The AI Transformation Mandate, Part I

Which part of the business does research say is the least prepared for an AI transformation?

And what’s the biggest challenge that CEOs face in leading that transformation?

And hey, HR leaders, where are you at?

Did you know that you need to be prepared more than anyone else today to grapple with the impact of 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 and Technology Officer Mohan Rao, and Chief Strategy Officer Pete Buer.

For this special two-part episode, Knownwell’s Chief Strategy Officer Pete Buer joins CEO David DeWolf to discuss his research into AI transformation and why it’s imperative for middle market companies.

Later, we’ll have a discussion with John Evans of Impact Networking on how you can make the transition to an AI-enabled company.

But first, let’s dive right in to the first part of the conversation between David and Pete on the AI transformation mandate.

Pete, welcome to the show.

I get to turn the tables on you after a full year, and I’m so excited about this.

How are you today?

I’m doing great.

I’m looking forward to seeing what it feels like to sit on the opposite side of the table.

I love it.

I love it.

So the listeners of the AI Knowhow know you as our Chief Strategy Officer and Thought Leader at Knownwell and an individual who is typically in my chair, interviewing others and really sharing the wisdom that you see from pouring through research.

What they may not know is that if you rewind all the way to last year in the earliest months of Knownwell, you and I together along with Courtney and Mohan, actually discovered two different business models that had very relevant applications for the point in time that we’re on.

One is what has become Knownwell.

The other one is a special project that you have been working on.

That special project is diving into the second business model and really doing even more research.

I’m excited to be able to talk to you about that research today and learn more about it.

Do you mind starting off by just sharing a little bit of the research journey that you have been on?

Sure.

To your starting point, it began under the roof of Knownwell as we were working on a set of advisory services for companies in our target market.

The early thinking was that these companies not only ultimately would need a product to serve them but also could use some consulting and guidance to make sense of AI and AI transformation in the first place.

As the business evolved, of course, the team doubled down on the product platform piece, and off I ran with the advisory work.

Through conversations with quite a few different customers, I’ve gotten deep and come to understand in some level of useful depth, I think, what some of the big issues are that companies are wrestling with.

And so, the business that we have spun out is called Nordlight, and Nordlight’s focus is to help companies make sense of AI, help them chart their path toward AI transformation.

From upstream, looking at the needs of investors and board members and making sure that their companies and portfolios are properly focused and taking advantage of the technology, managing the risks, through to CEOs and transition leaders who are on point to come up with the actual strategy and the plan for getting work done, through to, I think, one of the biggest challenged personas in the chain, the people who are leading the talent transformation work, HR, the Chief People Officer, the Chief Human Resources Officer, legal to some extent, who are kind of the takers of the frame and who have the most work to do to get actual behavior change to happen to get to RLI at the end of the day.

Okay, so let’s take that and dissect it, Pete.

You just painted a great picture of, I think what you’ve dubbed the AI Transformation Mandate, right?

There is this mandate in the organization and from the board to the C-suite to what you’ve pegged and really done the research on to find is the talent organization, the HR organization in helping to transform the people aspects of business to be ready for this AI world.

Can you double-click into it and talk about what are the actual pain points each one of those is experiencing?

What’s driving this mandate and why it’s so critical at this point in time, given we’re so early on in the life cycle of AI?

Well, I will say that the circumstances can be different based on the industry and the business size and the funding mechanism of the business that we’re talking about.

But I love starting with the example of middle-market, PE-backed knowledge worker companies, because it feels like all of the challenges show up in a really meaningful way with that focus.

What unites everyone in the chain is the focus on business outcomes.

That at the end of the day is what this is all about.

In middle-market PE-backed companies, you not only are on the hook for delivering an annual number, but you’re working toward a particular outcome for the business on a particular timeline.

This lever of AI and its magnificent capability in terms of changing, rewriting the economics of the business becomes an extremely important tool to focus on in your strategy.

