4 AI Strategies and Tactics to Deploy in 2025

What AI strategies and tactics should you be sure to adopt in 2025?

And how can executives set the tone for the rest of their organization to roll up their sleeves and use AI?

And if the Wall Street Journal’s tech columnist is finally all aboard the AI bandwagon, is there anything stopping the rest of us?

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 and Technology Officer, Mohan Rao, and NordLight CEO, Pete Buer.

We also have a discussion with Christian Madsbjerg about putting humans at the center of your AI efforts.

Pete Buer joins us, as always, to break down the business impact of some of the latest and greatest AI news.

Hey, Pete.

Hey, Courtney.

How are you?

Looking pretty festive, but I can’t see it.

What’s going on on this shirt?

Is that a car?

A 32 Ford Hot Rod.

A 32 Ford.

I didn’t know what that was.

Is that like Santa’s sleigh?

Is that the deal?

I think there’s a song about Santa having a hot rod sleigh somewhere.

That’s awesome.

Well, hopefully everyone that’s watching online can take us seriously with these get ups, but let’s dive into the news.

To close out this year’s segments, I’d like you to help us unpack a recent Wall Street Journal piece by Christopher Mimms, titled, A Powerful AI Breakthrough is About to Transform the World.

Pete, what do you make of this one?

I think this is a good one to put a cap on the years worth of news and interviews.

It’s worth noting first off, however, that the journalist Christopher Mimms appears to have found his way past skepticism over AI hype towards something a little bit more resembling religion.

His previous articles this year were, the AI revolution is already losing steam and AI is dumber than a cat.

This article has a very different feel to it and why the change of perspective.

I think simply it’s just the progression of the use of the technology and the emergence and evidence of farther reaching applications all across business and organizations worldwide.

So you should, as always, read the article yourself, but I can share the gist with you.

The thumbnail sketch is that the author’s take is that AI is proving itself capable of outcomes ranging well beyond the advanced search and text and image generation that we’ve become so accustomed to.

The same transformer technology that serves as the backbone of our most familiar applications is capable of doing so much more.

He offers a handful of well-researched and profiled examples, self-driven cars which are not news to us, but that are able through their use of the technology to identify and react to images that they’re not trained on.

AI-powered software that can run any robot, not just the robot it was purpose-built for, but any robot whatsoever.

Developments in plastic-eating bacteria, progress in the search for a cure to cancer, the list goes on and on.

The takeaway for leaders beyond, I think, hope, right, that the future is a time of prosperity.

Even though we’re through so many breathtaking innovations already with modern AI, we are still very early days.

As Christian Madsbjerg put it, we still don’t really know what AI is for.

And I think he’s right.

So keep learning, keep experimenting, keep pushing on the possibilities.

Put your very biggest and most pressing problems under the microscope and figure out how we leave this world in a better place than we found it.

What a beautiful way to end 2024.

Pete, thank you as always.

Thank you, Courtney.

With a new year and a new way of doing things on the horizon, how can you tap into AI to power your company’s success in 2025?

I talked with David DeWolf and Mohan Rao recently to get their takes.

David, Mohan, in our last episode, we made some predictions, and by we, I mean you two.

Yeah, thanks for participating.

Appreciate that.

What will happen in 2025 in AI.

Today, we’re going to help our listeners, you all listening, prepare for the new year with four AI strategies and tactics that we believe can help you harness AI in innovative ways this coming year.

David, would you kick us off with the first tactic?

Yeah.

So I used to hate the word mobile first back when we had devices and we’re talking about kind of mobile first strategies and all this kind of stuff.

But I like that you frame this as a tactic.

So I’m going to start with AI first.

Right.

I do fundamentally believe that the organizations that are thriving with AI are the ones that think it first.

And I think it starts with as simply as an executive when you’re going to do knowledge work, when you’re going to go start writing something, a thought piece, if you’re writing a policy, like those types of things, go and use AI first.

