How to Become the AI Early Adopter

Your company is counting on early adopters and innovators to take the reins with AI.

How do you become one of these intrepid souls leading the charge?

And are there any downsides of being one of the first to get started with AI?

Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era.

As always, I’m joined by Knownwell CEO, David DeWolf, Chief Product Officer and Chief Technology Officer, Mohan Rao, and Chief Strategy Officer, Pete Buer.

We also have a discussion with Djan Turan about becoming the innovator your company needs.

But first, break out those mosquito nets.

You know what’s coming, because it’s time for another AI in the Wild.

Pete Buer is back for another installment of AI in the Wild.

Hey, Pete.

Hey, Courtney, how are you?

I’m doing good.

Okay, so you’ve probably noticed, Pete, especially you, because you’re in the DC area, a little outside, but you’re in the orbit of DC, and it is election season, my least favorite years of the years.

So for better or worse, it seems only fitting for a Wyoming man to be pushing to get AI on the ballot to become mayor of Cheyenne.

Pete, what can you tell us about what’s going on here?

So Cheyenne resident, Victor Miller, he’s trying to get his creation called Vick, virtual integrated citizen, onto the mayoral ballots.

The question that sits at the center, could AI actually do the job of making good, fair decisions about complex challenges involving people?

A recent Pew Research Center study tells us that while 28% of Americans say no and 41% are unsure, fully 30% of Americans do believe AI can be designed to consistently make fair decisions in complex situations.

In other news, another recent Pew study gives us insight into our trust for politicians to do the same.

Only 16% of Americans trust the government to do what’s right most of the time.

So I know, not the same study, not the same people, but kind of funny, kind of telling to see the two stats side by side.

All of that said, my take on the question is that however dismal our outlook on government these days, AI independently running the show is just not the answer.

Too much hanging in the balance of life or death leadership situations involves relationship, counter intuition, judgments, gut, heart, and that’s still the domain of the human.

But is there a supporting role for AI in government to help make it make us better?

Heck yeah, and Vic is my co-pilot for instant research to get up to speed fast on a topic, to crawl through reports from my constituency to understand what needs across that group happen to be and to digest the 5,000 page report that gets dumped on my desk the night before.

We have to make a decision on the central question in committee.

So anyhow, while I don’t see AI as right answer on the ballot anytime soon, a little competition for the humans wouldn’t be such a bad thing.

Maybe we’d show up a little less cringey at debate time.

Maybe we’d be held to a higher standard.

On actually knowing our stuff and knowing our people.

And maybe we’d stay a little more true to the goal of democracy, which is about letting the truly best ideas win.

So obviously this one probably isn’t the right time for AI, but very interesting to think of how AI might play a role in government in the future and make everyone’s lives better.

Pete, thank you as always.

Thank you, Courtney.

We’ve talked on previous episodes about identifying those early adopters of AI in your organization and elevating and empowering them.

So how do you become one of these early adopters that’s driving innovation with AI in the first place?

I chatted with David DeWolf and Mohan Rao about that very topic.

David, Mohan, we have talked several times on this podcast about identifying the early adopters in your organization.

And how to elevate them and empower them.

But I want to start with a more basic question because I think there are quite a few people looking at what’s happening with AI and kind of questioning, okay, how do I become an early adopter?

How do I become the person in my organization that’s actually helping drive innovation?

So can we just like break it down from the very base?

How do I know if I’m an innovator?

How do I deploy that in my organization?

What does that look like just practically, especially for people that I think a lot of times we associate innovation with AI as like a technical thing.

And we all know that it’s not.

So let’s get into it.

Where do you think people should start from?

Yeah, you know, it’s an interesting question because I think there is a how to it and you can learn to do it better.

I also think that there are individuals who are naturally inclined, get passionate about, are emotional about wanting to leverage the latest and the greatest, right?

We’ve all met that person who sees technology comes out and just has to try it before everybody else, right?

And I do think some of that is a personality thing.

And so I love the fact that you asked about early adopters as opposed to those leading edge, cutting edge innovators, right?

If you go back to Geoffrey Moore’s Crossing the Chasm and understanding the infusion or the diffusion of innovation, you know, it typically starts with those early innovators.

I’m not sure that you can train that.

Maybe you can discipline yourself into trying things.

But when you talk about those early adopters, I think it is first and foremost kind of doing the research, spotting the trends.