If you go to the three personas, if I’m running a PE and I’ve got a portfolio of a couple dozen companies, I want to know that in every case, the leadership teams have looked very closely at their pain points and at the risks to the business and are taking the right steps to deploy AI.

Or by the way, any other digital or process based transformation, look at it all at the same time.

But to get them to a place where they’re able to deliver greater value to customers or they’re able to operate more efficiently and ultimately get to a better profitability profile on the right timeline.

If I’m the CEO and in some cases we’re seeing, especially in larger companies, but in smaller companies, it can be a committee effort, but we’re seeing chief transformation roles appearing or centers of excellence that are doing some of the legwork for the CEO.

But if I’m the CEO, it’s AI as we know from the research is a top three priority for all CEOs.

I’m on the hook for charting the path to performance.

Do I understand where in the business my greatest risks exist so that we can take the right steps to mitigate them?

Do I know where the technology can be deployed?

With the help of the team, can I get to a roadmap that helps to plot out, not everything under the sun, but the most important implementations and investments to make on a reasonable timeline that takes into account the people factor to get us to the kind of outcomes that we need?

And by the way, aligning the organization against a single vision, I’m finding is one of the biggest challenges of CEOs in the space.

Each of their direct reports is on the hook to find efficiencies in their domains.

And so in some companies and in some cases, people are kind of working a little bit out of lockstep with one another, or making decisions on their own, reacting to what their tech stack providers are offering in terms of tools and letting that drive their strategy.

And so it’s really a moment for the CEO to pull the team together and get them focused on the right things in the right order.

And then lastly, for the talent management and migration piece, all of the benefits promised by AI and AI transformation depend on our ability to fundamentally change the way people show up to and do their work.

And so the work of looking at work flows and asking ourselves how they can be done differently or more smartly, understanding the talent implications, understanding the skill implications, understanding the, you know, you can work your way all the way down through the levers of what makes talent work effectively.

All of that work is falling on the implementation end of this process, led in part by technology leaders, but also led very much in part by HR, who by the way didn’t grow up with AI, right?

And so, you know, one of the big challenges that they have as actors in this journey is not only, you know, helping the organization get where it needs to get, but also getting themselves to a place where they’ve got a sufficient level of acumen that they can lead with credibility and know the right things to do in the moment.

So there’s a lot of work to be done.

So much there in what you just said to peel apart.

I want to go all the way back to the beginning before I dive into some of those specific topics that you brought up, because there seems to be this implicit assumption that is underlying everything that you just said, that I want to put explicitly on the table and really explore.

It sounds like everybody is assuming this is going to be a massive transformation and that AI is a given and there is truly a global mandate.

Is that what you found in the research or is that just my impression and what I’m hearing?

Like, did you find anybody scratching their head and saying, nah, this isn’t going to be much of a big deal?

So, I will answer both questions in the order that you laid them out.

Number one, stepping back, we know again from the research in knowledge work industries, 50% of the work, something like that, at the end of the day, ultimately can be automated or augmented with AI and other digital technologies.

And so, the opportunity is there.

I think the pressure of delivering on investment and keeping up with the competition kind of means everyone needs to get after the opportunities to tweet.

So, if they’re denying it, it’s truly denial.

It’s not a reality.

The research is clear that it is a game changer.

I will say, in the places where it’s not true that it’s an all singing, all dancing agenda for our leadership team, those are places where the company has fundamental problems that they’re working out first.

Like, my go-to-market strategy isn’t working and I need to sell more, or I’ve got a retention problem with my teams, and until we get stabilized, I can’t be thinking cleverly about reorienting, mapping value streams and rethinking the way work gets done in the business.

Interesting.

But in all cases where we’re talking to businesses that are doing any work, the ones who are the smartest are starting from strategy and looking comprehensively across the business, and then, of course, being wise about how much energy they deploy into the different opportunities for change, but it’s, yeah, it’s center of the plate.

It’s interesting.

It’s a prioritization thing.

So if you’re not getting up and brushing your teeth in the morning, you may not be getting dressed, but otherwise you are.

Yeah.