And if you start with that mindset and you embed that mindset in your organization, and you are driving that mindset throughout the organization, I think you will drive both effectiveness and efficiency gains.

And so an AI first mindset is the first tactic that on every single thing you’re doing.

And ask yourself, what can AI do for you?

What would AI do?

Yeah, and can I just add, it might be wise to just deploy people going and doing the research for you.

So if you have a problem, I know this came up for me recently that we were trying to solve, but we wanted to do it.

We just didn’t have the resources of funding to do it the way you traditionally would, we’re a startup.

And so I asked one of our amazing interns, like, hey, can you go research?

Is there an AI platform or tool that could do this for us?

And sure enough, she came back with quite a few options.

And so even though that’s a simple thing, like, don’t be afraid to go, like, deploy other people to go do that research work for you.

Awesome.

Okay, so the first tactic, adopt an AI first mindset.

I think that mindset word is really key as an executive.

Mohan, can you kick us off with the second tactic?

You know, it’s really a fact of life in enterprises that people are using ChatGPT and other type of gen AI tools.

If it is not in their systems, at least they’re using tools.

And I think this is time where executives should start thinking of the augmented way of working and make sure that there are good guardrails around it, but also enable the employees to use it and make it front and center in terms of productivity and how can they build a better organization by getting the AI and human collaborating well together.

Hey, Mohan, I think a big piece of that you said, empower the employee.

I think a big piece of that is just the training, the upskilling.

How do you invest in your employees to really empower them with the ability, not just the permission?

Exactly.

And now it could be as simple as saying, hey, you use ChatGPT for this, then you copy the text and then you put it in some other system, so on and so forth.

I mean, just sort of integration of these tools.

Just think of the GenAI tools as your mainstream, whether you’re a software developer using various co-pilots or your marketing or a support person, just make it mainstream.

Do you two think there is a way, if you think of the old adage, incentivize the behavior you want to see, do you think there is some incentives that we can leverage as executives to kind of, again, you’ve got to kind of change workflows and just kind of the default thinking around using this new technology?

I don’t know how much it’s about incentives because I think people are already using it to a large extent, right?

So this is a case of where the executive team needs to catch up with the way things are already being done.

Interesting.

So it’s more of bringing it to mainstream and taking the productivity enhancements that are already there because people are using these tools and just getting to a much higher level of productivity because now you’ve thought this through from the ground up.

I always wonder because we’re in an AI company, we’re surrounded by companies that are more forward leaning in this way, they’re more innovative, that I always feel like is the population at large really deploying these in their work or is that just how we feel because we’re so close to it?

I think you have a good point, Court, in terms of the knowledge economy is where this is being used.

But the knowledge economy or however you want to describe this part of the workforce is not the majority of the workers.

So in that sense, it is not there everywhere.

But if you are in a marketing agency, if you are in a software development shop, if you are providing customer support, this should be mainstream or should be emerging mainstream.

I think what you can do is praise what is working, right?

So when you see the grassroots effort, calling out, complimenting, highlighting where it’s being done well, and those that are out front using it is probably the quote reward that you can do to reinforce that behavior.

And those that aren’t on the bus, I think will flock to that bus.

Okay, so the first two tactics were adopt an AI first mindset and as an executive, the second being invest in human AI collaboration.

Mohan, why don’t you take the third one as well?

You know, the leveraging real-time AI and predictive analytics is something that’s really important.

It’s going to be hard to pull this off, right?

Because it’s a fundamental rethink of how you run your operations, what data stores do you have that are getting produced as part of your operational processes, and then make predictions towards what is the next best action that anybody in the company can take, right?

That’s what we’re talking about.

So this is a pretty big theme that’s going to require fundamentally rethinking the enterprise and the digital modes that people are working in, and the factory, the data factory underneath all of the operations need to be rethought.

So this one’s going to be a hard one to put into effect right away, but I think people should, executives should start planning for this and see what elements can be purchased out there versus what can be built in house.

But one way or the other, this is a little long-term destination, but the journey should begin in 2025.

