there, and they're there a lot of times they're your front frontline workers, uh, midline workers, your your frontline uh leaders, even mid mid-level managers around it is you know, those individuals that know how the job is done and and get the job done, you as an executive may never see that. You may never understand what they do and why they do the things they do every day with it. You just know that's there's an accumulation of people that make get things done and eventually it rolls up to me, and I may have to make a decision, or I'm I'm I acknowledge that we've accomplished a goal or a task or something like that with it. But there's a lot of steps to be able to make that happen, and that's where uh those frontline workers who really actually know how who are dealing with most of that ambiguity every day, that's where all your institutional knowledge is with it. And they're the ones that are managing, and those are the ones that are invisible from a lot of the decisions that made because everything that moves up that chain has been kind of constructed and say, This is where we're at, this is where the numbers are at, this is how things are getting done. You know, it's all story building, and that's why I talk about when it comes to AI, that's the whole purpose of AI is building stories. You know, you ask a question, it builds a story. And a lot of times, some of these bigger stories, that's the whole reasoning process. You look behind the scenes and you uncover when when AI is breaking things down, it's building breaking it down to build smaller stories, to build smaller stories, to build smaller stories. And then once it figures all those smaller stories out, it puts them all together and puts them all together and puts them all together until it gets to that top level that you want, that you are going to make a decision on. That's not any different on how organizations work, you know, how people behave, how things move up the chain with it. And so that's why I said AI mimics human behavior, and that's really what it is. It's uh so what are the all the behind-the-scenes people that are doing that? Those are those frontline workers to eventually feed everything up to the decision maker, uh, with whatever level that's going to be.
SPEAKER_02Now, David, what's the biggest mistake you're seeing right
Stop The POCs And Prove ROI
SPEAKER_02now companies currently making with AI?
SPEAKER_00So I think the uh the biggest mistake I see is is that you know, the time the time of POCN has now kind of ended, you know, because AI was free to a certain extent where people can kind of do whatever they want to do, you know, out there on it. And um, because now things, you know, where people say it may be getting uh certain things may be getting cheaper in the long run, yes, from a self-service standpoint it is, but people want volume, they want to use AI at volume. Well, that's expensive, especially how many iterations it takes to be able to make that happen. So, uh, and I anticipated this. This is one of the reasons I came out with the book, is because everyone was sold with the what ifs. What if this, what if this, what if this, what if this? But in order to get to the what-ifs, you need to understand the what is. You need to understand where you have a problem, what that problem is, and and does it make financial sense to address that problem and how to address that? So people ran into it and tried to make things happen and and do a lot of a lot of the magical things that are being put out there, but it doesn't scale, it's not sustainable out there. And and a lot of people spent a lot of money and they failed and they failed hard on here. Now's the opportunity for discovery. And so take a step back and think about you need to slow down to speed up. And when you when you look at that lens and you look at your behaviors and where there's the real opportunity, you need to start small. You need to look at those behaviors where those opportunities are. So, like a call center is a very common example that's out there. Um, if a call center, a single step in a call center employee, it normally takes them, let's say, maybe 30 minutes to research something. Or excuse me, five minutes to research something while they're on a call with a client. What if I can take that five minutes down to 30 seconds, you know, in that circumstance with it? What kind of soft gains would I get from that? What kind of hard gains would I get from that? That's a single step in a business process. You don't have to automate everything, even a single step can have huge ROI, depending on how many how much your volume is. And if you tune it that way and you do that one thing really, really well, then though that ROI helps pay for other things when it comes to the AI opportunity. What other things can we solve with this? We don't have to break our business process. You know, our business process generally works, there's just certain parts that are slow. So let's augment, let's enhance that. Let's break it down to something that's tangible that has that real ROI. That is what's going to, and then you start doing those, and those things accumulate, and those things tell stories to a point where okay, we have saved enough money by automating these different types of processes with AI. Let's go for the big one. Let's go for the one that's going to be expensive, but now we have a better understanding on that opportunity. We have a better understanding on how to discover, on what we need to know in order for this to be this larger project to be successful. And it's understanding human behavior. I can't keep stressing that. Is that that's the part that's skipped? That's the mistake. They skipped over the human part of all of this. And if AI is here to mimic human behavior and you don't understand how humans behave, how successful do you think you're actually going to be in your AI project? You're not. So take a step back and understand why.
SPEAKER_02Now, in the book, you emphasize clarity before acceleration. What does that actually look like inside a company?
