Transcripts
What you have to do now is figure out the edges, how far it can go and where it either fails for you as a company where you don't want to go past or where is the end.
Speaker A:So the failures are actually what's more important to note.
Speaker A:This really was terrible.
Speaker A:This gave me a ton of hallucinations.
Speaker A:This generated the worst code ever.
Speaker A:Those conversations and sharing that is actually really important.
Speaker A:The successes are fun.
Speaker A:The failures are really critical to log somewhere or keep track of.
Speaker B:Welcome to behind the Product, a podcast by Sep where we believe it takes more than a great idea to make a great product.
Speaker B:We've been around for over 30 years building software that matters more, and we've set out to explore the people, practices and philosophies to try and capture what's behind great software products.
Speaker B:So join us on this journey of conversation with the folks that bring ideas to life.
Speaker B:In this episode of behind the Product.
Speaker B:I'm joined by co host Raman Orey and our guest Angie Carroll for a thoughtful and refreshingly candid conversation about the real challenges behind AI adoption.
Speaker B:Angie shares why skipping over AI literacy is a recipe for failure and how, quote unquote, corporate recess can unlock meaningful insights and why blending real world experience with AI fluency is the key to unlocking true potential whether you're in tech or not.
Speaker B:This one's packed with takeaways for anyone looking to lead in the age of AI.
Speaker B:Hope you enjoy.
Speaker A:The reason I think marketing has allowed me to learn generative AI so broadly and so effectively is because it does interestingly encompass all, I say all corners and sides of generative AI.
Speaker A:Because I do have to understand the data side of it and the metrics and the prediction and hypothesis and I have to understand image generation and video generation, I have to understand text generation and prompting and I build AI assistance.
Speaker A:And so when it comes to a category of use, like a department that you would use gen AI across basically all of the generative capabilities, the marketing department is one of the only ones that you can pretty much saturate every gen AI use.
Speaker A:You've got all of the statistical and data points, the ad generation, the AB testing, the prediction, that side of things you've got the creative, the visual, the image generation, the song generation and all of that side of things.
Speaker A:And then you've got the technical builds, the AI assistants, the automations are incredible.
Speaker A:And so, so from a I feel very much like because I came into Gen AI through the lens of marketing and I just went to town, I was just like, okay, what can I learn how can I build, you know, my skills through the lens of marketing.
Speaker A:I just was like, okay, I'll learn that this day and that this day and that.
Speaker A:And I feel like that because of that.
Speaker A:That's why I learned so quickly, so broadly, because it was marketing.
Speaker C:It touches everything, every part of the business.
Speaker A:I didn't stick with just one specific topic.
Speaker A:I just kind of was like, okay, gotta touch all the pillars and, and that.
Speaker A:I learned that way too.
Speaker A:So marketing is an interesting place to start.
Speaker C:So one of the reasons why I thought it'd be fun for all of us to chat.
Speaker C:So you two were supposed to be part of a panel together, but inclement weather prevented that.
Speaker A:Ice storms in Indiana.
Speaker C:I know, stupid Indiana.
Speaker C:And it's weather patterns.
Speaker C:I thought it was really cool the way that you kind of couched the panel at the beginning of that where you talked about kind of like three main buckets of AI.
Speaker C:AI as a product, AI as an enabler or business enabler, and AI as a productivity tool.
Speaker C:So, you know, there are three basic rubrics.
Speaker C:Obviously it's more complex than that.
Speaker C:And there's probably more than three buckets.
Speaker C:I think that's a good, that's a good framework.
Speaker C:And I thought that couching that would be a great way to kind of frame our follow up conversations since you weren't able to be a part of the panel.
Speaker C:But it'd be fun to kind of bring that voice.
Speaker C:Voice together.
Speaker D:Yeah.
Speaker C:And you can go listen to that show maybe somewhere, I don't know.
Speaker C:But everybody's gonna be able to hear about your perspective.
Speaker C:So obviously, as you just talked about a minute ago, your kind of foray into into AI started through the lens of marketing.
Speaker C:That's a deep focus for you as a professional.
Speaker C:And by going in super deep, it's allowed you to kind of like broaden your exposure in the AI world.
Speaker C:How would you define kind of your passion area for AI?
Speaker C:It's not necessarily just marketing anymore.
Speaker C:It's now broadened into other areas of business and maybe even product development.
Speaker C:Like, what would you tell folks?
Speaker C:Is your passion area in the bucket of AI or which one of those three buckets do you feel like you must align to?
Speaker A:I have sort of two focuses.
Speaker A:I would say passion areas.
Speaker A:Oh, that's so hard because I know, and my personality is so multifaceted.