The attack on I’ll offer is the pressure and the comprehensiveness of focus varies from persona to persona in the business.

And so I’ll use the example of HR.

The leadership team may be quite thoughtful in terms of what will get done this year, what will get done next year, and take a measured and time-honored approach to get the work done.

And so in the minds of the CEO and the leadership team, returns are kind of, maybe they’re 18 months out, they’ll start seeing change early on, but then their big stuff will come down the road.

Unfortunately for the head of HR, the first day that employee number 332 kicks on ChatGPT and feeds some customer information into it to try to make sense of a spreadsheet, their job has begun, right?

And so the timelines are misaligned, and right out of the gates, HR and Legal have a big job to nail down how we keep ourselves out of jail, how we protect our reputation, right?

While the rest of the team might be saying to themselves, we’ve got a path to go down before anything actually starts hitting the fan.

Interesting.

So that actually leads to exactly where I was going next, around these personas.

You talked about the board level, you talked about the CEO, you talked about the executive team, and then the head of the talent organization.

It feels from that answer that it’s very much that the board and CEO are driving the vision and the transformation, but it is the talent organization, maybe the legal organization, that has to pick up the pieces of the here and now and has the immediate kind of urgency versus the important vision.

Is that the way we should be thinking about it?

Your question at the end is the right one.

It is the way things are working at the moment.

The language we’ve been using is that the talent team kind of takes the frame, whereas the CEO and the team probably are making it.

But no, I think the right answer for the business long term is that the talent leader should be involved from the get-go because there needs to be, around AI in particular, there needs to be a voice of agency for the human in the reworking of business, knowing better to understand and appreciate the implications for the employee base than the head of HR.

And it makes for a better strategy.

Ultimately, if you can factor in the right kinds of timelines, the right kinds of investments to go through transformation in a successful way that lands with the right numbers and skills and shapes of people to do work in the right way.

So we’re seeing, but for in the most progressive organizations, that’s not actually how things are working.

But there are some cases out there where the HR leader has a deep business background, maybe has some technology background, is in a kind of company that’s continuously in the flow of these sorts of conversations where talent matters a ton.

They’re in the conversation from the beginning.

Let’s talk about that hard reality then, because I think it’s interesting.

You describe it in the context of AI, but you and I have actually had conversations before, especially in the middle market.

Talent organizations tend to be undercapitalized, underserved, underinvested in, to be true business partners, and to really honestly have a seat at the table in a lot of situations.

It feels like that is leading to part of what’s going on, and is one of the obstacles that we need to overcome if we’re going to successfully navigate this period of transition, where you mentioned aligning vision is one of the biggest things.

I mean, what better way for talent to participate, for example?

Can you talk about that a little bit and what you’re seeing in terms of this intersection of the reality of AI with this undercapitalization, underinvestment in AI for what feels like quite a long time?

Yes.

The circumstance of talent in middle market, is as you described, I agree that it is under resourced and undercapitalized.

I think that’s in most cases a legacy of how companies have grown.

They’ve added people slowly but surely and built the thing up.

And in the very early days, the leadership team can do its own hiring, right?

And so by being frugal and keeping the headquarters cost base low, there’s kind of a continuing set of decisions that find you minimizing the flow into building up the HR organization.

Unfortunately, this, I think, brings us to a tipping point for the function because the current capability doesn’t line up with the work ahead.

So the frame that we’ve developed at Nordlight for thinking about the jobs to be done for the CHRO is that there’s kind of one set of tasks that are about enabling the organization for AI transformation.

So putting the right risk mitigating factors and training in place, enabling initiatives and implementation, building out the right support mechanisms for the major AI work getting done.

And then also they have the work of being a functional leader and finding the places where AI can be used to make their own part of the business more efficient.

And so we know in talent acquisition and L&D, generative AI in particular has wonderful and high-impact implications.

And the economics of HR can be even, given our starting point, can be even more efficient than they are currently.

That’s a huge mandate for a leader whose team, for the most part, is under-resourced.