SPEAKER_00Yeah, and and uh when it comes to clarity, is like that's where I talk about that behavioral lens
Clarity Before Acceleration Step Zero
SPEAKER_00and looking at um, look at your processes. And from a self-service standpoint, you know, um, you know, a lot of people ask me, well, how do I get started on this? Like, what do you mean by organizational self-discovery? And I said, Well, you have a phone, right? You know, with it. Um, your voice is one of the most powerful tools out there to discover this. And what and and so what I say is open up like your notes app or notes app equivalent, tap the dictate button and start telling your story. Start on just get it all out, you know, with it. How you behave, what you're frustrated about, how you do your job, how you do your processes, get it all out there. It may take multiple days, you know, of doing this and getting it all out. Now that you've done that to a certain extent, then what clarity can I get from this? What if I start asking questions? What is this telling me? What is this telling me about my dynamic and how I behave and how I do things and challenges relating to my position and job and all these different types of things? What opportunities are there for me? Maybe it's automation, maybe it's um you need to go and have a conversation with someone. You may there's there's all potential if you know how to ask the right questions there, um, with all those dynamics with it. And uh, and so if you uh if you do that, you gain all kinds of clarity, but that's only a part of the equation because AI is not going to solve the problem. AI is gonna give you signals, it's gonna give you information. You're still making decisions and still accountable of that. So you also have all your lived experience and lived consequence that's sitting in your head. So if you bring the two together, that's the opportunity for clarity. That's the opportunity to take action and move forward with those types of things. It's the relationship between the two, it's that symbiotic aspect. You know what you do best. It helps you create ideas, concepts, signals on where to potentially take action. And then you start learning what clarity actually means and how AI can be benefited for you. And that scales because if every person in the organization did that, means every team just did that. What does that story put together as an entire team? And then you have the whole company. Doing that, then you start seeing the, you know, you put all these things together and you start discovering wow, there is a ton of opportunity here. And that clarity is going to, if everyone understands that clarity and can move forward from that, the entire company is going to move forward. Everyone's going to get ideas and everyone's going to start talking about these dynamics and opportunities and ways to solve problems with that. That's where real change comes into play. And that's what I encourage companies to do.
SPEAKER_02Now, David, what should leaders actually tell employees who are afraid AI is like
What Leaders Should Tell Worried Teams
SPEAKER_02Cyberdyne and Skynet, and it's going to replace them.
SPEAKER_00Yeah. Um well, I think the biggest thing is one messaging that I highly recommend for leaders to kind of slightly change their tune around some of these things is that we recognize everything that you do as an employee. You know, when we talk about the official contract and unofficial contract, if you if you think about that and you spend time with that, like how much stuff do I throw at these people and tell them deal with it, figure it out, you know, all that kind of stuff with it, make it happen. So if you recognize that and own that, then you can basically say, we recognize everything that we throw it at you. And what we want to do is because you don't have enough breathing room to do the things that you do best, why did we hire you in the beginning with? We hired you to be able to think critically, think innovatively, help bring the company forward in ways that you never that we wanted you to do that. Well, if we can free up time and opportunity for you to eliminate some of these tedious behaviors through self-discovery and opportunity with this, now you can do the things where you never got a chance to because people have a long backlog of ideas or tasks or things they never get around to doing just because they're they're surviving, they're dealing with all the ambiguous aspects of the job. So if we can free some of those ambiguous aspects and those tedious aspects and say, now here's your opportunity. Use AI as an opportunity to figure out ways where we can be better in your role. How can your role be better? How can our tasks be better? How can the whole organizations be better? And if you basically communicate that and say, this is the opportunity for us to shine and grow as a company and give you that time to be able to make that happen. And then people start putting their heads together on everything that they found out and discover with it, your company will change in very quiet ways that will just overtake you. And you won't even realize your company just flipped or changed. It'll just, it'll be massive, it'll be quiet, but then you will start seeing all this amazing opportunity, amazing uh critical things that people um have thought of and and iterated over and and discussed and worked out because they have the opportunity to do so and communicate and collaborate. And that's the things that humans do best. When you put people together and allow and say, come up with ideas, go explore, figure out ways where we can be better as a company, and we put together in that collaboration aspect, that's where real change comes into play. And if you create that opportunity, and that is what your message is, people will be like, okay, I get it, I understand that. And you're giving me the opportunity to be able to make this happen. Um I'll own it, I'll move forward with it. And and then people will overall be happier because they feel like I have a voice, I have an idea that someone actually is going to listen to. I have the opportunity to make potentially make that happen. They'll get excited over that. And and so when they have that opportunity to do so, it will create great change in your organization.