I think people that are attached to news as an example and just watch the way technology is hitting society and are aware of it are more equipped to be able to leverage it than those that are not staying in tune with the trends, right?

So that would be an example of something.

I think we’ve talked a lot on this podcast about experimentation, right?

Just being willing to set time aside to try it out and use it.

I’m still amazed at how many rooms I go into and I’m talking to people and they haven’t actually ever opened up ChatGPT and typed anything into it.

And I don’t really get why.

Like legit, legit.

Like legit, legit.

Like just last week, I was in a room where 30% of the people asked, raised their hand, like how many of you have used ChatGP?

And they literally hadn’t typed into a sentence of it.

Right?

And I do think some of that is personality, kind of like those early innovators.

Some people just have to be first.

Some people, like it’s just overwhelming to them.

They don’t want to try new things, right?

That type of thing.

But I also think that especially in the work world, in the professional world, we can discipline ourselves to stay abreast of what’s going on, of experimenting with things that hit a certain critical mass and push ourselves to be in the early adapters category so that we don’t get behind.

I think anybody can be an innovator, right?

So there are a few things that you need to think about, right?

So one is, what is the problem you’re trying to solve?

It always sort of starts with that, right?

So if you can’t find a compelling problem, it’s hard to be an innovator, right?

So, but when you work in a business context, there are problems everywhere to be solved, right?

So you can, it shouldn’t be that hard to find that.

The question is then, do you have enough backing in the company to challenge the norms and be able to think differently, find those unique angles, right?

So some organizations allow you to do it and some you get slapped for doing it, right?

So you got to be a little careful there in terms of making sure that you’re in the type of organization that encourages this.

But even if you’re not, there is always a band of people that who are thinking like this.

It’s about just getting your tribe together, who are these types of innovators and who think differently.

That’s the fundamental starting point.

There’s some risk involved in this obviously, right?

So if you’re going to go disrupt something and try to make it better, but I think you can always find a way to do it if you’re so inclined.

I love that idea of just trying to identify the people that are like-minded or are interested in innovating.

You know, it could be as simple as, hey, we’re going to meet once a week for 30 minutes to just talk about new developments in AI.

Just because people that are probably interested in that probably are these people and surrounding yourself with them.

I can only imagine that that would make it when the risk level goes down.

You know, maybe there are some ideas that are generated from that team that could be elevated more quickly in an organization.

Exactly.

Yeah, you know, Mohan, just real quick, I was thinking back, we were talking in an episode or two ago about the grassroots efforts of innovation.

And I think that’s what that’s about, is tapping into those folks that are naturally inclined.

There are people doing it anyways in your organization.

How do you surface them?

How do you highlight them?

How do you praise them?

How do you reward them in order to create more of a culture of this?

Because it’s shown that it’s not only accepted, but rewarded behavior.

Exactly, you should be able to find other people who are curious, who are open-minded, who are interested in learning and form a team.

It could be just a virtual Slack channel, for example, or whatever you use in the company.

I cannot believe that there would be any company out there that would say, don’t start a Slack channel that says AI learning, right?

So just kind of start that and start a discussion, right?

So, and then from there, there are obviously courses and things that you can read and share with each other, brainstorm around solutions.

But I think it’s just about lighting this fire, right?

This fire of change, of how do you start this in an organization and how do you become an innovator?

I think anybody can become that.

You just need the ambition and the energy to go do it.

I love this discussion because I think sometimes we make things harder than they are.

It can be as simple as just starting to ask the people that you’re working with, that you’re around, how are you thinking about AI?

Because you’re going to find in discussion those people that are more inclined to innovate, that are thinking creatively about how to use new technology in the business.

David, Mohan, what do you think about from the leadership standpoint?

How do you encourage this?

How do you find these people in the organization?

Yeah, I really go back to this empowering of the grassroots and how do you do that?

There are people there that are doing it already.

There was a recent study by Microsoft that said, I think it was 52% of people who are using AI at work are actually reluctant to admit it.

And I think there’s been so much talk about the ethical ramifications, the privacy, the security, the this, the that, that there’s almost been this atmosphere of it’s not safe to do it, but people are doing it anyways.

So I think as a leader, creating psychological safety.

And one of the ways you do that is with parameters.

I’m not saying bar none, use it without any thought and just make sure everybody can do it, but can you define what the parameters are?

Share with people what they are so they know their boundaries.

And when people know their boundaries, they’re able to exercise and flex their muscles within those boundaries a lot easier.

