Your boss walks in and says, “What are we doing about AI?” How do you respond? On this week’s podcast, Paul and Rich break down the problem with the question itself, and the way AI is being offered as an imprecise, ineffective solution to solve business’s structural problems. Who actually needs AI—and how do you figure out the best way to use it? 

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Who Actually Needs AI?

Paul: Hello, I’m Paul Ford, the co-founder of Aboard.

Rich: And I’m Rich Ziade, the other co-founder. We are coming to you from probably the best city in the world.

Paul: New York City.

Rich: Yeah, baby.

Paul: I’m actually, I’m downtown, in Manhattan, Richard, you’re home in Brooklyn. We’re about to, about to meet up, but we, let’s record this podcast. Let me tell people what Aboard is, real quick. Aboard is a tool, we’ve been working on it for years, that manages your stuff. And when I say stuff, I mean your organizational stuff, your company stuff. We talked to somebody yesterday, they want to use it for inventory tracking because it’s easy and pretty and a way to take ugly data and stuff that’s buried in spreadsheets and just make it in the software where people can collaborate and be friendly with each other and hug and hold hands and sing songs.

Rich: [laughing] All right. You can start a cult with Aboard.

Paul: Yeah, yeah, it’s pretty good. So anyway, let’s do it. This is the aboard podcast. Let’s go.

Rich: Let’s go.

[intro music]

Paul: You know what’s funny, Richard? I can feel us going back out to the world to communicate about software and things that we’re building, and reflexes kick in. Reflexes kick in include getting new eyeglasses. I have pretty good eyesight, but I could use glasses.

Rich: We could charge more for software licenses if you have nice glasses on, Paul.

Paul: I just ordered a bunch of clothes, and it’s like, oh, it’s slacks time again. I’m going to need some slacks, right? [laughter] Need a Brooks Brothers shirt. Gotta, gotta get a couple of those.

Rich: I mean, you’re thinking the right way here. I’m not gonna get in your way on all this.

Paul: No, no, this is, it’s just pure instinct. It’s like, I can feel it happening. We’re going to meetings and I’m like, the funny thing is, when you run a company, your life becomes essentially, like, your office becomes a wardrobe. I remember this at the last, at the last shop.

Rich: Sure.

Paul: Like, I had blazers everywhere. I had them hidden behind the boiler, you know? Because you just, you’re like, oh, God—

Rich: Just in case.

Paul: I mean, I had, you know, essentially, you keep, like, a pharmacy. You need Advil, you need toothpaste. Because here’s why—you’re gonna have an event in the evening and, like, you need to brush your teeth.

Rich: Totally.

Paul: So all these things—you have to shave at the office. That happens.

Rich: It’s the salesman kit.

Paul: Yeah, yeah.

Rich: Survival kit. It’s the salesman—no, we’re not salesmen. We are deep thinkers and technology leaders. Let’s be real.

Paul: [laughing] Yeah, but also sales. Let’s, like, yeah—

Rich: [overlapping] Ultimately, you need mouthwash. [laughing]

Paul: Ultimately, we are enterprise software salesmen. Let’s be honest. So, speaking of enterprise software sales, we have a product. Let me tell you something about Aboard, Rich. Let me tell you something amazing about Aboard that everybody needs. Aboard has one thing that absolutely everybody wants and needs, and they should have it right away. Because it is powered by AI, the most important, exciting, new, wonderful technology ever. And that’s what every organization needs. And I want to throw that over to you and let you riff on it and tell people how much they need AI and how good it is in their organization.

Rich: Before I do that, I want to talk about a friend. I don’t even know if it was a friend, he was more like a neighbor. My teenage years were spent in Canarsie, Brooklyn.

Paul: Phew! [laughing]

Rich: And this neighbor owned—

Paul: Wait, you got to get—Canarsie is still, Canarsie is rough. It’s big. It’s, but Canarsie, like, when you say Canarsie, there’s like, five or six neighborhoods that still have a, like a deep Brooklyn, like, whoa, okay, you’re from Canarsie.

