Why Your AI Strategy Is Probably Going to Fail

Workforce Alchemy

Artificial intelligence is changing the workplace fast, but buying AI tools is not the same as having an AI strategy.  In this episode, Mason Duchatschek talks with Ben Tasker, an AI education and workforce transformation leader, about why AI adoption succeeds or fails based on people, skills, communication, and change management.  Ben explains why CEOs, business owners, executives, HR leaders, and team managers need to focus less on chasing the newest AI platform and more on building an AI-ready workforce. They discuss responsible AI, prompt engineering, employee anxiety, AI governance, workforce upskilling, and how leaders can introduce AI without creating unnecessary fear or confusion.  You’ll learn how to think about AI as a business transformation issue, not just a technology project.  Topics covered in this episode:  • Why AI strategy fails when leaders start with tools • How to build an AI-ready workforce • Why human skills still matter in the AI era • How to reduce employee fear around AI and job security • The AI skills leaders should hire for today • Why prompt engineering matters across roles • How responsible AI reduces business risk • Why AI implementation requires change management • How non-technical professionals can start using AI • What CEOs should do before investing in AI tools  Guest: Ben Tasker Host: Mason Duchatschek  Learn more about Workforce Alchemy: https://workforcealchemy.com/  Connect with Mason Duchatschek: Website: https://masonduchatschek.com/ LinkedIn: https://www.linkedin.com/in/masonduchatschek/  Connect With Workforce Alchemy: Facebook: https://www.facebook.com/ReverseRiskConsulting Instagram: https://www.instagram.com/workforcealchemy/ X / Twitter: https://x.com/WorkAlchemist Rumble: https://rumble.com/user/WorkforceAlchemy Dailymotion: https://www.dailymotion.com/WorkforceAlchemy YouTube: https://www.youtube.com/@WorkforceAlchemist  Keywords: AI strategy, artificial intelligence, AI adoption, AI in business, workforce transformation, AI change management, responsible AI, human centered AI, prompt engineering, upskilling, reskilling, future of work, employee training, AI governance, CEOs, business owners, HR leaders, workplace automation, leadership, workforce development  #AIStrategy #ArtificialIntelligence #AIAdoption #FutureOfWork #WorkforceTransformation #ChangeManagement #ResponsibleAI #Leadership #BusinessOwners #CEOs #HRLeadership #Upskilling #WorkforceDevelopment

Transcript

00:05Welcome to the Mason Ducatech Show.

00:08And before we jump in, this episode is brought to you by WorkforceAlchemy.com, a place where

00:15business owners and executives go to uncover profit leaks hidden in your everyday operations.

00:21Today's guest is Ben Tasker, a leader in artificial intelligence education and workforce transformation.

00:30Ben has served as an AI program director and professor.

00:35He's built applied AI certifications for more than 225,000 learners and speaks widely on

00:44how organizations can humanize AI adoption for real business impact.

00:50He helps leaders bridge strategy, skills, and sustainable change so that their people thrive

00:57in the AI era.

00:58Ben, super glad to have you.

01:00Welcome to the show.

01:01Thanks for having me, Mason.

01:02I'm excited.

01:03So you said that AI strategy often fails because leaders focus on tools instead of people.

01:11What are the first questions CEOs and executives should ask before adopting AI in their organization,

01:18in your opinion?

01:19AI is changing all the time.

01:21In fact, it's changing so quickly that within 30 minutes, by the time we're done recording

01:26this podcast and by the time listeners are done listening to it, AI is going to change.

01:31There's going to be a new news article, some new application.

01:35So instead of focusing on tools, you really have to focus on the skills.

01:38Just because you have AI tools doesn't mean you have an AI strategy.

01:41But the skills behind AI, they have a higher shelf life because how you prompt AI, how you

01:48can use AI in your workflows, how you can mitigate risk, those skills, training your employees now

01:55have a much longer term impact than deciding what tools you need because a tool you might

02:01get dedicated to might change and might be sold.

02:04They might not be in business anymore.

02:05So I really like to stress that organizations, even though you're moving quickly, yes, we

02:11are moving through this AI between times together.

02:14And I can explain that a little bit more after.

02:16But you really have to sit down and you have to think about what skills do we want to teach

02:20our employees?

02:21How are we going to teach those skills?

02:23And it's really change management.

02:25So the next second question is, what's our change management plan?