Wait, Mohan, couldn’t we make this really easy for them and they just buy the Knownwell platform for their enterprise?

May, if you’re talking about client relationship, commercial intelligence, of course, that’s what we offer.

But that’s one of the big value chains, but there are other value chains in a company.

So, but to that point, like joking aside about Knownwell, obviously, we love Knownwell, but there could be pieces of this that you can step towards in 2025, which is your point.

It may not be across wholesale, across the board, but that you can make movement towards this in 2025.

David, want to take the last one here?

I think the last one is really starting to focus on the user experience.

We had an episode where we talked about explainability and usability.

And I think it’s really important that as we double down on AI, we focus on making sure that these systems are understandable to the users, that we’re building trust, and that we’re really thinking about this from a consumption standpoint.

There was the era of IT where we went through the consumerization of IT, and it was all about that user experience starting to look like Facebook, right?

Now I don’t think the consumerized AI products are really there yet.

I think there are some that are starting to figure out what the new user experience is going to be in AI, but it’s very early.

But I think pushing the envelope on trust in those things is critical.

I think this is a really helpful conversation, and hopefully for all of you executives as you’re thinking about 2025 and thinking about what your mindset needs to look like when it comes to AI and how you approach 2025.

Again, these four strategies and tactics are, the first one was adopt an AI first mindset as an executive.

The second was invest in human AI collaboration.

The third one was leverage real-time AI and predictive analytics.

And the fourth was prioritize user experience and explainability in AI tools.

David, Mohan, thank you as always.

You know what one of the best AI strategies you can take in 2025?

Well, it’s investing in an AI platform like Knownwell.

Empower your team to spend more time doing what matters most with your client relationships and less time guessing.

Knownwell gives you a much clearer picture of your portfolio’s commercial health than existing tools like NPS or customer satisfaction tools.

Knownwell gives you a real time, objective, proactive view of what’s actually happening with your commercial health.

It’s easy to use, easy to set up, and easy to understand.

If you’d like to see more, go to knownwell.com to learn more and to sign up for our beta waitlist.

Christian Madsbjerg is the author of Look, and he’s been one of the AI Knowhow team’s absolute favorite guests.

Out of all the amazing people we’ve had the honor to interview for the show.

We were thrilled to have Pete Buer get a chance to talk with Christian again recently, and this time about putting humans at the center of your AI efforts.

Christian, hi.

So wonderful to have you back on the show.

We had such a delightful conversation last time.

I’ve been looking forward to this.

Yeah, me too, Pete.

Thank you for having me back.

It’s been, believe it or not, a year since we last spoke.

So I thought I’d just give you the opportunity to start out open-ended and see if you had any sort of high level observations on AI and the human from 2024.

Many thoughts, I think.

But the first thing is, we still don’t know what it’s for.

I don’t think anybody knows what it’s for.

I don’t know if we even know what the right questions are yet.

But it seems like there are experiments happening, and whether that technology is successful or not, those experiments are happening.

For instance, I saw the other day an experiment happening in Brazil on charter school kids in fifth grade.

That are being taught how to write with machines.

So learning how to write now involves machines in a way that is new.

And whether that is right or wrong is, of course, relevant question.

But most of all, it’s just a massive human experiment we’re rolling out.

And I think we get to see it happen in its early days, which is fascinating and terrifying.

I feel like there’s a lot going on in your brief statement of the fact that we’re not sure yet what it’s for.

Can you speak to that just a little more?

I think in any new massive technology, there’s always a period that’s often longer than we think, where we’re trying to figure out what it was.

I’d imagine if you’re inside of the people that made the first automobile, they didn’t know that we would cover our countries with roads at that point.

They just thought it would be used for some rich people to go for dinner parties.

They had no idea.

I think we’re maybe in the same state now.

There was a person the other day I met who said, now might feel the same as the time when Charles Darwin wrote his book, which was that this difference between humans and nature is no longer there.