SPEAKER_02Now, David, your company's about to discover that your biggest technology problem was actually a people problem.
SPEAKER_00Um I would say it's not so much of a be a people problem. It's more of just uh institutionalized behavior with it. At some point, maybe someone made a decision to do X, Y, and Z, and that X, Y, and Z process was institutionalized because they didn't have anything else at the time with it, and then it just got adopted uh as a part of that, and then just and then over time, over many years, this is the way we do do things, this is how we do things, this is the way we deal with it. They don't know any better, they don't know any other opportunity to uh make that change, and they're not given the the breathing room to make that change
Institutionalized Workarounds And Security Risk
SPEAKER_00around it, or they're not given the funding to make that change with it. Um, all of these things are 100% relevant with it. So um people problems are discoverable, and they're way more discoverable now nowadays, around what I call it from the from the inbox standpoint, the behavioral record. But um, but I wouldn't necessarily the the institutional challenges are generally the same no matter what company, and the reasonings for that with it. And a lot of times these types of behaviors have existed for a long time, and uh, and it's just recognized that they exist, and we probably should do something about it. You can't just keep having your head in the sand over this. And I talk about this with uh chief security officers a lot, where um, you know, all of these citizen developed solutions that are out there, you know, the the shared mailbox or you know, the spreadsheet or a collaboration tracker or anything like that. As I said, there's there's hundreds anywhere to hundreds or tens of thousands of these, even hundreds of thousands of these, depending on how big your organization, they exist. They are risks to your company and your operating model with it. Um, you can only deal with that, uh that you have a volume problem. So you need to look for ways to address that technical debt in some way, in some manner. Otherwise, people will keep behaving the same way that they are, and it will just, and and you will not self-improve around that. So you have to recognize you have a problem first, and then have a plan to work through that. And there are tools and technologies out there that can help industrialize that and kind of rapidly get those behaviors out of those kinds of avenues with it and get people into something that's more sustainable, more secure, and and more operatable. And then maybe AI is an opportunity to enhance that process with it. But um, but from a people problem standpoint, I think it's it may initially have been, but at this point now, it's just an institutionalized problem. And someone just needs to say, we can't keep doing this anymore. We need change, we need something to make happen. How can we understand that? How can we understand how to make this change happen?
Ambition, Intent, And The Observant Climb
SPEAKER_00And and so we can move forward from this.
SPEAKER_02Now, speaking of enhancing, David, could AI actually make great employees more valuable while exposing the mediocre ones?
SPEAKER_00Yeah, absolutely. I um I actually uh wrote a uh so I I do uh um a newsletter, I try to do it once a week to kind of extend this conversation around you know uh what I talk about in the book. But I I actually I really like this one. It's I call it the um the observant climb. And it's actually about um two up-and-comers, they're interested in getting into leadership positions with this, and um and they're using the behavioral record to discover and understand so they can get ahead, you know, with this. That's the basis of the article. But the one thing is one of the it comes down to intent. And um, and so you have one person who has used that behavioral record to essentially social engineer an executive leader to basically say whatever you, you know, you learn what they want to say and what they want to hear, and you get into their good graces over time, and eventually you get into that position, you know, they may lead into that position. The problem is now they're accountable at that point. They've they hit the goal that they had, but they never learn how to really do the job. They think they know how to do the job, but they never learn how to do the job. So, how long does that person actually last in that role, you know, with it? And so uh unfortunately they may end up stepping on people, but um, but you know, you'll eventually, you know, the uh it'll come due at some point. Where you have the other person who basically did a similar behavior with that and started learning, but they their lens was different. They're like, I need to know how leaders talk, I need to know how leaders think and how they discuss and work through issues. I'm going to use this opportunity not to social engineer, but to create insight so I can be better and be able to move forward from that. And and they ended up earning the position, maybe not the exact position that the other other individual, but they learned how to engage with leadership. They learned how to be a part of the team and how it works. That individual is going to be much more successful in their career in the long run because they used AI in the right way with the right intent in a non-malicious way. And and they are the ones that are going to thrive in the long run with it. And uh, and and that's and that's real. People are doing these types of things to be able to figure out how to get ahead internally within an organization.
SPEAKER_02Now, David, five years from now, what do you think we'll realize we just completely misunderstood about AI and more?