02:28How are we going to build AI out across the organization?

02:33It's interesting how you talked about how fast things change.

02:37I can remember even a year or two ago, maybe 18 months, realistically, probably 18 months

02:42ago, I knew people in companies where they were, and most of those were nonprofits, but

02:47still they were organizations.

02:48And they're like, you're not allowed to use AI.

02:51And I'm like, okay, really?

02:54I mean, it was like prohibited in the company, like, oh, we can't have that in there.

02:59Wow, what a change just 18 months brings.

03:03Now it's just like, why would you not?

03:06But anyway, we'll get into all that stuff, I'm sure.

03:09So in your opinion, what does a successful AI transformation look like when it's centered

03:14around human skills rather than just technology adoption?

03:18So Mason, you brought up a really good point there.

03:20You said human skills.

03:21So for listeners that may not know, I really like to emphasize the World Economic Forums

03:29skills taxonomy.

03:30The reason why I like it's pretty simple.

03:32There's two skills lanes, AI skills, systems thinking, coding, traditional technical skills.

03:39Maybe it's prompt engineering.

03:41And AI is going to be able to do those skills really well.

03:44But right now they're paying a premium because humans are still doing it.

03:47And then the other swim lane, human skills, think empathy, think leadership, think communication.

03:54Yes, AI can resemble and mimic some of those skills, but those skills are going to be universally

04:01human.

04:02Humans are still going to excel at those skills because just because you can resemble something

04:05and mimic it doesn't mean you actually can do it.

04:08And humans can do it.

04:09AI, no matter how good it gets, won't be able to do it.

04:12So human skills are important to think across all roles along with AI skills.

04:17And then I kind of like to think of an organization like a cake.

04:21So you have the base of the cake, the foundation, that's your frontline workers.

04:25Maybe that's 80% of your worker base.

04:28How are they going to use AI?

04:30Really that systems-based approach, really understanding the skills and the change management,

04:35and then linking what you want these employees to do to actual learning.

04:41So you have to create a learning culture.

04:42And then you get to the middle of the cake.

04:44And that's kind of your AI-enabled specialist layer.

04:47So these are individuals that may already have advanced degrees like myself in data science

04:53and AI.

04:54They might be robotics engineers.

04:56They could be project managers.

04:58They could be business leads, program managers.

05:01They're not just your front door employees.

05:04They're the employees that can work behind the scenes.

05:07And they're more operational.

05:08But they might need a little bit more training, a little bit more depth.

05:11They might need to understand how to code a little bit to set up your AI systems,

05:16where the foundational crew, they might just be doing AI to help.

05:20And I hate comparing it to automation, but they're going to be using AI for more advanced automation.

05:25And then you have the top of the cake where the frosting and the sprinkles sit.

05:29And that part of the cake is your leader.

05:30So how are the leaders communicating to the rest of the organization?

05:34Why AI is important?

05:35How are we transitioning for the future?

05:38How doing this now actually helps protect your job versus lead to elimination?

05:43And it really is more methodical than just a chainsaw approach.

05:48So by incorporating that change management, by slowly baking the cake,

05:52it's really more effective than organizations that are trying to rush through this,

05:57quickly implement some tools.

05:58And then if you look into this, 95% of organizations that forget the change management

06:03or forget the upskilling, forget the reskilling, don't consider the different tiers of their organization.

06:0995% of those organizations fail in AI implementation.

06:13So what that really means is they spend a boatload of money and they get nothing out of it.

06:18Whether the AI is successful or not, just because they don't have the people behind it.

06:22I've spent a lot of time in HR strategy sessions.

06:26And we've talked about with, I've talked with senior leaders about how do you adjust in strategy

06:34and what matters and what's important.

06:36And in the old days, it used to be a little easier.

06:39You had these, if you're hiring someone for accounting, they had accounting skills.

06:43If you're hiring someone for engineering, they had engineering skills.

06:46And what a lot of them are talking to me about now is adaptability.

06:51It's like really what you did before was great for the way the world worked before,

06:56but now the things are different.

06:58It's not what do you know?

07:00It's what can you learn?

07:01How quick, how can you adapt and assimilate and grow?

07:04And I'm hearing people talking about things like coachability and adaptability way more

07:10than, oh, well, they got straight A's in their computer science classes.

07:15That's great.

07:16You're spot on, Mason.

07:18Adaptability and flexibility are two of the top skills.