Speaker A:But I would say if I have to pick a passion, it's AI literacy.
Speaker A:Because as I went through, I've been in AI adoption consulting for the last three years and I have learned that fundamentally the cause of failure in corporations is not focusing on literacy.
Speaker A:That's my opinion.
Speaker A:People want to get the big wins fast and they bypass the teaching of the basic fundamentals of what generative AI is.
Speaker A:Productivity gains, efficiency gains at a task based level because they want to reach for the pie in the sky goals.
Speaker A:And so early on I started saying, listen, if you're working with me, we are doing a intro to generative AI workshop in the very beginning.
Speaker A:We are getting everybody at a baseline understanding of what generative AI is.
Speaker A:I talk to people that you would think know the difference between AI, you know, machine learning AI and generative AI that would say like what is ChatGPT and is that the same thing as robots?
Speaker A:You know, I would literally get these questions and you cannot be successful in an AI adoption strategy unless people understand what that is.
Speaker A:So I guess as far as like implementation of an adoption strategy, literacy is my passion project.
Speaker C:And would you say if I park on the literacy piece?
Speaker C:So it's about what, defining what is gen AI in the first place versus other buckets of AI.
Speaker A:It's not about defining what it is.
Speaker A:It's about teaching people so that they can make the steps towards using gen AI because fear is the barrier.
Speaker A:So everybody describes generative AI with human characteristics like it's intelligence.
Speaker A:But when they realize that it's just a computer doing what a computer does at a speed and scale that we can't comprehend, then they don't fear it as much.
Speaker A:That basic understanding of what is generative AI, what is the computer doing to create the results.
Speaker A:When you type in a sentence and you get a sentence back, it's just prediction and pattern.
Speaker A:And when they realize that and then they break through the barrier of fear, they start using it.
Speaker A:And so it's like the literacy side of things is about teaching, you know, what generative AI is and just that basic understanding to reduce the barrier of fear and allow people to start their own learning journey.
Speaker A:It's like that corporate America is one thing and then there's individual learners that are another journey.
Speaker D:When you start an engagement with a group, can you tell?
Speaker D:Like are there some tells that oh, they've missed the literacy step and I can see that.
Speaker D:Are there any kind of obvious signs to you?
Speaker A:I will say that almost no one has a literacy strategy in place.
Speaker A:So if they have, you know, their hand raisers like we have, I have worked with people that have the teams in place and there are some higher tech companies that are full speed ahead.
Speaker A:They're doing A great job.
Speaker A:But the companies that need help, and need help by, you know, from people like me, generally they've got the hand raisers that are using AI and they're using it well.
Speaker A:But then there's a large portion of their organization that doesn't even know that there's hand raisers using gen AI or the part of their organization is using their own ChatGPT accounts, not telling anyone they're using it.
Speaker A:So I would say, to answer your question, almost no one has a literacy strategy in place yet that I work with.
Speaker A:If anything, their strategy is what I'm calling like the dabbling strategy.
Speaker A:And it's easy, it's, it's as simple as just doing, you know, this structured approach to making sure that everyone has a baseline understanding.
Speaker A:There are companies that are on that upper level that were early adopters and I'm sure have the core.
Speaker D:So it's interesting you'd say that.
Speaker D:So for the last, I'd say six to 12 months, SCP has been on this journey to get adoption.
Speaker D:And part of our challenge has been we can't, we couldn't for a long time use like AI code assistance on our production work because of IP concerns.
Speaker D:Like we build other people's software, we have to be good stewards.
Speaker D:And so we were encouraging people to do things on their own, but they couldn't do it at work.
Speaker D:And then we did start to get them do it at work.
Speaker D:And it's not what you might expect from a building full of brilliant people.
Speaker D:You still have all the same distribution of personalities and readiness to change and openness and literacy like the software skills are.
Speaker D:They don't necessarily buy them anything.
Speaker D:They may know exactly how it works, but that it's not the same as the literacy you're talking about.
Speaker A:Are you getting fear?
Speaker D:I think what you're talking about is universally useful.
Speaker A:Are you getting fear of.
Speaker A:Fear of job displacement?
Speaker D:For sure.
Speaker D:For sure.
Speaker D:I put it here.
Speaker D:So I almost one day sent an email and just said, hey gang, go do this, go do some stuff.
Speaker D:And I had gotten some wins of teams that were having some reaction to the idea.
Speaker D:And I thought, and it just, it hit me all of a sudden like this is like every other substantial disruption.
Speaker D:You have early adopters who are the hand raisers, super excited.
Speaker D:You have a big group in the middle who's open and ready whenever you tell them.
Speaker D:You have the passive resistors, please don't make me change.