Rich: Yeah. It’s far out, away from the city. That’s why it’s rough. I’m gonna give him a name. I’m gonna call him Mike. Mike owned what was essentially, I guess, like a Nissan something. Give me, a Nissan Electra. Is that. Is that a car?

Paul: I mean, we can say it is. That’s how, that’s another way. You know, we’re New York, New Yorkers, is we don’t know what cars are.

Rich: Cars. Yeah. And the thing with this car was it had problems. It was a used car. It was Mike’s first car, and it had problems. And he probably should have saved up and either gotten rid of the car and gotten a different one or, like, really changed, like, the transmission. Like, it had problems. But you know what Mike did? He would go to Autozone, and he would get neon glow under his car. He would get stickers, like, script in, like, fancy script. It would say RESPECT along his door. And he bought subwoofers that, I kid you not, whatever I had for lunch that day would knock it out of my digestive system. [laughter] And I would ask him, and I would say, “Mike, I think you have, like, more fundamental issues.” He goes, “Yeah—” “—with this car. And you keep, you keep dolling it up and, like, it looks like a spaceship at this point, from Canarsie.”

Paul: Mmm hmm.

Rich: “And yet the core issues, like, the core, the core problems is the car doesn’t run well, dude.”

Paul: Like, the carburetor.

Rich: Like, he won’t take it out if it’s over 95 degrees out.

Paul: Mmm hmm. Mmm hmm.

Rich: [laughing] It’s not going to be a good day.

Paul: Mmm hmm.

Rich: And he looked at me and he said, “All right, Rich, I got two problems. First off, I want to look cool.” I’m like, “All right, I’m not going to debate that.” “And second off, I don’t have three grand. I have $180, and I can go to Autozone and buy stickers.”

Paul: So let me, let me see. Thank you for that metaphor. That was five minutes well spent. Let me see if I can translate it. IT spend is vast. If you go, and I don’t think people realize how vast it is. Why is there a company called Salesforce that’s worth hundreds of billions of dollars? Right? Why are there these companies like SAP? And when you go into a big org, what you realize is, I don’t know, like, 5% of all their money might go to software. Like, just like, you know, they sell carpeting. They sell—

Rich: It’s a massive amount of money.

Paul: Aluminum. Right?

Rich: Yeah.

Paul: But so much of, because the efficiencies of software are so necessary, and because software is what lets them manage their tax bill and their billing and their invoicing, because software is so critical to revenue in every which way, it’s a tax they’re willing to spend. They’ll just, they’ll pay it.

Rich: It’s not even, I mean, people run their businesses on the software.

Paul: In some ways, Rich, like, a large business can just be understood as, like a database with people floating around it.

Rich: Yeah.

Paul: Right?

Rich: I mean, the software going down, that’s why, you know, why is, you know, an SAP and a Salesforce, why are they behemoths? It’s because entire businesses are running on them. Like, literally, the transactions, the inventory management, the sales pipeline, it’s all in software. It’s all inside of software.

Paul: Any scaling business in 2024 has invested an unbelievable amount of their money in their resources, whole percentage points of the whole value of the company into software.

Rich: Yeah.

Paul: And they are desperate not to do that again. That’s a bad feeling. You do it once? There are projects. We talked to somebody recently who’s got a six-year ERP system rollout.

Rich: He said, and we’re paraphrasing, “I might retire before this rolls out.”

Paul: Right. So much money flowing through the door, and most people, especially midsize organizations, truly can’t stomach it. It’s all their profit. It’s their bonuses. It’s the expansion plan.

Rich: Yeah, yeah.

Paul: Am I going to buy software or am I going to get a new warehouse? That’s the way they think.

Rich: And I think what’s so interesting is that you would think we were talking about year-over-year innovation and forward-thinking software deployments. It’s not that. It’s not that at all.

Paul: I’m going to just say something. It’s indistinguishable from the stuff we saw in 2006.

Rich: That’s…now we’re getting to the crux of it.