07:21They actually outrank all of the AI skills.

07:24And I think it's going to continue that way just because organizations are rapidly changing

07:28and you need those two skills to change in these times.

07:30And I think about people who I know, you talked earlier about how, how fast things are changing.

07:36Like I just learned to use this system and I really mastered it this way.

07:39And all of a sudden that system's gone something.

07:42And then you see them all frustrated.

07:43Like they just wasted their time.

07:45And like, but no, like you got to keep evolving with it, but you'll get me on a rant there.

07:49But I, I am fascinated by this topic, which is why I wanted to invite you on.

07:53So how should executives in your opinion, balance long-term AI ambition with real world risks,

08:00such as, let me see, ethical concerns and data governance issues?

08:05So all AI, even more simplistic AI, all AI has risks.

08:10I like to call it responsible AI.

08:12So it's not just compliance.

08:15Responsible AI takes individuals across the organization and you really weigh out the risks

08:21of whatever you're trying to implement.

08:23And you do that before any type of implementation.

08:26Yes, it might take a little bit longer to do this.

08:28But if I'm trying to implement even a simple chat bot to answer some IT tickets, you should

08:35have some people from IT there.

08:36You should have some people from HR there.

08:39Just because what happens if you misclassify or whatever, you want to have some business

08:43owners there, people that actually understand the ticketing system and how that works today.

08:48So there might be 10 to 15 people on this, but then that really helps set up that system.

08:54You can then create some guardrails and some rules.

08:57Like what happens if we do misclassify a person or a ticket?

09:01Or what if, you know, if this is more agentic AI, which means it's more automated?

09:06What if this tool gets a little bit more intelligent and does something it's not supposed to do and

09:11damages the system because it thinks it's supposed to do that?

09:14How do we mitigate that risk?

09:16How quickly can we shut this off?

09:18Is that baked into this or have we not thought of that?

09:22How are we measuring the prompts that are going into it and the user engagement?

09:26Are we doing that?

09:27Is it anonymized or de-anonymized, meaning that we can look it up and see what everyone's

09:33doing?

09:33Or is it anonymous where it's random, but we can still see what everyone's doing?

09:37And depending upon that recipe and the different levels of risk, then you can really set up

09:44a successful AI implementation.

09:46But I think it's really important to understand that in this responsible AI roadmap, you're

09:56also putting into the change management.

09:58So I just want to reemphasize that this is part of that change management.

10:01I'm not calling it risk and compliance.

10:04It's its own separate entity.

10:05There's going to be bias risks.

10:08There's going to be accountability risks, like if this thing does hallucinate, who's

10:12responsible for it?

10:13And yes, some things are lower risk, but a lot of people want to go for the highest level

10:18of AI without understanding the lower levels of AI.

10:22And companies are going to keep doing that.

10:25And it's just going to keep getting riskier and riskier.

10:28So you've helped build programs that made thousands of professionals AI ready.

10:35What are some common misconceptions about AI skills that most leaders still have?

10:40It's fast.

10:41You can do this really quickly.

10:42To learn new skills at the rate you need to learn them, especially if your organization

10:47hasn't really explored AI, to your point, if they shut it off and now are just getting

10:51into.

10:52It takes about 18 months to bring someone from a level one.

10:55They don't really know what AI stands for, let alone use it to a level three where they

11:00can successfully prompt a chatbot, use it for common tasks, take the output, iterate

11:05on it, put it back into the chatbot.

11:07That takes 18 months.

11:09To get someone for a four or a five takes even longer than that on a capability scale.

11:14In some of these AI domains, you need advanced degrees, like robotics, for example, drones.

11:20That might take five to six years to train.

11:23And a lot of the executives are like, well, how quickly can we implement this?

11:27My answer to that is how quickly can we upskill and reskill our employees?

11:32Even if these aren't skills that we're looking for now, all jobs are going to be impacted by

11:37artificial intelligence.

11:38We might as well start with the reskilling and the upskilling because of that change.

11:44But also, even though on paper, this might take time, there's cost to that.

11:48It's cheaper than less expensive than just going up to the market and hiring for each

11:52niche, niche skill that we need because you're never going to ask about that.

11:56I was going to ask about that.

11:58Like, do you have any specific tips on in that area between the upskilling and hiring?

12:05What are your thoughts there?

12:06I mean, I think upskilling is extremely important.