We find in conversations with companies as we’ve been talking to them about AI investment and transformation and implementation work, that as they look across the business at all the different functions, HR tends to be one of the last ones to get funding for project work.

Well, that kind of makes sense, right?

Why wouldn’t you plow money into the sales machine and marketing, right?

HR tends to be one of the last functions in the organization to get funding.

And against this big mandate right now, in the middle of the year, kind of where the wave is crashing, they don’t have the resources to get this job done.

So it’s going to be a problem for business going forward.

So really investing in the talent organization, just from an existing status quo operational perspective, is a fundamental thing we need to be looking at.

But then there’s also this, go all the way back to the beginning, you were describing, Telling said, in many cases, they didn’t come from a technology background.

So this is a little bit new to them.

It sounds like there’s some gating factors, just for organizations as a whole, around getting the talent organization up to speed to serve them.

But I imagine you found several other areas in the research as well.

Talk to us about some of those factors, and where does talent fit in in terms of the priorities?

Because if it’s so easy to invest in sales and marketing, how should leaders be thinking about where to invest right now?

What’s funny here is we did some research based on a tool that we developed as we launched Knownwell in the first place.

So the AI Transformation Readiness Assessment.

10 measures in 5 groups, 30 questions, all of the moving parts associated with getting transformation right as an enterprise.

And at this stage of the game, I think we’ve got 50 or 60 companies who have participated, and we’ve run the data, run sessions with companies individually, and taken a look at the at the results.

And when they evaluate themselves, this is by the way, CEOs and leadership team, when they evaluate themselves on the places where they are most and least ready, number 10 out of 10 on the list, least ready is talent.

The least amount of thinking has gone in to what are the implications of change on our talent base?

What different skills do we need to have going into a world that’s AI powered?

How should we be thinking differently about our workflows and our structures?

Wow.

It is very much either not thought of, and I know this from conversations with the teams, either not thought of or just kind of treated as we’ll get to that.

When the time comes, but of course, this is the work that is longest pole in the tent from a lead time perspective, right?

Right.

Actually getting people to fundamentally change the way they work and learn new skills and work in new structures and functions and processes is 18 months of work, not eight weeks worth.

So I will say to the credit of the leaders taking the assessments, they recognize that it’s a place where they are least ready.

It’s just not a place where they’re spending time yet.

Yeah.

Fascinating.

What’s on the other end of that spectrum?

So of those factors, where are we excelling?

If the people aren’t even ready, how can we be ready in any part of the organization?

Yeah.

So typically, what scores best is questions around knowledge and strategy.

So especially on the leadership team.

The CEO, sometimes prompted by the board, sometimes on his or her own, has done the work of getting the team aware, put them through in some cases an initial strategy session, some initial education to make sure that they’re clear on what the basics of AI are and what the implications for business could be, and have done some workshops to understand maybe what the implications for the business might be long term.

So they’ve taken steps, like honoring the fact that it’s a top three priority.

They’re doing the work.

Typically, also, leaders will say they have started the work of investing in the right technologies to underpin the ultimate work of AI.

And a lot of times, they’re thinking of cleaning and organizing and centralizing data to be used and so forth.

And that’s great, because that’s a long lead time item.

Also, what it suffers from, of course, is it’s not always done in the context of knowing exactly what the applications and uses are going to be.

And also, part of me thinks with some amount of time, there will be AI-powered solutions that allow you to step around the ugly, messy, expensive step of tying all of your data together.

But that’s a better question for you to answer than for me.

In the middle, there are some really interesting stories about the other drivers of transformation readiness and one that I love to point at is the questions around leadership and culture.

So for the most part, these are the levers where when executives take the assessments, you find the greatest standard deviation in responses.

They’re scoring in the middle, but half the group thinks they score poorly and half the group thinks they score off the charts, whereas the technology question and the talent question, there’s a concentration of response.

They’re in agreement on that.

Yeah, right?

And what we find in conversation with these teams is that on leadership, you either think your people are awesome and are ready to handle any challenge coming their way, or you’ve had the benefit of seeing just how disruptive this technology can be and you feel like you understand this leadership team is up against something that it’s not quite ready for.