Paul: So now back to your metaphor, right? I know that my car, I know that my software is beat up. I know that it’s broken inside, but it runs. I get places. And what I just need is a little something to keep, keep everybody happy, keep everybody thinking I’m cool. I need, I need to like, and I don’t want to spend, I can’t spend 5%, but I can spend a million dollars. I can spend a million dollars so that everybody thinks I’m awesome.

Rich: Well, here’s the distinction I want to make. Mike can’t replace the car because he can’t afford it. These businesses can, can afford it from a price perspective. What they can’t afford is the cost of change. These businesses are in motion. They’re transacting, you know, millions and billions of dollars. Change, as an organization gets bigger and moves faster and grows faster, the cost of change becomes absolutely terrifying. Like, that sort of like, oh, we’re going to switch over to the new thing over the weekend is absolutely terrifying.

So what happens is IT, classic IT, their primary job is not to, like, disrupt and innovate. It’s to make sure, frankly, nothing goes wrong. Like, that things stay stable and secure, and there isn’t breaches of any kind. When you come to them and you pitch the future, they sort of smile at you. They might put a little money in the innovation group. I don’t know what, we should talk about the innovation group. It’s sort of, when I had, my kids were babies, we had fences that we put up in the house, like plastic fences, so they didn’t hurt themselves and break anything. That, to me, is like the innovation group inside. [laughing]

Paul: Well, no, we’ve talked about this before. My thesis of the innovation group in an organization is really simple. You need a place, you need some smart people to kind of just come up with ideas so you have something to present and talk about.

Rich: Yeah.

Paul: They tell themselves that they are the future of the company, and you put them in a political bubble, and you never let them out. You don’t let them ever get any power. And if you want to know how well this works, find me one innovation group leader who later went on to become, like, a CEO or even a CIO, right?

Rich: Yeah. Yeah. And this is not to shit on innovation group leaders.

Paul: No.

Rich: I mean, honestly, that sounds like a pretty damn fun job to be outside the politics and play with stuff.

Paul: It is, but it’s literally outside the politics. You don’t get access to power.

Rich: You don’t get access to power. Now, AI is here. Now, you gotta understand, this is the backdrop. We took a minute to paint this backdrop that most stuff is 2006. Most of the world is real basic, man. And now AI shows up, and it’s not that different than any, like, big-promise tech leap showing up, right? Like, crypto is like, you know, we’re banking all wrong, guys. This can’t work.

Paul: Crypto was just grim. Like, AI? There’s actually a, you can use the product. Like, crypto is like, you know, one day you’re gonna be able to buy a soda anywhere using your eyeball. And it’s like, but I can buy a soda now for too much money, in cash. I can just go to a store.

Rich: [laughing] Yeah, yeah.

Paul: And they’re like, no, no, no, you idiot. You idiot. And that was, and literally, whole companies would, they’d come and they’d be like, we need to put all of our office chairs on the blockchain so we can keep track of them.

Rich: Yeah, yeah.

Paul: And you’re like, why would you do that? That’s a spreadsheet.

Rich: Now, look, I do think there are some smart things happening with AI in that they’re finding sort of these extremely high-friction patches in the process where, like, everything’s moving along, and then all of a sudden, it takes forever for, like, that one step. And AI can help there. Like researching compliance in a particular geography.

Paul: Translation between geographies. I mean, I used it to, you know, explaining concepts, translating from one sort of form of communication to another. It’s great.

Rich: It’s great, it’s great. It’s great for I need to look up a very strange regional or local law around regulations for a particular permit—

Paul: Mmm hmm.

Rich: —that I need get so I can build the factory. Like, holy hell. It used to be like, go, legal team. Do your research. Give us a memo in two weeks. It’s. It’s pretty amazing that way. But you’re not uprooting legacy software and its roots. If you ever yanked mint out of the soil, it doesn’t end. And that is legacy software.

Paul: Mmm hmm.

Rich: Like, it’s just so deep in. And people become experts at it. Right? And so they don’t want to—

Paul: This is real. You got it. You gotta cut mint, because every time you think that you can pull it, it just, like, you end up with this huge pile of mint. That’s all stalk.