12:08You're going to have to develop that for all your employees.

12:10I think for super niche projects, maybe robotics, drones, it's really dependent upon what your

12:16organization does.

12:18But if it's super niche that you might need a specialist for, then that's when I because

12:21you can't really train for that, right?

12:23You have to have that expertise.

12:25With that being said, though, a lot of organizations, when they think of AI, for some reason, think

12:31of the more advanced versions of it, but they can't see what's directly in front of them.

12:36So I also recommend maybe focusing on some of the lower hanging fruit for the ROI.

12:41So what processes and problems can we fix?

12:44Is there a form that individuals need to fill out that you can just create an agent for?

12:48It fills in the form and then submits it.

12:51Maybe time sheeting can be replaced with an agent.

12:54Kodak has an AI agent with their driverless truck system.

12:58And the agent asks each driver before the door unlocks on the truck, whether it's driverless

13:03or not, to understand if they're feeling well that day.

13:06And if they're not feeling well that day, they're asked to go home and they're still

13:09paid.

13:10But it's a safety concern.

13:11So how is that something that your organization can do?

13:15Eight questions, the manager's notified, they can't get in the truck, they're not losing

13:20pay, so they're incentivized to learn.

13:21And when I say change management, those are the things that I'm talking about.

13:26So you talk about human-centric AI.

13:29What does that look like in everyday business operations?

13:35So human-centered AI, exactly what it sounds like.

13:39There's a human in the loop.

13:40So all these decisions just aren't made in a boardroom.

13:44You have the entire organization experimenting and using AI, finding pain points where it

13:50may be successful and where it may fail.

13:53And that learning, right, that's creating a learning culture.

13:56That's another way you can do upskilling and reskilling because you're sanctioning it at

14:00that point.

14:01Instead of saying, we're not doing it, everybody's encouraged to do it.

14:04You can then create what I like to call a backlog or a problem list of where AI might

14:10be helpful.

14:10And then that can go to the specialists and the leaders.

14:13And then you can kind of assign value to some of those complexities.

14:18And then based upon that value, you can decide which AI projects and implementations you

14:23want to pursue for the year versus the ones maybe you don't want to and you can attach

14:27risk to it better.

14:28So even though it seems unorganized because we're allowing everybody to do AI at the same

14:34time, it doesn't necessarily have to be.

14:37It can be organized chaos instead of unorganized chaos.

14:41But that's one way that I would approach it.

14:44So can you maybe share a story where AI adoption increased trust and performance rather than resistance

14:51inside an organization?

14:52Yeah, absolutely.

14:54So I'm going to go back to Kodak.

14:56So back in 2018, before driverless technology, physical AI, deep learning technology was even

15:03being discussed, they knew that and Kodak's a camera company.

15:07Kodak has trucks on the road for shipping and there's going to be less truck drivers in the

15:14future because of the demand.

15:17They take time to train and there's just not enough truck drivers between that one organization

15:23and all other organizations.

15:25So they were leaning into driverless truck technology.

15:28So think of a semi-truck.

15:29These semi-trucks today can now drive themselves, but they didn't start that way.

15:33So initially, they had to figure out how to design a driverless truck.

15:37So that was part of the change management.

15:40Then they had to figure out which routes a driverless truck could go on.

15:44Then they had to figure out how the driver could drive in the truck still so that the

15:49AI can learn.

15:51And were some of the assumptions correct?

15:54Like, for example, can it park itself?

15:56Does it know how far it can go?

15:57Some of those questions that on paper might make sense, but I own the road or may not.

16:01Where and where can it drive?

16:03Does each state allow this?

16:04Is it only in specific regions?

16:06What's the responsible AI?

16:08And then how do we get the buy-in across the organization?

16:12So they really attach to that safety aspect.

16:15A lot of truck drivers sometimes do get injured or they have to sit for a long time.

16:21It could cause mental illness as well.

16:23And they still got paid while they were training it.

16:25So they got paid overtime.

16:26So that's a human in the loop approach because there's still trucks at Kodak that don't drive

16:32themselves.

16:33They have more than 100 truck fleet.

16:35It's a very small percentage of their fleet that is driverless.

16:38And it's doing very specific tasks that a driver probably wouldn't want to do.

16:43So they actually need more drivers than less because of that demand curve.

16:48So jobs weren't really impacted.

16:50And they really thought through this implementation system more than just the AI.