And so having those conversations and getting people to see the differences and try to find a way to think similarly about the challenges is terrific.

That is fascinating.

Just to point out, you’re talking about leadership and culture.

Again, something that a great organization that has strong HR leadership should be at the center of, right?

And a critical piece of.

Yes, absolutely.

Absolutely.

And to your mention, culture is the other piece.

And it kind of follows the same form as leadership.

People either think our culture is strong and can withstand anything, or they think we don’t even know what the implications are for culture on what’s coming with the AI wave crashing on our beach.

And we need to get down and dirty and understand, like, are the things that we stand for playing out in the business the way they should?

Should we rearticulate them?

Like, what are the implications for mission vision values, strategy, ideology?

And so that’s good thinking as well.

As you’ve been listening, you’re probably wondering, is my company ready for the AI transformation that’s here?

You can find out by taking our AI transformation readiness assessment that Pete and David were just discussing.

Go to knownwell.com/assessmenttoday.

Fill out that short survey and get immediate results that show you how prepared your company is for AI transformation across five key categories.

You can also visit the nordlight.com to learn more about the AI consulting and advisory services business Pete and David referenced early in the interview.

John Evans is the VP of Managed Digital Transformation at Impact Networking where he’s building a team to handle their own internal transformation to become AI enabled.

He recently sat down with Pete Buer to talk about what it means to become an AI enabled company.

John, so great to have you on AI Knowhow.

Welcome.

Hi, thanks Pete.

Could you help listeners with a bit of context on Impact Networking, your role and where AI fits in?

Sure.

Yeah.

Impact Networking is a national managed service provider, mostly focusing around IT and technology concerns.

Our main audience, our main marketplace is the SMB.

How AI fits into that space?

I think I’m qualified to comment on this as I am the now newly appointed Chief AI Officer here at Impact Networking.

Ask me about that next, but let’s keep going.

Yeah.

How AI fits into that is pretty straightforward.

First of all, how can we use AI most effectively in our business, both to enable people from a user experience perspective, to have the best possible jobs that they can have, and then also how can we extend those kinds of efficiencies and that thinking out to our customers in the SMB space.

As between figuring out what the technology tool use case application looks like and plowing energy into migrating talents to the new approaches, where’s the real work?

Oh, the real work.

So there’s, I mean, there’s a fair amount of things in there, right?

Like, there’s a lot of work in just disaggregating the use case into like why it matters, you know?

Why does it matter to the organization?

Why does it matter to the user?

Then there’s a lot of work to then realize what technology is going to meet that particular outcome, and how do we orchestrate that technology?

How do we find the right partners?

All of those sorts of things.

Then there’s the actual implementation and building portion of it, and that we have some very talented people, particularly head up by my friend Chris Kukla, who is a Director of Technology in the AI space here at Impact.

So he and I work very closely understanding the landscape of AI as a whole, right?

So there’s a lot of research that goes into staying relevant and current in this space that’s moving, right?

Then figuring out like from that research, what matches to the use cases or what are we going to build?

What are we going to buy?

Who are we going to partner with?

Really, all of that feels like work.

Like there’s a lot of it in there.

But then the hidden layer of it is, okay, once all that’s put together, then how do I get it into the hands of people to use?

How do I monitor their experience and understand what needs to happen from a continuous improvement perspective to keep those things relevant?

This to me feels like it’s an entire pipeline of things that need to be done at each and every use case.

I do wish that there was an easier answer, and some people pitched these kinds of things to me early on in the AI Wild West.

Adopt Platform Z, and Platform Z is going to enable all of these things.

But really, it’s like Platform Z and A and some custom programming, and a whole layer of crazy data that has to make all of that ecosystem work.

It’s a lot to unpack.

Does every company have the same bowl of spaghetti to sort out, and should every company have a chief AI officer?

Yeah, that’s a really good question.

I have, even though this is my title, I have a sort of conflicted opinion about it, right?