And I think that statistic really speaks to what the leadership mandate is, is to create room for this, not just by giving people time, not just by throwing it out there, but actually by making it safe and by fostering what sits on the ground already.

The beauty of AI technology is it’s applicable to all functions, right?

It’s not just in the tech team that’s getting used, it’s in all departments.

One of the things leadership can do if it is relevant to that organization is to bring it out of the black market into a legit way of working and put guardrails, the governance that David was talking about into making this legitimate and saying what can be used, what can’t be used, just because there are legal implications to this.

So it’s really important to empower through good guardrails is how I’d say it is the job of the leadership.

The other thing that I think when we talk about this rewarding and those types of things, I think the other really interesting piece of that research by Microsoft was that how much it’s paying off.

The users that were using AI, rather they were doing it in the black market or the white market, reported all sorts of increases to not only the time they saved, but their ability to focus on important work, to be their ability to be more creative.

And ultimately I’ve seen multiple surveys, including this one, that report employee engagement is going through the roof.

This is actually good for employees and there’s such a talk track about what is it gonna do to jobs and all those types of things, which may have merit in itself, but I think it’s overshadowed in a lot of ways that this is actually increasing people’s fulfillment at work because they’re able to delegate things that they’re not good at or they don’t enjoy doing to spend more on the complex, hard, creative, fulfilling work that they love to do.

David, Mohan, you two, both innovators, thank you for your words of wisdom.

I don’t know what else to say.

I’m surprised you haven’t made a comment about Mohan not wearing his uniform.

I mean, where’s his Knownwell quarter zip that we all agreed to show up on?

After our last episode, I went all in on also dressing like Steve Jobs.

I wear it on the inside, I don’t need a shirt.

Always the innovator.

David, Mohan, thank you.

Thanks.

If you want to be an innovator, an early adopter, it helps to have the right tools in hand.

Fortunately, we’ve got you covered.

We’re revolutionizing client retention and client growth with our AI driven platform.

We’d love for you to check it out right now at knownwell.com.

Djan Turan is an AI entrepreneur and founder of Pebbles AI, an AI SaaS platform that automates the full B2B go-to-market workflow.

He recently chatted with Pete Buer about becoming a successful innovator at the intersection of AI and business.

Djan, welcome.

So great to have you on AI Knowhow.

Thanks for being here.

Let’s get into it.

I was hoping that we could start with a quick introduction to Pebbles AI and your background to give listeners a little bit of context for the conversation to follow.

I’m CEO and lead researcher at Pebbles AI, which is a go-to-market platform for B2B companies to help them to go to market.

It’s a SaaS platform with our own AI that is dedicated for each individual company that signs up.

My background is in marketing and strategy and in science that go to market principles.

With that, I mean persuasion sciences, communication sciences, corporate strategies.

I worked for the big tech at Google, Cisco and Walmart Holding in different fields of marketing.

And then finally took the plunge, became an entrepreneur just because I wanted to close the gap as for the injustice that I saw that only the big tech companies and the leading such consultancies, the likes of McKinsey would hold kind of the monopolies of the go-to-market knowhow.

And I wanted to close that gap.

And I saw that opportunity, I took it and here we are.

In your introduction, you referenced science led marketing and some of the impressive big companies that you’ve done some work for.

Tell us more about science led marketing and how AI factors in.

That’s a very good question.

It’s also a big answer about trying to keep it succinct.

So science led marketing is really based on a couple of things.

So number one is market validated methodologies, things that don’t necessarily fully make sense in the academic scientific eye, but work.

As you know, science is ever evolving.

So if we haven’t have an answer for why this happens, doesn’t mean that it doesn’t exist.

So if it’s market tested and it works, then that is for us, it qualifies as science led.

And number two is obviously the academic sciences, the persuasion science, the communication sciences, how does our brain work?

So for example, persuasion science is a great way to understand how to convince people to do a certain action that you want them to do.

So either review a proposal or reply to an email or sign a service agreement.

And finally, of course, data is very important.

So good old quantitative and qualitative data analysis and really translating insight, essentially telling stories from numbers.

Those are the three main pillars that essentially develops into science-led go-to-market.

And given that the topic of the podcast is AI and helping leaders get to a place of comfort with AI, is AI an enabler, an accelerator, a technology and methodology to help scale science-led marketing?

It’s more the transformation.

It’s a good question, by the way.

I think it was important for us to digitalize essentially what we were doing with my previous consultancy.