Rich: Yeah, yeah, there’s, like, little hand saws for mint, actually.

Paul: That’s a very nice little metaphor right there.

Rich: [overlapping] Thank you.

Paul: [overlapping] That’s a good one. I like that.

Rich: That’s a delicious metaphor. It’s summer here.

Paul: Yeah. Have some iced tea.

Rich: And so, eventually, every so often, you do get a stakeholder that says, enough. Mike said, all right, no more stickers. I’m gonna sell my subwoofers. The subwoofers, each one is the size of a large, round coffee table. I’m done. I’m not gonna, I need to change. And we see this. We go to organizations, and they’re like, “Look, we, our system is kind of klugy We sort of cobble together excel and some other tools, but we can’t do it anymore. Like, we’re buckling now. We’re growing too fast. It’s not scaling for us. We’re ready to take the leap.” The problem with that is that is that is, and look, full confession. We are former consultants, in many ways, we’re advisors to the people we talk to today. They swarm. It’s like, “Ah, it’s time.”

Paul: Got to do something about AI.

Rich: You just mentioned our friend. He’s got a five-year plan, which is essentially code for a ten-year plan, right? [laughter] AI is showing up. Now, is anyone thinking about AI for not the additive that I was talking about before. Not for the, like, smart agent that sits next to me for that one hard step. But rather, can I accelerate the rebuild, like, the full leap across? And I think we are extremely early days for anyone to think that way about it as a path to accelerate. Now, let’s run down the list, Paul. Meeting. Requirements draft. Another meeting. Requirements, draft two. Another meeting. Spec. Designers are brought in. Now they’re in the room. They haven’t designed anything yet, but, boy, they like to chime in. So now designers are in—

Paul: Mood board time.

Rich: Mood boards, affinity diagrams, get the post-its out. A lot of designers we’ve been interviewing lately, they show us pictures of post-its on a wall. I’m like, that’s colorful.

Paul: Yeah.

Rich: Then they go. And then they start sketching. No fancy UI yet. Wireframes. Crude grayscale wireframes. More meetings. Let’s review these. Oh, we have a clickable prototype coming in 90 days, and then we’re going to have that circulate. And then Department X, which is annoyed because they’re in the one office, one floor on the campus that has the worst views, sends you eleven pages of feedback on the prototype. [laughing]

Paul: Hold on, we’re just about to involve engineering.

Rich: Engineering is hovering. Well, one engineer, he’s a data engineer, said, “Well, that’s not even possible.” And he just left the room. [laughing]

Paul: Well, it won’t work. It won’t work with the giant database that we have hosted out of the Delaware data center.

Rich: Yeah, this is anthropological in scale. This is humans. This is how humans express themselves, project their power, show their relevance. And then it’s just these artifacts of communication. And I haven’t written any code yet. I’ve written nothing. Like the engineers, when they come in the room, they look at the pretty pictures that the designers made, and they’re like, well, that’s cute. That’s really cute. Now, let’s talk about scope, and let’s talk about buh buh buh—

Paul: All right, let me. Let me advocate for the audience here. They believe you that it takes too long to build software, and they know that AI is coming into the organization. What is the, make, draw that connection for me. What point are you trying to make?

Rich: I don’t think anyone is perceiving AI as an accelerant for that today. Nobody is perceiving that at all. I think that, you know, AI has been packaged up as these, like, beings that are like really smart and witty and they won’t shut up, but they seem to have know a lot of things—

Paul: I think it’s a big mistake of AI, right?

Rich: That’s how people—so like, oh, wait, I don’t need another person in the meeting. I don’t need AI Joe in the meeting. Oh, I just came up with that. It’s like GI Joe.

Paul: AI Joe.

Rich: I don’t need that.

Paul: I think Apple’s making its moves there, right? Like it’s sort of baked in everywhere and it recognizes of faces, and it gets to know who your cats are in the photos app. Google, too.