16:55It was a human first approach, not an AI first approach.

16:58So for leaders that are hiring new talent today, which AI competencies matter most and

17:04which ones are just simply hype in your opinion?

17:07The AI competencies that matter most would be prompt engineering because all types of AI

17:13that most employees are going to use need some sort of prompt framework or prompt engineering

17:18to it.

17:18And it might sound simple, but there is some art to it.

17:22And different technologies use different prompting styles.

17:25So you need to know when to use what when you need to know responsible AI.

17:29So I would make sure that we're hiring for that, making sure people understand the risk

17:33tradeoffs, flexibility, adaptability.

17:37Like you were saying, that's harder to put in a job spec, but it's something that you could

17:42probably flesh out in the interview.

17:44And I would also try to look for AI skills across all domains because then that can help

17:51bake into your upskilling plan.

17:53So if you're in digital marketing, for example, and you typically don't require people to know

17:59generative AI tools, maybe you put a job spec out there that does require that with all

18:04the other specs just to see what kind of talent you can attract.

18:08And then that individual can help upskill the rest of that department while at the same time,

18:15you know, they're prepared for the future of work.

18:16So you're moving together more in tandem.

18:19So it's also a little bit of thought into that, right?

18:22Like it's not just like we're not exactly sure all the skills, but we know some things

18:26are going to stick around.

18:28So why don't we try to hire for some of those skills now?

18:31So how can managers support employees who feel, I would argue in many cases, justifiably

18:37anxious about AI replacing their roles?

18:41So there was actually a recent study in the Wall Street Journal.

18:43There's, to your point, more animosity towards AI than positivity.

18:48I think that's because the news, there's all these wordings around layoffs and change.

18:53And I don't, I mean, there is some positive news, but it's like a hundred to one.

18:57And in that part's opinion, I haven't looked, but there's way less positive news than, but

19:02I think AI can have a positive impact on organizations.

19:05Upskilling benefits you.

19:07It's paying a premium right now.

19:10AI individuals and organizations that are embracing AI and that have AI skills are producing

19:16a 52% more revenue than organizations that aren't.

19:20How that trickles down to the employees that they can make more with these AI skills.

19:24Also by learning them, whichever way the organization goes, you have these skills and it's easier

19:31to move individuals into new roles that don't really exist yet, but still have AI components

19:36than individuals that don't have those skills.

19:39It's harder to organize that into the org chart.

19:42And this technology is just going to keep changing.

19:44AI agents are very popular.

19:46There's physical AI, the technology that can drive itself.

19:49Now, who's managing that?

19:51Are we going to have individuals that don't know AI managing that?

19:54Probably not, right?

19:55So even though we might not have it in our organization today, how are we going to plan

20:01for that six to nine months from now?

20:04So what advice do you give to professionals who do not consider themselves technical, but

20:09want to thrive in an AI enhanced workplace?

20:12So AI doesn't have to be complex to learn.

20:16Yes, there are experts that have PhDs, master level degrees, but learning can be fun.

20:22You don't necessarily need that level of knowledge to use it for basic knowledge jobs like project

20:27management, finance, even executive leaders don't need that level of knowledge.

20:32They just need to know the skills to apply to the AI technology that's relevant at the organization

20:39today.

20:39So I would try to make it fun.

20:41For me, when I started using large language models, AI-assisted tools, I had it make a

20:48workout plan for me.

20:49I took a picture of all my equipment, then loaded that equipment into the AI agent, and

20:56I asked it for a specific type of workout.

20:58I do CrossFit, so I asked it for a CrossFit workout, and it was able to spit it out.

21:02I didn't have to type.

21:03I had the pictures over time because AI is personalized.

21:07I knew what we were doing, so I didn't have to prompt it as heavily.

21:12I then was like, hey, you know, this is kind of fun.

21:14What if I take a picture of the food in my refrigerator and ask it to make a meal plan

21:19for me?

21:20Again, all pictures, no words, something I wouldn't do normally.

21:23And now it's taking the workout with what we have for dinner, and it's optimizing for

21:28it.

21:29A fun way to understand the limits of the technology to see if it's true.

21:33Some of the recipes were not that good, but it tried.

21:36Sometimes it can't determine what you're taking a picture of because either the label is generic,

21:42but that's a limit, right?

21:44That applies to work.

21:45But then how can I apply this fun learning to work?