We couldn’t scale ourselves.

And the AI allows us to essentially download our proprietary marketing strategy models and our persuasion sciences.

And we essentially, we’re a SaaS platform first, a bit like Figma and Slack, but we have built AI agents that are what we call GTM, have the GTM knowledge and the rules-based systems that are otherwise monopolized by these big companies for people to use, for companies to use essentially.

So yes, it’s accelerate, of course, it’s more efficient, it’s much faster, the efficacy is way higher.

There are underlying principles that make sure that your success rate is higher, the risk is lower.

But ultimately, what it really does is it allows SMEs, channel partners, even larger corporations to have a real fighting chance that can’t afford half a million to McKinsey, another half a million a quarter to execute on that strategy, as it may.

Awesome.

That’s beautiful.

As it turns out, we tend to have a number of marketing executives who attend the podcast, and some of our early customers are marketing companies.

When you think about the occasion of AI and its impact in marketing, what are the other, beyond what we’re talking about now, what are the other big opportunities that marketing leaders should be thinking about?

When you come on Pebbles Ai, there’s an onboarding process, first off, so you do have to train your AI.

I mean, that’s the only thing we can’t do.

It needs the organizational intelligence context of your organization.

There is a golden circle scientific onboarding principle where we ask very specific questions.

We ask about the company, the approach, the processes, and also about the products and services, the want essentially, and then who they serve.

That initially enables the AI agents to be trained at a bachelor level.

And then the more you use the product, the more actually they get to a PhD level, essentially to understand more about your company and then the wider context of your company in the wider world.

And they will have different apps within that platform where they can choose like, okay, tick, I need a marketing strategy, tick, I need now a marketing campaign, tick, I need an upsell campaign, tick, I need a cross-sell campaign, tick, I need a BTB proposal for this client, tick, I need to generate a pest analysis because I don’t know whether or not I want to go into the German market.

So, hey, intelligence, which is a typical senior analyst at McKinsey question, should we go into the German market?

And if yes, why?

Give us a pest analysis because whether or not we should spend our time on that.

All of these things and much more, you’ll be able to do on that platform.

Yeah, that’s awesome.

We love hearing stories of kind of AI in the wild, what it looks like in real life.

So thank you.

Elsewhere in this episode, there’s a round table discussion about how leaders can become sort of early adopters innovators in their organizations to bring on, for instance, technologies and applications like we’re talking about.

What’s your advice to a leader who sees a lot of opportunity and wants to get the rest of the organization as excited as he or she is?

That’s a very good one.

So first off, I did this short course at the London Business School on digital innovation.

I’ll spare my criticism, but the one thing I did learn a lot was that the reason it’s hard, it’s just very human.

It’s just people find it fearful and scary to put their necks out for new things because they are scared to get fired or demoted or lose political capital, whatever the reason may be.

So I think if you have someone courageous that wants to push the agenda forward of AI, I think the first thing you need to look at is practicality.

It’s very important.

How practical is it?

Because there’s a lot of AI and a lot of functionalities, but how useful is this for us?

And how can we genuinely use this to speed up our existing processes or to save time or completely re-haul a certain department of our company?

So practicality really allows you to kind of narrow down.

We don’t need this.

This is a non-sense software.

This is waffle.

This is, you know, it gets, now the Dutch are very good at this, you know?

You know, being very pragmatic, like how does this help us?

Show some case studies.

That really does help.

Those case studies then, you know, kind of become kind of your calling card or within the organization.

And it helps you kind of win over more of your internal votes as it may.

Djan, thank you so much for joining us today.

It’s been an honor and a pleasure to spend time together.

Same feeling, similar.

Thanks, Pete.

Thank you.

Thanks as always for watching and listening.

Speaking of watching, did you know that our show is over on YouTube?

So what’s better than just listening to the show?

Listening and watching.

So make sure to check it out on YouTube.

Each week, we get one of the LLMs to weigh in on the topic at hand.

So today, Claude, welcome to the show.

Would love to hear what you think about how you can become an AI early adopter in your company.

Hey there, great to be on the show.

Becoming an AI early adopter in your company is all about staying curious and taking initiative.

Start small by experimenting with AI tools in your daily work.

Then share your successes to build momentum and look for bigger opportunities to integrate AI into key business processes.

Now you’re in the know.

Thanks as always for listening.

We’ll see you next week with more AI applications, discussions and experts.