Speaker D:And then you have the people for whom like is this an existential threat?
Speaker D:Or this thing that I love to do.
Speaker D:And each of them, like, that's where I say it's universally useful.
Speaker D:I don't care if you have a building full of PhDs or you have a building full of machining factory line folks.
Speaker D:You have the same distribution of style.
Speaker A:That's interesting.
Speaker A:I think that with literacy, so I start with people, and literacy is a part of my people bucket.
Speaker A:And alongside the literacy effort goes the culture transformation piece.
Speaker A:And that is where leadership has to go into it, ensuring that we will put a human centered approach first and there will still be people.
Speaker A:And you have to, you know, and I don't want to get like flu, flu, but you have to.
Speaker A:I don't know what the right word is, but you have to embrace the people that we really are dedicated to, the work that they do and because their heart is in it, don't want to give it up to AI, that marketing people who love what they do.
Speaker A:Because I did a talk with a group of writers and I said, you can keep the core of what you love to do yours, but you need to make sure that you carve out everything around that to be augmented with AI or you will lose track of your edge, you know, your competitive edge, but you can still keep.
Speaker A:So if you're writing your first draft is what serves your soul.
Speaker A:You write your first draft every single time.
Speaker A:And I've learned that developers are similar to artists, that they have their way of craft.
Speaker A:It's a craft.
Speaker A:I did not know this.
Speaker C:Yes, it is.
Speaker C:We have a kind of a phrase of what I would call our makers because they make.
Speaker C:They make software.
Speaker C:They're craftspeople.
Speaker A:In my journey around the tech space, I've learned that they consider themselves artists.
Speaker C:Yeah.
Speaker A:And I feel that they probably protect their craft with.
Speaker A:And so what they, you know, chisel down to why, what it is that makes that, you know, serves their soul.
Speaker A:But like, as a company, you know, you do have to like those people that are holding on for dear life.
Speaker A:We have to figure out why and what it is.
Speaker A:Because if they're the best employees, then we have to serve that.
Speaker A:But they will eventually come along.
Speaker A:But it's like the literacy piece is for me what starts the process of getting the people adoption that people, that culture buy in.
Speaker A:And that starts with leadership and so forth.
Speaker C:I love how you're kind of describing this idea of there might be friction, but there might be a place to play.
Speaker C:Like where to use SCP as an example.
Speaker C:We might say, all right, folks, we now have available these set of tools, GitHub Copilot, ChatGPT, and Figma AI.
Speaker C:I don't know, I'm just, I'm just picking things and those are in the buckets.
Speaker C:And then there are some folks who are like, man, I, I really like this part of my job.
Speaker C:What are you trying to balance this idea?
Speaker C:It's like, that's great.
Speaker C:Like, hold on to that, but don't fight against all the other ways that these tools can help you.
Speaker C:Otherwise you will, you'll, you'll lose your edge over time.
Speaker C:I think that's a really cool way to try to weave kind of the current state of AI tools and identity together.
Speaker A:We need to remember that we control AI.
Speaker A:We are in a world where every headline is talking about how it can solve every problem, but we are in charge.
Speaker A:And as company owners and leaders, leaders need to give the employees grace to allow themselves time to figure out where it sits with them.
Speaker A:And that is giving them time to play with it, understand how it works, understand how it fits into their workflows, fits into their processes, give them experimental projects and challenges and make it fun.
Speaker A:And then through that process, they can make peace with what the new life looks like, you know, on the other side of it.
Speaker A:But yes, it's a transformation.
Speaker A:Just like Caterpillar, Butterfly.
Speaker A:Like, it is a transformation here I'm flu, flu again.
Speaker A:But like companies that see and understand that and are able to let employees that need that go through it will retain their employees, you know, make and, and on the other side of things, everyone will be happier, but everyone's in a rush to adopt and it's, you.
Speaker D:Know, I want you to react to a statement I've made around here.
Speaker D:And I'm curious on your take, because this is, this is your space, right, folks adopting.
Speaker D:A thing we have said to our folks is we got permission to start using the tools for our production.
Speaker D:And so the floodgates are open.
Speaker D:But that doesn't mean anybody knows really how to do it.
Speaker D:Yes, I was experimenting or practicing.
Speaker D:That's not the same as my actual job.
Speaker D:And what I've said to them repeatedly is they, there's no best practice yet.
Speaker D:No one knows how to do it.
Speaker D:You're not behind.
Speaker D:So relax, experiment, share with each other.
Speaker D:We'll figure it out.
Speaker C:Right?
Speaker D:How does that land with you?
Speaker D:Do you agree or disagree on the best practices perspective?
Speaker A:I love just experiment and share.
Speaker A:I call it corporate recess with my clients.