So like, no, I don’t think everybody needs a chief AI officer.

But what I do think everyone needs to be paying attention to this technology.

As far as their bowl of spaghetti is unique, like it is their bowl of spaghetti, but it really, it does exist.

The complexity of that spaghetti exists on a continuum that is relatable to most people.

And what I found is first, it’s the organization might need education.

They might need to understand what’s possible in this particular space.

Why does it matter?

That’s the kind of question I hear often is like, why does AI matter to a $60 million manufacturing company in the Midwest that’s been the best widget manufacturer for 100 years?

Right?

Why does this matter to us?

And helping them understand what this evolution in this landscape is really going to mean to them.

Right?

So understanding how all of this unfolds is really the first tug at that overall spaghetti knot.

Right?

What do you know?

Where are you?

And where do you think you want to be?

Right?

And also, what do you think your competition knows?

That’s the other main point.

Right?

But from people who have already passed through that education gate, the next thing that happens is really around their infrastructure.

What data do you have that actually supports these AI use cases?

What technology are you currently understanding?

If I walk into an organization and everything is paper-based and they’re using CRTs and everybody’s answering a ringing telephone, my approach in how I’m going to have this conversation is different than some other organizations that might have some systems that are unable to be accruing some data.

So data and foundational things, then you get to the point that everyone wants to start at.

Everyone wants to start at use cases.

They all, everybody wants to show up and say like, here’s the eight use cases we want to enable that you think are going to matter.

And then the first thing that inevitably happens is we find out they have no data or infrastructure to support those use cases.

So from education to infrastructure, to use cases, to use case prioritization, and then finally to the work of doing the implementation.

That’s kind of my system of how I unpack that bowl of spaghetti for every organization.

There’s commonalities in where the problems are, when we get down to the nitty gritty, but for the most part, it exists.

And somewhere along that continuum is where they need intervention to get this thing to actually work in the way it should.

In conversations with leadership teams who are trying to make sense of the AI opportunity for their business, it feels very much like people are pulling together the boulders and mixing mortar, trying to figure out how these pieces are going to assemble.

But they don’t so much have a vision of the castle, the cathedral on the hill that they’re working toward.

Can you paint that?

What does an AI-powered enterprise look like?

What are its hallmarks?

Yeah.

That’s a great question, right?

I think first, if I continue the line of how does this affect users?

How does this affect individual people, right?

I feel like what you get from the situation where you’re in an AI-enabled organization is you have people that are empowered.

You have them bridging the gap of what information was available to them before, and what do they know now, or what can they find, or how can they be empowered to do their jobs quicker?

I feel like it closes the gap of expertise.

It brings everybody closer to the idea of, I can do the things that I need to do confidently and quickly.

I think culturally inside of an organization, that alone is a gigantic transformation.

Yes.

The future of an AI-enabled organization should have the right level of staffing to perform the tasks that need to be performed and have those employees working through it in a confident manner that prioritizes their humanity.

They are not performing the tasks of machines, but they are in fact performing the tasks that human beings are uniquely qualified to do.

Awesome.

John, thank you so much.

It’s been a delight.

Thank you, Pete.

Appreciate it.

Thanks as always for listening and watching.

Could you help me out?

Because our team over here, we’re having a debate.

I have lots of podcasts that I listen to, but I don’t subscribe.

Apparently, I might be strange, but maybe you are too.

If you haven’t subscribed to this show, if you do that right now, that would be great.

It really helps more people find the show, and it ensures that you don’t ever miss out on anything.

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

Hey, ChatGBT, how’s it going?

This episode, we’re talking about the AI Transformation Mandate.

What do you think?

AI Transformation is really pushing companies to rethink how they operate, from automating tasks to enhancing decision-making.

It’s exciting, but also a bit daunting, especially when it comes to keeping up with the speed of change and the ethical challenges that come with it.

Now, you’re almost in the know.

We’ll be back next week with the second part of David and Pete’s discussion.

You won’t want to miss it.