21:49So that's prompt engineering, risk, what to put in it, what not.

21:52I put in food and workouts.

21:54I didn't put in top secret information in there, right?

21:59So it minimized that risk.

22:00And then that really can set up an individual for success.

22:04Yes.

22:04So and that got me comfortable with it.

22:06So I could trust it because I think trust is an important factor there, because if it's

22:10wrong on the first or second use, you're probably not going to use it again.

22:13You're just going to shut off, especially if you're resistant.

22:16So that built the trust.

22:18And then I could take on, can I use this for coding?

22:20Yeah, obviously you can.

22:22But is it right?

22:24Because we're not sure that it was OK.

22:26You know, and this was a long time ago.

22:28And now today it's much better than it was then.

22:31Can I use this for data visualization?

22:33Can I use this to make infographics and slides?

22:36So I guess the other counterpoint to doing something fun is maybe try to do something

22:41or find something you don't like to do and how you can use AI to make that task more quickly.

22:47So an example of that might be using AI to organize your email box so that higher relevant

22:53emails are on top and lower relevant emails are on bottom, just so you can shift through

22:57your day and then maybe make a task list or automatically update your calendar.

23:01That right there can save you up to an hour, at least now you have an hour back.

23:09So as AI continues to evolve, what are the most underappreciated shifts that organizations

23:15are not preparing for today?

23:18I think a lot of organizations and rightfully so it's most of the hype, but AI is moving in

23:24their mind quicker than it actually is.

23:27I mean, AI is moving fast, but I think a lot of organizations already think we're out of

23:30that AI between times.

23:31So we're still trying to figure out what this AI thing is and companies already think it's

23:35solidified and it's defined and that's causing a lot of mistakes.

23:39But I think those mistakes are going to become more amplified.

23:42I call them AI whoopsies.

23:43Like we implemented a chatbot and it told all our customers something it wasn't supposed

23:48to like, whoops, like that's going to keep picking up.

23:51So really understand that there's risks associated with the AI that you don't have to move as

23:57quickly as every other organization doing this methodically actually might pay dividends.

24:02You need an upskilling and reskilling plan for your organization, especially as you get

24:06to the more advanced types of AI.

24:08How are you going to factor that in?

24:10What kind of jobs may you need, even if you don't have a definition of it?

24:14And then how are you going to change the organization's culture?

24:18So the change management, this isn't just a regular technology or a ticketing system or

24:23a marketing system, it's a technology that can learn, that can become personalized.

24:30It could really impact the business.

24:32It's much different and it's going to continually change to be much more different.

24:37So how are we becoming different with that?

24:40I'm interested in your opinion on this because I know people soft shoe around it and you can

24:44see it a mile away.

24:46Business, there are people that are legitimately scared my job's going to be gone.

24:53And they hear from management, I'm using air quotes for those that are listening and not

24:57watching the video, that, oh, no, no, this isn't going to, this isn't a risk to your job.

25:02This is about enhancing who you are, which I get, but when the employees who are fearful

25:09of losing their jobs hear someone say, oh, no, no, this is just about enhancing you and

25:15they don't believe them, some of them justifiably so, not all, of course, what do you say for

25:20your management?

25:21I mean, because that's a tough call and I know that's a little bit putting you on your

25:26spot.

25:26So in your opinion, you run an organization and you got people that some people's jobs

25:33are more at risk than others because things are changing for obvious reasons.

25:36I get it.

25:37I understand it all.

25:38But if people are that fearful and you're in charge of the company, what do you say

25:46to them?

25:48I mean, in my opinion, I guess it depends on how large this audience is, but some organizations

25:53have already tackled this problem.

25:56And so I'm a data-driven individual.

25:58But for example, Walmart rolled out AI to all their employees and encouraged them to use it.

26:05So they gave everybody free licenses.

26:06They can use it at home.

26:08They can use it at work.

26:09It didn't much matter as long as you were using it.

26:12And then that then changed the culture to become a learning culture.

26:16And then not Walmart, but other organizations have also embraced if you learn AI, if you go

26:23onto these learning tracks, if we do try to enhance it, there won't be any AI-related

26:29layoffs for three years, four years, five years.

26:33So it makes employees feel safe around that change.

26:37Honestly, to get any of the ROI successfully anyways, you probably need that amount of time

26:43because if you make a decision too quickly, there's a lot of organizations that think AI

26:48is fully implemented.