Speaker A:Just give them corporate recess, tell them, go play.
Speaker A:And recently, this is not my idea, so I can't take credit, but I totally started doing this or suggesting this.
Speaker A:There's a book, it's called the Toilet Paper Entrepreneur by Mike McKellar.
Speaker A:You probably will have no reason to read it.
Speaker A:But the premise behind is very universal.
Speaker A:You restrict people, they're innovative, you restrict the resources of people and they become more.
Speaker A:So corporations have started sort of giving teams challenges, but restricting.
Speaker A:So you can only use this, this, you can have this budget, you can only within these parameters and you have to produce a result.
Speaker A:And forcing people to use AI to do X, Y, Z in this period of time.
Speaker A:So it's an absurdly short period of time if it's budget related.
Speaker A:Absurdly small budget.
Speaker A:But it's a fun project and it forces the team to use an AI product to get the job done.
Speaker A:Expedited way of learning how to use something.
Speaker A:And then everybody sort of shares what they've learned and how they did it and if they accomplished their goal.
Speaker A:So I think like creating fun exercises like that within corporate environments to make it playful.
Speaker A:And then sharing is everything because people think.
Speaker A:And I've done this all along.
Speaker A:Sharing success is great, but sharing failure is even more important because with AI, it used to be where I used to say, let's figure out what it can do.
Speaker A:Like, rewind my life.
Speaker A:Three years ago, I used to sit with corporate teams and say, let's talk about what you want to do with AI and see if you can do it.
Speaker A:Now it's just like, what do you want to do?
Speaker A:We'll figure out how to do it.
Speaker A:Like it literally can do anything.
Speaker A:What you have to do now is figure out the edges, like how far it can go and where it either fails for you as a company, where you don't want to go past or where at the end.
Speaker A:So the failures are actually what's more important to note.
Speaker A:This really was terrible.
Speaker A:This gave me a ton of hallucinations.
Speaker A:This generated the worst code ever.
Speaker A:Those conversations and sharing that is actually really important.
Speaker A:The successes are fun.
Speaker A:The failures are really critical to log somewhere or keep track of.
Speaker C:That's really interesting.
Speaker C:This makes me think of something that you've helped Robin, you've helped me understand around when using some of these tools.
Speaker C:It's really important.
Speaker C:And I know you got this from somebody else, I think at least to know when it's wrong.
Speaker C:And if you step outside your core core competency, like that becomes harder and harder and harder to do.
Speaker C:Like, I'm a business guy who has worked in tech and I'm like technical.
Speaker C:I have never been a software engineer.
Speaker C:I have done some scripting and learned some coding.
Speaker C:I should never be able to evaluate whether or not this code generator is good or not.
Speaker C:You know what I mean?
Speaker A:This is a major problem with everybody right now, what you're explaining.
Speaker C:Yeah, I don't know, Remy, did I quote you?
Speaker D:Well, yeah, and it's a funny nuance.
Speaker D:We write automated unit tests for software.
Speaker D:We do that because it's not unusual for your project to get to 500,000amillion lines of code.
Speaker D:It's big, it's complex, it's just hard to think of everything.
Speaker D:And so we write automated unit tests to make sure it does what we thought it did.
Speaker D:The ironic thing here is that's what makes AI useful for software development.
Speaker D:Because I can an automated way figure.
Speaker C:Out if it got it right.
Speaker D:Now if I ask the AI to write a legal agreement for me, there's no automated unit test for that.
Speaker A:No.
Speaker D:If I ask it to come up with a creative campaign, that's even more like, that's in the realm of taste and audience, buy in and brand.
Speaker D:Like how.
Speaker D:Maybe this goes back to your literacy point.
Speaker D:That's the internal literacy.
Speaker D:Like, oh, it does a great job at this.
Speaker D:Yes.
Speaker D:But here's the edge.
Speaker D:Well, you should be suspicious.
Speaker A:Yes.
Speaker A:And this is where I get very.
Speaker A:Like the kids these days.
Speaker A:No.
Speaker A:The people are so trained to think that young kids graduating from college are so adept at using tech.
Speaker A:Right.
Speaker A:So there's this feeling that everyone that's graduating is going to be using AI very well.
Speaker C:Fluently.
Speaker A:Fluently, yes.
Speaker C:Yeah.
Speaker A:The fact is that they have no real world experience.
Speaker A:So a marketing professional that graduates with a marketing degree using generative AI.
Speaker A:Generative AI is so agreeable and it's generating strategies, like a hundred strategies in three minutes that all sound like they are perfect and going to be super effective.
Speaker A:But that marketing professional has absolutely never worked with another human being, maybe an internship.