We are nature.

And he said, maybe the feeling is the same right now.

It’s no longer humans and machines are different.

It’s actually vastly overlapping.

So that feeling that it must have been to be there hundreds of years ago, when those books came out, or that book came out, The Origin of the Species, it might be in the same feeling that we would talk about now 200 years from now.

I hope I’m not making an unfair leap, but I read recently a little something about HARL., H-A-R-L, Human Activity Research Lab.

I think that’s a project that you are a co-founder of, and I went to the site and I snooped it out a little bit, kind of stalking you a little.

It spoke to a methodology that’s about observing humans as they engage with new technology.

Is that your effort to try to help figure out a little bit of what AI is all about, what it’s for?

Exactly.

Exactly.

Yeah.

It’s a lab I founded with two people I admire.

One in Tokyo, one in Copenhagen, one in New York, or me in New York.

We’re going to do these longitudinal big studies with multiple partners to understand not so much the technologies themselves, new technologies themselves, but the effect they have on human life.

Instead of just understanding language models, we would want to understand it in a fifth-grade class somewhere in Brazil and see what it’s like to be a child or a parent or a teacher, as these technologies just ripple through society.

It’s a serious effort, like a laboratory effort to understand the effects that these technologies will have.

Not just AI, there are many other technologies that are important too, but technologies that hit our society like a meteor, and then have all these second and tertiary effects that we don’t even understand.

I think the lab is set up to study that in an organized way.

It’s pretty exciting.

Last time we spoke, there was a powerful thought that you left us with.

Technologies should support the human experience, not be at the core of it.

With a year having unfolded now, and all that’s going on with AI and its many forms.

How are we doing?

Is technology at the core?

Is it enhancing human existence?

We don’t know yet.

I mean, you’re interested in the new versions of AI, which is exciting, right?

We don’t know what effect this will have on education and learning, and our kids.

We don’t know the effect it’ll have on human to human relationships.

Like we will definitely have humans to machine relationships that are different than they were five years ago.

But what would that mean for dating and friendships and workplaces and things like that?

We have no clue yet.

So it’s a giant, pretty reckless implementation at, you know, four or five billion people at the same time.

I’m with you on that.

And the thing that we talked about last time as well is that there’s an important role for, in our context, business leaders in ensuring agency of the human and that the reckless, that the implementation isn’t so reckless and that we’re keeping the place of the human in workflow in mind as we shape strategies and work going forward.

Do you feel like businesses are being deliberate in that way?

Absolutely not.

No.

They’re just full cloth implementing it.

I mean, we could sit here and be sort of hand wringing about it, but it’s going to happen.

So let’s deal with that, right?

And I think the main moral point of view you could have as a business leader is to learn really fast.

So set up experiments that makes it possible for you to learn what it means for the people you interact with.

So whether you’re in like hardcore B2B logistic systems all the way to softer things like educating children, the entire thing is one big experiment.

And I think learning in an organized way as it happens is what businesses ought to do here, just like anything else, but just more because the technologies are bigger and the risks are higher.

I wonder if there’s a way to get that across to the CEO who’s got 18 months and leading a middle market company before they go to exit and they’ve got to somehow find X percentage points of margin and they’re just imagining swapping out people for technology solutions.

They’re not operating from a incentive base that lends itself to the measured approach of science.

What do we do?

Well, and that is fair.

If you run a middle-sized business and you don’t have that amount of time and resources around you, it’s unfair to ask for something like that.

But I found dealing with leaders my whole life, or my whole grown-up life, is that people really want to learn and they really want to do the right thing.

They just don’t always have the tools or the resources available and so on.

But on average, I think people understand the magnitude of these new technologies and their role in it.

It doesn’t have to be university-involved enormous studies.

It’s just organized thought as it’s rolled out.

And that can be done without breaking the bank.

If you’re a services business, I guess this is a time to look for help from the outside.

And of course, I’m sure an organization like your own could be helpful there.

But are consultants smart about this?