26:50I mean, go look up a news story.

26:52There's a bunch of them.

26:53An entire 30,000-person organization will go away.

26:56And then the next week, they have to hire everybody back because the AI wasn't as good.

27:01So yes, artificial intelligence is intelligent.

27:04I'm using air quotes there for people listening, not watching.

27:07But it's not as a lot of people think.

27:12And you really need to understand your business.

27:13So there's some foresight there.

27:15But in my opinion, I think leaders should be transparent.

27:18Jobs are going to change.

27:20The upskilling and the reskilling prepares workers for those jobs.

27:23And it's not a replacement technique.

27:25It's when these things do change, we're ready to change with it.

27:29I love what you're saying there.

27:30That's kind of what I hoped you would say because you're being honest with them and

27:34saying that the environment is changing.

27:36And if you refuse to change and you refuse to adapt, you refuse to grow and you refuse

27:40to learn new things, whether it's AI or anything for that matter, that's a choice you as an employee

27:46are making.

27:47Probably not a good one, whether it's AI or anything.

27:50In this particular context, in this particular discussion, we're talking about AI.

27:54But if you're telling me as an employee, I don't want to learn, I don't want to grow,

27:58I don't want to adapt, and I don't want to lose my job, good luck with that one.

28:03Whatever your field is, in this case, I mean, who in any role, regards to AI, maybe it's

28:10continual learning in the legal field or continual, what do they call it, continual learning in

28:16the HR or in sales or in marketing or like, oh, I don't want to learn this new stuff and

28:22I want to maintain job security.

28:23I mean, come on, that's not realistic anywhere.

28:27So I like that you chose to be open and transparent from the managers.

28:32And I'm using this in air quotes for people that are just listening.

28:35Managers sitting, not filling them full of nonsense, but telling them the truth.

28:39Like, hey, the times are changing.

28:41We're adapting to keep up and we want to encourage you to do the same.

28:45If you're worried about losing your job or having your role eliminated, then stay the

28:50same.

28:50Don't adapt with it.

28:51Don't improve.

28:52Stop developing your skills.

28:53But if you do that in any role in any company, you've reached your career call to sack anyway.

28:59And I think that's extremely important to have those learning tracks.

29:02I know a lot of leaders don't think in that sense, but if you have some learning pathways

29:07for employees to follow so that they know where to go on the menu, then it's easier to

29:14engage with the organization and encourage it.

29:16So then it's not just a blanket statement.

29:18It's like, hey, I really do believe this.

29:19Here's some learning tracks.

29:22If you're not seeing something there, let us know.

29:23But we developed X amount of them.

29:26We're hoping that you embark on your journey.

29:28So if there was only one piece of advice that you could give to business leaders who

29:33are listening or watching today, what would be the most important piece of advice you

29:37could give and why?

29:38I really think a lot of individuals don't consider AI implementation change management.

29:44I know I've said that a lot today, but I would really challenge everybody to think of

29:48AI anything as change management because there's a lot of dynamics, as we discussed today, around

29:54AI, and it's only going to exacerbate.

29:57I think there's going to be less positivity around it.

30:00There's going to be more negative news around it, even if AI has a major breakthrough and

30:05discover something that people thought was never possible.

30:08I think there's still going to be some negativity around it.

30:11So I would really think about it in change management.

30:13How are we going to message this across the organization?

30:15How are we going to design those learning plans?

30:17How are we going to embrace some of these other changes that come along with the AI?

30:22And is our organization ready to do that?

30:24And if there's more nos and yeses, then how can you move those nos to yeses so that you

30:30become ready?

30:30But just rushing into it because everybody else is, that's not a recipe for success.

30:35You're just going to end up as the other 95% of organizations that have tried to implement

30:42this and have failed.

30:44So for people who want to know more about you, your work that you do, what are the best ways

30:48for them to learn more and connect with you?

30:50You can connect for me on LinkedIn, Ben Tasker, and you can go to my website, BenTaskerAI.

30:56There's a meeting link there.

30:57We can set up a conversation, but happy to help you or your organization discover your

31:02learning tracks and your AI capabilities.

31:05Really appreciate your time.

31:07Thank you for sharing your wisdom and your insight and your experience.

31:09I hope everyone else learned as much and enjoyed it as much as I did.

31:11Thank you so much, Ben.

31:13Thanks for having me, Mason.

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