Speaker A:So you take that person using ChatGPT or someone that's been in marketing for 20 years and you are going to get extremely different results with the generative AI outputs.
Speaker A:The fact right now is what you're saying is you've got a challenge that you can present the AI to know whether it's right or wrong with something that doesn't have that yes or no answer, then the human has to make the decision and that human has to have real world experience and knowledge because the AI wants to please.
Speaker A:And especially right now, with my gosh, it's just, it can just like generate, generate, generate.
Speaker A:And you've got These people that are just like using it and they're claiming to be experts.
Speaker A:I'm an expert marketing director, I'm an expert AI consultant.
Speaker A:Now I'm an expert this, I'm an expert that because they've got the resumes to prove it.
Speaker A:But they generated their resumes in ChatGPT.
Speaker A:And so yes, it's a big problem.
Speaker A:I talk about talent and hiring talent and what employers are going to need to be looking for in the next few years, if not the next three months.
Speaker A:But this is going to be hard for employers.
Speaker A:They're going to have to hire on soft skills and really do testing inside.
Speaker D:Before they hire, maybe even compounding it in this moment.
Speaker D:And I think this will get resolved.
Speaker D:But right now higher ed doesn't know what to do either.
Speaker D:So the graduating seniors may have exposure to these tools, but it isn't because the education program they went through was ready to use them in a smart way with their traditional curriculum.
Speaker D:So they may not know their actual curriculum as well as they should.
Speaker D:And they're not great at using these tools to solve the problem.
Speaker D:Like it's a double.
Speaker D:Like it's compounding the problem.
Speaker A:Absolutely.
Speaker C:That's really interesting.
Speaker C:Like they haven't really, like educators haven't really caught up to figure out how to properly teach these things.
Speaker D:They are going through the same disruption every other knowledge work is right now.
Speaker D:There is no best practice.
Speaker D:Nobody has figured out how to do this well.
Speaker D:And so some have their head in the sand, others are trying things, but they're trying.
Speaker D:It's unevenly distributed.
Speaker C:It's.
Speaker D:Yeah.
Speaker C:Interesting.
Speaker C:Well, and it's, and it's like a.
Speaker C:Here in kind of like what you each were talking about.
Speaker C:Like it's really important to bring experience and AI fluency together for you to supercharge without both components.
Speaker C:It's really hard to allow these tools to be very effective.
Speaker C:That's what I'm hearing in the current state.
Speaker A:What I tell people is you can get either really really great outputs or average outputs.
Speaker A:The average outputs can be.
Speaker A:Anyone that knows how to use AI can give you average outputs.
Speaker A:But if you want to get really great outputs, you have to have not only the skills to know how to use the AI.
Speaker A:Prompting is still very important.
Speaker A:And the knowledge of the use of the market, if you're using it for marketing, you need to be a marketer to get excellent results.
Speaker C:If we kind of compare and contrast these two worlds, let's say I'm a 20 year professional, still haven't really gotten super deep into Gen AI and I've got somebody right out of college that has some exposure to your point, some exposure to AI tools but I don't have a lack world experience.
Speaker C:Do you give each of them different advice like what do we start to create that baseline or what do you do with that?
Speaker C:Like what's the hope and the action for folks in those camps, both of you?
Speaker A:There still has to be like in development and developer world there still has to be people in this space that understand how to manually develop.
Speaker C:Yes.
Speaker A:And because you can't just have someone come into a company and jump into using only AI to develop.
Speaker A:I mean in marketing there still has to be people that understand the human connection with why you create campaigns the way that you do.
Speaker A:I don't know how it works exactly but I don't think the human element will ever be non existent out of and and I think the way we learn marketing and develop it will have to have a hybrid approach.
Speaker A:I'm not like one way or the other.
Speaker A:I do think that they marry and it becomes like a process that we overlap and some things are completely, completely taken off the plate with AI like so that it does allow for more time to be a more effective marketer to learn better, to learn how to create more effective campaigns and so that the junior level marketers can become highly effective marketers way faster.
Speaker A:But it doesn't just happen, you know, they still need taught by someone that really understands you know what's happening from a human standpoint.
Speaker C:Well that's interesting.
Speaker C:I've heard of some companies that are creating products that you know as some of their kind of go to market marketing messaging is about like well this supercharges the senior rep so they don't need all the junior reps. Like that's a great short term outcome there.
Speaker C:But what are you going to do 20 years or 10 years when you need the next generation of senior folks equipped?
Speaker C:What do you do?
Speaker C:It just seems like it's such a short sighted goal.
Speaker A:I don't know, maybe they're building AI assistance to manage all of that.