Rich: You’re nailing it. Let’s talk about Apple for a second. How they think about AI. They see AI as something that most of their customers will never utter. It will be a smarter, more interesting, more clever phone. They don’t care. They have never been feature-centric because they just want you to find the photo or they want you to. They want to answer your question. And the more they can hide away how they did it, the happier Apple is, right? They see it as an it has to sit inside the context of the experience. That’s how you should think about AI. Not AI-first. Right?

Paul: Why are you and I doing a podcast about technology when no one should care about technology?

Rich: Because I think we. I think we’re special, Paul. I think we’re actually special because we think about technology in a cultural context almost always. And I think that makes us really, really special. [laughing]

Paul: I would say there’s a—I’m glad we’re special. The flip side to that is if technology is the empowering mechanism for people to make enormous amounts of money, and it sways elections and it changes the economy, it’s in everybody’s best interest, and they get more power the more of it they understand. And it actually, it became the kingmaker in the world for the last 20 years.

Rich: It did. And we have, I feel like, two goals. One is to demystify it. People are utterly, they stand down to technology in some—

Paul: [overlapping] They think it’s a wizard.

Rich: Yeah!

Paul: They think their computer is full of little wizards.

Rich: And now AI is here, so there are actual wizards running around. Right? Like, there’s, it’s, that’s where we are, right. And so it’s. It’s gets more and more scary and creepy. Right? And the other bit is, I think I. We love it. We think, if used in the right way, is an incredible agent for change. Right? And a positive change. Like, we pulled that off for years for our customers—

Paul: I still want to believe there’s definitely been some ups and downs over the last few years, but I still do believe this. And I’ve watched there be all these different reactions. And I think there are two major reactions to new technologies in the world today. One is a kind of natural rejection of it as another artifact of capitalism come to take away your privacy and your rights, which is actually, which people think is new, but has been going on for 60, 70 years and longer.

Rich: Yeah, yeah.

Paul: I don’t know if people know, people used to go and they always wanted to blow up the computer during the Vietnam War on campus. So you had the early computer nerds, and then you had the other people who saw it as a tool of the state, because often it was funded by the government. The government funded a lot of early computers. And so, like, this tension’s always existed between this, this is a mechanism of control, and then on the other side, you have the, like, this is the answer to every corporate problem that has ever existed, and it’s absolutely wonderful, and if you don’t get on board, you will miss the gravy train. Again, you fool.

Rich: Yeah.

Paul: Sadly, Richard, I think you and I are technology centrists. We are technology centrist dads, and, which is the least cool thing a human being can be. And yet I do feel called to continue in my role as, like, the Tim Kaine of technology. Remember him? Remember him?

Rich: Yeah, I do.

Paul: He ran with Clinton.

Rich: Yeah—

Paul: That was a cool guy.

Rich: Yeah, that, yeah. Didn’t help the cause there. [laughter] Look, man, I think we love it because we see it as additive to peoples’ stories, individuals’ stories. Businesses don’t care about, like businesses that make a certain product or push a certain craft or whatever tech is like trying to explain to a real estate person that their tech can change their business is like one of the most impossible things.

Paul: Right.

Rich: Because they’re literally moving physical plots of land, right, like that, and they go to mixers and they throw cocktail parties and they stage up houses. So when you tell them you can give them 7% more efficiency, they look at you like you’re crazy, right? And the reason for that is because that’s not their world. And technology is always threatening you. It’s always like, oh, your world’s about to get turned upside down. You thought you had it nice now? You thought you had it in control? You don’t have anything in control because we’re about to unleash the robots. And we don’t like that context, and I don’t think anyone should buy it. Right? Because the truth is the world is incredibly stubborn. It’s incredibly stubborn to the point where I don’t know what percentage of the web still has jQuery embedded in it, but I bet it’s a lot.

Paul: It’s very large. Same as, like, lots of the web still runs on PHP.

Rich: And that’s okay—and you know what? I don’t see that as a bad thing, Paul. I see that as, like, you should see technology as something that needs to come into your world. Your world is the world. And that’s okay.