Are there places to go to get this kind of help?

I don’t know how much bandwidth I would have.

But the first thing that happened, actually, when we announced the lab, the first thing that happened was I got swamped with people from the big consulting firms and the big IT companies saying, please, can we be involved because this is a problem we’ve been looking at?

So I think there is a lot of good faith.

I wouldn’t be able to handle a percentage of that.

But there is an interest and there is certainly an awareness that releasing technologies into the wild is something you ought to study when you do it.

That’s so interesting.

Because so much of the, I mean, all of the focus of consulting through to here across the last couple of years has been, I don’t want to call it all reckless, but it’s had the same, it’s sharks, you know, sensing blood, figuring out what the next big wave is going to be and taking advantage of it, riding it and making money on the technology build and not spending as much time if any on the thoughtful implementation as regards to the human and changes in behavior.

So like, maybe there’s a blossoming subsector here that we should keep an eye on going into the future.

I mean, that’s capitalism, right?

That people are capturing markets, that’s fine.

But the thing is that you would be a better services firm that implement technology if you also knew the second and tertiary effects of the technology you’re implementing.

And you would make more money that way.

It’s just a lot, it should be a line, a service line across the board that you’re dealing, when you’re dealing with people, you need to understand how those technologies affect those people.

There are implications for skills and roles and jobs and culture and how people interact with one another.

And I think not enough of that is kind of under the microscope at the moment.

And the fun of it, right?

The fun of being in the middle of a societal transformation.

Our mind should be lit up with excitement and sort of the joy of it.

It’s amazing.

And, you know, seeing these technologies and experimenting with new technologies is one of the most exciting things you’ll do in your work life.

So it should be a joyous human thing, too.

Well, so we’re coming up on the end of the year here, and people are making their resolutions, taking a look at how 24 unfolded and how they’d like 25 to roll out a little bit differently.

What are you excited about?

And what are you going to be focused on in the new year?

So I’m excited about building two, three years, longitudinal studies of how humans interact with technology.

And I’m excited about doing that in a way where we can learn fast.

So that if we make mistakes in implementing technologies in the schools in Brazil, we will learn from that in Vietnam before we make the same mistake there.

That we can learn together as these things are being rolled out to four or five billion people.

That is fun and I feel important.

Two to three year studies.

Will we know what it’s for in two to three years?

Or do we have a few cycles of two to three year studies, do you think?

I don’t know.

I mean, the other day I saw a new technology that the Google Labs rolled out with a musician called Jacob Collier.

And it’s a language model, but it generates music and sounds that has never existed in nature.

So you can ask, you could say the sound of reverse paint or the sound of ice oars crashing against a boat.

And it generates a sound that has never existed before.

So suddenly, you have not just, you don’t have just an intellectual language-based relationship to a machine.

You have an emotional, musical, sound-driven relationship to a machine.

Now, that’s new.

That’s new in a way that hit me much more than the first time I saw GPT-2.

This is deeper and more human.

I think what that would mean, I have no clue, but that feels big.

That’s awesome.

Well, I hope we can all, as part of our resolution making, devote ourselves in the new year to the thought that this new technology deserves and experiencing it for its possibilities, and finding some room for joy in the work as I experience from you every time we talk about it.

Take care of yourself, Christian.

It’s been wonderful to see you again.

You too.

Thanks as always for listening and watching.

Don’t forget to give us a five star rating on your podcast player of choice.

And we’d really appreciate it if you can leave a review and or share this episode on social media.

At the end of every episode, we’d like to ask one of our AI friends to weigh in on the topic at hand.

So, hey, Chad’s UBT, what’s happening?

This episode, we’re talking about AI strategies and tactics for 2025.

So, what do you recommend?

Hey there, for 2025, I’d recommend focusing on personalized AI solutions that adapt to user-specific needs and investing in ethical AI practices to build trust and reliability.

It’s all about staying flexible and future proof.

And now, you’re in the know.

Thanks as always for listening.

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