Speaker A:Yeah, I think there's a lot of people that aren't thinking through the entire ecosystem of AI right now and they're just jumping ahead and I mean there's a lot of people that are trying to take advantage of the opportunity that exists.
Speaker C:Absolutely, that's always true though that's not unique to AI.
Speaker A:The passion, I mean the literacy, the people, the human.
Speaker A:I love building, I love building solutions and finding things that people need and building and Serving that to people and saying, even to friends and so forth.
Speaker A:So there's so many opportunities.
Speaker A:And I think that we're in the very, very beginning of the people that see the opportunities that exist.
Speaker A:I think there's going to be a whole lot of snake oil salesmen out there.
Speaker C:I think they're probably already there.
Speaker A:They're there, but I think it's going to be so saturated in the next, you know, year two, three.
Speaker A:So we'll all have to be aware.
Speaker D:I want to go back to something you said before.
Speaker D:You've talked about starting the program with literacy when you're working with a new cohort.
Speaker D:And then you've mentioned leadership a few times.
Speaker D:Say more about that.
Speaker D:What does leadership need to do well to support these initiatives?
Speaker C:Asking for a friend, asking.
Speaker A:I have a, you know, a little postie on my computer that says you don't have to be in tech to be an AI leader.
Speaker A:I think that leadership looks different than in the AI world than it does in other technical spaces.
Speaker A:I think with this, you have to support your people.
Speaker A:You have to let them know and be the person that states that, that you are looking out for their best interests.
Speaker A:In a world where knowledge work is looking like it could easily be displaced by AI, I think you have to approach it with, you know, very rigid policies and ethical and responsible use guidelines so that they feel protected in what they can use and they understand their edges.
Speaker A:Like, they understand I can go and I can play all day because I know that if I go too far from home, I can get back safely.
Speaker A:You know, like, I think you need to have really solid ethical and responsible use policies well communicated through the company.
Speaker A:But more than anything, you just need to be positive and speak about it transparently and communicate it through the company in a very honest way.
Speaker A:And I think not only to your employees, but to your clients and the public, it's quite simple.
Speaker A:I mean, empathy, like the human skills that we all have and need, we need to tap into those and we need to use those to lead the AI revolution.
Speaker A:But I think like most employees that won't.
Speaker A:I, I will never forget, I sat with a CEO and very first, one of the very first people that I ever worked with said, oh, none of my people are afraid.
Speaker A:He's a great leader.
Speaker A:Sure, great leader.
Speaker A:None of my people are afraid that I would let anyone go.
Speaker A:Did a survey, success metrics, you know, we take those and see what will make the people happy with their jobs.
Speaker A:And literally 60% of the workforce was afraid of job displacement.
Speaker A:If they adopted AI, but leadership did not think that that was even a concern because they had a solid grip on their leadership and it was a great leadership program.
Speaker A:So even if you think that your people are, you know, okay and comfortable and happy, they have deep seated fears right now.
Speaker A:And so coming out and saying, I know that even if you're not saying it, you probably fear that your job is at risk of being displaced right now.
Speaker A:And we are going forward with a human first approach.
Speaker A:You know, we want to, like I tell people, tell people you want to scale and you don't want to hire anyone, you want to grow, you want to double in size without hiring another person because of AI, that's okay.
Speaker A:But you don't want to double in size and fire half of your workforce.
Speaker A:Just like reassuring people just the things like saying we will protect what makes you love your job, we will work to protect that.
Speaker A:We aren't forcing it on you.
Speaker A:We are making sure that we create an ecosystem that allows you to adopt in a place that you feel comfortable in.
Speaker A:And I, I help companies write communication plans that express that because it's not always something that is natural to the executive suite.
Speaker A:You know, it's unsaid.
Speaker A:Like a lot of what people are feeling is just unsaid said and that sigh of relief, creating a space where people can say, I'm uncomfortable.
Speaker A:That's good.
Speaker A:You want people to express their fears.
Speaker A:It's good.
Speaker C:Is there anything about this moment, just in our world around AI that's different from a past big change?
Speaker C:What I hear a lot, like, don't make assumptions, Go find out what people are actually afraid of.
Speaker C:Be human about it and empathize with where they're at.
Speaker C:Try to assuage fears, be data driven.
Speaker C:Data driven and bidirectionally.
Speaker C:Is that unique to AI or is are we just in another acute moment and AI happens to be the topic that's forcing the discomfort?
Speaker D:You know, like my take is just humans only process and change so fast and we've never had a technology disruption that was fast, so.
Speaker D:Oh, that's interesting.
Speaker D:Everything you said I think is kind of classic organizational change management.
Speaker D:Good leadership, right?
Speaker D:Like we've been taught this stuff, it's not a new idea.