Paul: Everybody, everybody likes to, well, progress. You can’t make money off of old technology.

Rich: You can’t.

Paul: It’s not exciting. All right, so let me, let me, let’s, let’s frame this for people. You are working, let’s say, as a product manager at a midsize company, and your boss, the CEO or the CIO or somebody with a C walks in and says, “Hey. Rich. Mid-level guy. What are we doing about AI? Can we use this to fix customer support?”

Rich: Such a tough, like, that, that is being put in front of people a lot right now, because there’s look, executives are anxious about competition. They’re anxious about falling behind. And so when that question gets posed, that’s a crazy question.

Paul: Okay, but let’s assume, let’s assume the person on the other side will actually listen to me. Let’s not assume it’s like they’re just going to ruin my life. Like, what do I say?

Rich: Let me give advice to the person asking the question, not to the person that’s responding to it. Saying, what are we going to do about AI? Is like saying, what are we going to do when the aliens land? Like, that’s a, it’s just, it’s an open-ended, banana-cakes question. What you should say is, I’m hearing that there are a lot of opportunities to sort of relieve pain in many parts of this company because AI is doing—I’m seeing some interesting examples out there. Right? I’d love to hear about ways to make us more efficient, find us opportunity, whatever, through AI. Why don’t you think of it that way? Go to, like, the main pain points. Start with the problem. Gosh, we keep losing track of inventory. Do you think AI can help? Maybe not, but at least you’re setting up a context.

Paul: Right.

Rich: What are we gonna do about AI? With apologies to McKinsey, is a banana-cakes question.

Paul: I think this is what’s going on. Right? It’s just like the desire to get connected to the new thing, it gets just sort of machine-gun-sprayed at every single possible problem.

Rich: Exactly.

Paul: You basically just said, hey, I’ve got this new hammer. Can we fix the call center with this hammer?

Rich: That’s right.

Paul: And then your poor head of product, or your tech team has to look at you as the boss and blink.

Rich: Yeah, exactly.

Paul: And take that request seriously. But that’s what they heard. You just came in and said, I have purple nodules, and I would like to turn them into iced tea and and biscuits.

Rich: Yeah.

Paul: And they’re like, what? Why? You know, it’s just utterly bananas.

Rich: So, okay, let us, let us close it with this, you know, just to flex our consulting muscles. We were, we were talking to a potential prospect yesterday, and we spent 90% of the time not talking about technology. We spent 90% of time talking about their problems, like, just about the whole time, and talking about a way out. There’s no—

Paul: And to be clear, we’re not talking. We’re not even talking about Aboard at that point.

Rich: No, we’re listening to them. We’re, like, restating and articulating their pain so that we have a full picture and diagnosis. That is how a conversation should start, whether it’s your boss asking about AI or whatever. It’s like, where is the pain? What have we been living with that can get better?

Paul: This goes back to a larger point, which is rarely has the boss walked around the floor and looked at how the processes actually take place. Right? Like, that’s where you should start. Hey, how does an order go through the system?

Rich: Yeah, that’s right. So plot twists to close out this podcast. Paul.

Paul: Yes?

Rich: The, the Mike from Canarsie?

Paul: Mmm hmm.

Rich: It’s Michael Bloomberg.

Paul: [gasps] No!

Rich: He can get any car he wants now.

Paul: It all worked out great for him. And he was your buddy. That’s crazy because he’s like in his eighties.

Rich: [laughing] It wasn’t Michael Bloomberg. I tried to think of another Michael. Michael Imperioli, of The Sopranos.

Paul: That’s a little more believable, actually.

Rich: Yeah, exactly. All right. Check us out at A lot of what we’re saying here is pretext. We’re thinking about big challenges out in the world and how software can help AI can help us do things quickly. We’re going to talk a lot more about it in the future. But for now, go play with it. Check it out at we’d love your feedback. Reach out at

[outro music]

Paul: Sounds good.

Rich: Have a lovely week.

Paul: Bye.

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