Why Lived Consequence Still Matters
SPEAKER_00I think uh I think that misunderstanding is is what I keep coming back to, like why humans matter, you know, why and why they're important to begin with, and and really what this relationship looks like. And that's what I was anticipating is like people are gonna start running through this and then people are gonna fumble and they're gonna have challenges with that. And and then people are gonna get dragged through the mud as a part of this. And my goal from this book was honestly not to sell books, but to sell the message, you know, from the book with it, is that I want people to make the right decisions. I want companies to be successful, and I want them to have the right lens when they make these decisions out there. And five years from now, you know, not all companies are gonna succeed. And some companies are gonna go under because of the mistakes they made around AI with it. But the companies that self-discover and recognize what the value people had, they will understand what that dynamic and relationship is going to look like over the long run with it. And once they once they understand that and put the right things in place, they're the ones that are gonna thrive out there. And um and and really uh their mistake is is that is that AI is doesn't have that lived experience and lived consequence, you know, with it. Um, if it did, it would put all us out of a job, you know, uh in all reality. But if you wonder why I say that, is that um until AI can crawl out of the machine and lived amongst humans, but even living amongst humans, uh that downstream or upstream dynamics with this. And and I'll use this as an example. I think this is a very solid way to kind of portray this. It's a very extreme way, but do you remember several um uh I think it's several months ago at this point, I think it was in March, um uh that horrible incident in LaGuardia where the airplane um hit the fire truck and you know the pilot was killed and all that kind of stuff. But all but all the passengers were, you know, there was a lot of people injured, but uh, but they lived, you know, with that. Well, as a part of the black box, and and they're still working through this, but the pilot had six seconds, roughly six seconds to make a decision. And and and while this is not absolutely confirmed, I would like to presume that in that six seconds, that pilot, all of his experience, his lived experience in being a pilot for years was flashing in his mind during that time. It's like I have to make a decision around this. Do I swerve or do I you know hit it dead on? That was the only two options they had in that circumstance with that. And so I like to think in that circumstance that he thought about all the lived experience and all the downstream issues. If if I swerve, this is what it's gonna mean. It's likely that a bunch of passengers are likely going to die. The um all their families are gonna be affected as a part of this um with that, or if I hit it dead on, I am likely going to die. And that's going to affect you know my pilot and all of our families with that. You know, and they and the decision was made, they hit it dead on instead of swerving with it, and so the pilot was killed in that regard. That's what lived experience and lived consequence come comes into play. AI is never going to understand that, it will never understand the emotional aspect and that intuition of making those kinds of decisions, that gut feel based on everything that's about us. And we are machines, if you want to think about it in terms of that. We have all these senses, we have all this knowledge, we have all these different types of things. We're a part of the equation, and there's things that we do really well. And companies that don't respect that and understand that in the long run, they're not gonna succeed. But the companies that do and recognize where that is valuable and where that is needed, those are the companies that are gonna succeed as a part of the equation. And so that's where I see, you know, five years from now, um, where uh those are the companies that are gonna make mistakes that don't realize that. And that's why I was trying to get the book out and say, don't make this mistake. Recognize the role that people have and recognize the role that AI has, understand that, figure it out, and create the ecosystem that's gonna allow you to be successful and sustainable in the long run.
Where To Find The Book
SPEAKER_02Wow. Impressive. David Dean, an author of An Inbox Between Us. Now, David, where do we get the book?
SPEAKER_00Yeah, so uh David Christopher Dean, uh, which is my personal website, um, has a whole bunch of information on there relating to like some of the concepts I talk about. But uh, you can find my book uh there. Um I also have an audiobook version of this. I'm on all major retailers, you know, Amazon, um, uh Barnes and Noble from the print book. Audiobook is widespread. So you can pretty much find it on almost any platform, not just on Audible, but on um, you know, Spotify and all those other areas with it. So um I would encourage you to check it out. It's a good listen. It's uh it's really just getting that right, that step zero, that right mindset positioning to think about before you really start making real decisions around AI.
SPEAKER_02And how do we people, how do people find you?
SPEAKER_00Yeah, on my on my website, davidchristopherdean.com or LinkedIn. Um yeah, LinkedIn. I'm very active on it. Feel free to reach out, message me. I'm happy to talk and chat with you.
SPEAKER_02David, thank you for the book. Thank you for the opportunity of just having a conversation with you, brother. Best of luck with everything, an open invite to ever just come back and discuss book your future books and your future endeavors.
SPEAKER_00Absolutely. Thank you for having me. It was it was uh a pleasure to be with you.