Speaker D:But this is all just this tidal wave is hitting us and it's hard to reground yourself.
Speaker D:This is the fundamentals, this is how we do it, this is how we lead.
Speaker D:Because we're also processing in this moment.
Speaker D:Does this mean for me?
Speaker D:And yeah, I don't have the answer either.
Speaker A:A hundred percent.
Speaker A:This speed at which the change is happening is incredible.
Speaker A:And if you look at the timeline in which other change has happened, I don't remember the exact numbers, but like the telephone, it took 76 years for 50 million people I think to adopt the use of the telephone.
Speaker A:And I think it was 13 years for the use of the radio, the adoption of change.
Speaker A:And I think it was like, even with Facebook, it was something like five years for 50 million people to use social, like Facebook social media.
Speaker A:Even that changed.
Speaker A:It was a half a year for 50 million people to use ChatGPT.
Speaker A:So if you look at the condensed, just like you said, the speed at which adoption has happened is enormous.
Speaker A:But also on top of that, this is knowledge work.
Speaker A:Nothing against blue collar change, but this is PhD level people that are looking at job displacement or a threat to what they have worked.
Speaker A:And also this is affecting every industry in every city, all over the world.
Speaker A:This is not just in the Midwest, United States of America where we're putting down a railroad line.
Speaker A:This is every city all at once.
Speaker A:All at once, all over the entire world.
Speaker C:Interesting.
Speaker C:I haven't thought about how acute the moment is.
Speaker A:Yes, acute, yes, it's intense.
Speaker A:And there's very few people out there that are sort of leaders in helping us understand.
Speaker A:You know, I have a handful of people that I follow that are helping me lead other people.
Speaker A:It's happened so fast.
Speaker C:I want to like shift our conversation more to hope.
Speaker C:Let's look ahead, you know, so if you find yourself in a conversation with a CEO, a CMO marketing background, let's give it a lens, a leader that you're advising and it's like, okay, they're just getting started with Gen AI world thinking about adoption across the organization.
Speaker C:We've already talked about literacy, human element.
Speaker C:What are the first like three steps that you would tell this person?
Speaker C:Okay, here's how we're going to move forward and here's why it's going to be hopeful, why it's going to be good.
Speaker C:Where's your head go in that circumstance?
Speaker A:The hopeful thing or the great thing is it's very, very simple to learn.
Speaker C:Simple to understand, hard to adopt.
Speaker A:Maybe generative AI is a very simple tech to learn.
Speaker A:The use cases are hard to identify, but once the use cases are identified, teaching the people in the company how to actually use the technology is very, very simple.
Speaker A:So it's just that the use cases are hundreds of thousands of use cases and the productivity gains for the use cases are enormous.
Speaker A:How I start is with a literacy effort and Then I just identify with one department first.
Speaker A:Very simple, the highest efficiency gain, use cases for the lowest effort.
Speaker A:This is so simple.
Speaker A:Highest impact, least lift, lowest lift.
Speaker A:And so we identify literally maybe six to eight use cases within one department of generative AI.
Speaker A:And I mean almost all the times these are like whatever people are using or chatgpt text based.
Speaker A:This is so simple.
Speaker A:Like it's just that people need guided and told what to do.
Speaker A:So I talk to these people, I do an impact assessment and I tell them, okay, here's where we're going to start.
Speaker A:I'm going to teach you how to automate this, generate this with AI, organize this and do this.
Speaker A:That's it, that's all we do.
Speaker A:And then I map the solutions, call it solution mapping and I train them how to do that.
Speaker A:Then I make sure that they do that.
Speaker A:That ends right there with most people, okay, I've been told how to do it and then they never do it.
Speaker A:And so I make sure that they do it.
Speaker A:Once that happens, people get super excited.
Speaker A:I mean we're seeing like 70, 80% efficiency gains with that.
Speaker A:That's it, that happens.
Speaker A:They start doing that, share your wins.
Speaker A:They start talking to other people in other departments.
Speaker A:People are like, oh my gosh, I want a piece of that.
Speaker C:Yeah, corporate recess, yes.
Speaker A:And then people are like, I want a corporate recess too.
Speaker A:But we're talking that part is a month, that's it.
Speaker A:And so you get the momentum going.
Speaker A:I call it the next month is the quick wins month, executive buy in.
Speaker A:That's when you get the executive to say, okay, yeah, we can start taking this seriously.
Speaker A:And then I start basically a more strategic adoption cycle where I do an education, just a literal cycle where I do an education focus and then a very strategic cycle that I each month for adoption.
Speaker A:But it's actually quite simple.
Speaker A:The hope factor is that most corporate employees have more on their plate than they can handle right now.
Speaker A:And this simply, it makes the people to the point that they can walk out on a Friday and they have their checklist ticked off.
Speaker C:I wonder what that feeling is.
Speaker A:They've checked their emails, right?
Speaker A:They've checked their emails.
Speaker A:They don't have to check in on the weekend right now.
Speaker A:I mean right now.
Speaker A:It's that simple.
Speaker A:And it's a matter of these really easy task based use case adoption level stuff right now.
Speaker A:I mean in the end we have companies that really want to reduce employee work days.
Speaker C:Like go to a four day work week kind of thing.
Speaker A:Go to four day work.
Speaker A:I have a company that wants to offer geriatric.
Speaker A:Like leave for parental care.
Speaker A:Parental care.
Speaker A:Geriatric care.
Speaker A:Yeah.
Speaker A:Like, you know, there's innovative things that corporations are thinking of if they do free uptime for their employees.
Speaker A:There are ways of compensating.
Speaker A:And I do think, just as a my.
Speaker A:This is what I want to be known for maybe, is the companies that lead the charge and doing these innovative things when they do have these efficiency gains will attract the best talent and they will produce the best results for their services.
Speaker A:And if they attract the best talent, they will get the best clients.
Speaker A:And so they will grow the fastest and they will then be able to take out their competition.
Speaker A:I want my companies that I'm working with to have that, you know, we're talking years, but I want them to have those types of goals on their radar instead of announcing that they're reducing their workforce by 50%.
Speaker A:But I also don't work with the Dells of the world and the, you.
Speaker C:Know, so no mag sevens.
Speaker A:Yeah.
Speaker C:I love how there's this beautiful picture and then it's.
Speaker C:The outcome is.
Speaker C:Crush the competition.
Speaker A:Yeah.
Speaker A:Oh, yes.
Speaker A:Yeah.
Speaker A:You know, it's hope.
Speaker A:Hope is crushing the competition in the world of marketing.
Speaker A:Sorry.
Speaker C:I love it.
Speaker A:I don't.
Speaker A:I still have a competitive.
Speaker C:I'm one of the competitive people in the building.
Speaker C:There's not many of us.
Speaker A:Yeah.
Speaker A:I'm always crushing the competition with.
Speaker C:In the end, I love it.
Speaker C:All right, as we wrap up, any spicy takes that you want to throw out into the world, listen to either one of you because, Remin, I can sometimes count on you for a spicy take.
Speaker C:Sure.
Speaker A:Spicy take about what?
Speaker C:Germane to the conversation.
Speaker A:We're like our best friends.
Speaker C:Yeah.
Speaker C:Yeah.
Speaker C:Germane to our conversation.
Speaker C:Yes.
Speaker D:You want my spicy take?
Speaker D:Yeah.
Speaker D:Just familiar with D idea of an S curve.
Speaker C:Right.
Speaker D:Things are slow, then they're fast, then they're slow.
Speaker D:And that last 5 to 10% is very expensive.
Speaker D:Whatever it is, whatever you're trying to optimize or do.
Speaker D:This idea that we should try to replace all the knowledge workers.
Speaker D:Like, okay, now we're in the fast part.
Speaker D:Maybe we're not.
Speaker D:Maybe it's still coming.
Speaker D:But we need to get to a hundred percent and then have less.
Speaker D:Why?
Speaker D:Why don't we just get the win, call it at 90, leave that last 10% for professionals to do what they love to do, what they're great at, what they're differentiate on.
Speaker D:And these tools make us more like we're aiming for the wrong goal.
Speaker D:Here's my spicy take.
Speaker C:I like that.
Speaker C:That's a good spicy take.
Speaker A:I'm gonna just piggyback on his spicy take instead of throwing my own in the mix.
Speaker A:But I've always been a stop at 80% type of person.
Speaker A:Like, and with AI even the out, like everything.
Speaker A:If you get to an 80% output that you're happy with, take it from there.
Speaker A:As a human, like, I like that, but I don't.
Speaker A:I don't know.
Speaker A:I don't really have a spicy take.
Speaker C:And you throw a couple in here.
Speaker C:I've taken notes.
Speaker A:Yeah.
Speaker A:Oh, and just add those on as pss at the end.
Speaker C:We'll reference them in our intro.
Speaker C:Well, I appreciate you spending time with us, Angie.
Speaker C:This was a lot of fun.
Speaker A:This was a fun conversation.
Speaker C:We deviated from my show notes completely and I'm really glad that we did.
Speaker A:I feel so gypped.
Speaker C:It was good.
Speaker C:Thank you so much.
Speaker A:Thank you for having me.
Speaker A:This was a. I love this conversation.