Ep 19: Bridging the Knowing-Doing-Leading Gap for AI-Driven Transformation with Charlene Li

[00:00:09] The HOT's Bob Pover, I had the very good fortune to sit down with Charlene Li at six-time New York Times Best-selling

[00:00:15] author and leading voice in technology that transformation.

[00:00:19] I've long admired Charlene's work and perspective, which have consistently shaped how leaders

[00:00:23] worldwide think about technology's impact on organizations and leadership.

[00:00:28] Our conversation delved into the exciting world of AI-Driven Transformation, scoring its

[00:00:32] distinctions from previous transformation efforts and examining the crucial importance

[00:00:36] of responsible AI in maintaining a human-centric approach as work evolves.

[00:00:42] I'm deeply grateful for Charlene's time and insights which will undoubtedly provide immense

[00:00:46] value to many of you as you embark on your AI journey.

[00:00:50] Take around until the end, Charlene gives us a sneak peek at both for upcoming HR Tech Conference

[00:00:56] Keynote, Address and Turnthrough Book.

[00:00:59] This is A Do Not Miss Episode.

[00:01:01] Thanks for listening.

[00:01:03] Hello again everyone.

[00:01:05] Welcome to another episode of Elevate Your AIQ.

[00:01:07] I'm your host Bob Pover.

[00:01:09] Today, I have the pleasure of meeting with Charlene Li.

[00:01:12] How are you today, Charlene?

[00:01:14] I'm doing great, Bob.

[00:01:15] How are you doing today?

[00:01:16] I'm doing excellent.

[00:01:17] Thank you so much for joining me.

[00:01:19] Good to be here.

[00:01:20] I could just give you the opportunity to do your own introduction about your background in

[00:01:25] the space not just in AI of course but digital transformation and your background at

[00:01:30] all time there, etc.

[00:01:32] I am in New York Times Bestselling Author of Six Books and soon to be seven.

[00:01:36] And I started out as an analyst looking at the internet media and marketing with forest

[00:01:43] research and in 2008 started my own company called Old Timothy Group focused on digital transformation

[00:01:50] and then 2015 sold that to profit, brand strategy and bounced around and corporate jobs

[00:01:55] for a little while and then recently became independent again going back to my entrepreneurial

[00:02:00] roots.

[00:02:01] And I graduated from Harvard College in Harvard Business School and pleased on what that

[00:02:05] against me because I do not have a technical degree, but I'm focused much more on business

[00:02:09] and strategy and leadership and especially the disruptive impact of different technologies.

[00:02:15] Fantastic.

[00:02:16] I know you've been an avid blogger for quite a while.

[00:02:19] I won't date you but I know it goes back quite a number of years and certainly I built

[00:02:24] up quite an audience online on that side of the book.

[00:02:27] Yeah I started blogging actually about 20 years ago this month.

[00:02:31] Oh my goodness.

[00:02:32] It's been exactly almost 20 years to the day.

[00:02:35] It's amazing.

[00:02:36] So one of the things that I thought would be interesting to kick things off and we talk

[00:02:42] about AI-driven transformation, we talk about, you know, remaining human centric as we do

[00:02:48] that.

[00:02:49] But as we think about transformation just the concept of me that work kind of gets overused.

[00:02:54] But as you think about what we're experiencing now or what people are setting out to

[00:03:00] do with this type of transformation, how do you see it comparing and contrasting to what

[00:03:06] you've seen before with digital transformation or social business transformation or

[00:03:11] maybe a transformation within a specific, you know, line of business or domain?

[00:03:15] Yeah sure.

[00:03:16] I can't do it.

[00:03:17] There have been so many types of social business, digital transformation and they

[00:03:21] all have something in common which is some new business trend or technology typically

[00:03:27] comes along and it's an opportunity to change the way you normally do things.

[00:03:32] So that's the status quo.

[00:03:34] And the reason why I feel so disruptive is that it upends the way you think about the

[00:03:38] world and how you fit into it because the way you get worked done is completely changed.

[00:03:44] So it's highly disruptive and the most powerful transformation ones are unfortunately

[00:03:48] the ones that are also most disruptive.

[00:03:51] And AI is a huge transformation because the way we work is based on how we know how to do

[00:03:58] things and AI can in many cases do a better job of doing that than we can as humans.

[00:04:06] So it it upends the way that we do work, it changes the way we relate to each other

[00:04:12] and it also calls into question, this existential question that if a machine can do it,

[00:04:18] what's my value?

[00:04:20] So this transformation is much bigger and we think of it as a technology transformation

[00:04:24] but actually like any other transformation that came before, it's always about people.

[00:04:31] It's about the digital which is the technology side but we forget that the transformation

[00:04:36] side is about the people and how we have to change.

[00:04:39] So in that regard when you think about what it takes to alter people's behavior and drive

[00:04:48] a cultural change and things like that, I guess I'm trying to think of in prior transformations

[00:04:54] like we sort of deputized people right?

[00:04:56] We had champions and change agents and things like that.

[00:04:59] And there was a lot of grassroots efforts that sort of pushed the organization forward

[00:05:05] and created some inertia within individual teams.

[00:05:09] You know, it can't just be bottom up right?

[00:05:12] Now it absolutely can't be and for one simple reason, it is the potential for transformation

[00:05:17] and value creation and benefit to the organization and its customers and employees.

[00:05:23] All its very stakeholders is huge and if you just let little pockets of it spring up,

[00:05:29] you'll see little pockets and little bits of impact.

[00:05:33] So sure we can write better marketing copy with AI.

[00:05:36] But what if you were to rethink the entire marketing process, the way you actually engage

[00:05:41] with customers, that's the most strategic question and that can't be driven by grassroots.

[00:05:46] So the opportunities to completely rethink the way you get work done, how you engage

[00:05:51] with customers, how you do live a product or even develop new products and services is possible

[00:05:57] because of AI.

[00:05:59] You can do things now in create new companies, in new products and services with no new people,

[00:06:06] no additional costs and in the fraction of the time.

[00:06:09] So unless you look at it strategically that way, you'll never get to that point by boiling it up

[00:06:15] from the bottom up.

[00:06:16] So you would argue that now there were entering sort of strategic planning time of year

[00:06:21] that this needs to be front and center rate, your AI strategy align to your business,

[00:06:27] your technical and your talent strategies.

[00:06:29] We have a saying, think big, start small scale fast.

[00:06:34] And oftentimes we're forgetting the first part.

[00:06:36] We're just starting small and hoping we can figure out what to scale without that big thinking.

[00:06:42] And align me at two years strategic opportunities.

[00:06:45] And what your strategy is overall as a business, you'll never get to a point where it becomes

[00:06:49] strategic.

[00:06:50] So as a chicken and an egg here, and that most executives don't feel comfortable with AI.

[00:06:55] They think of us a technology rather than as a transformational strategy.

[00:07:00] And so therefore say it's not my job, it's my CIO's job or somebody overindigital.

[00:07:07] Instead of thinking, oh this could complete transform our business.

[00:07:12] So when you prepare an organization as you talk to the leaders at different organizations

[00:07:18] and I'm sure you did this part of research for your new book and for all the great newsletters

[00:07:24] that you've been publishing, it just seems like everyone wants to make sure they've got some

[00:07:31] voice and some proverbial seed at the table.

[00:07:35] But they may not know what they're actually asking for and what it's going to take to be in that

[00:07:40] position and contribute meaningfully by getting their own hands dirty and upskilling themselves

[00:07:47] and what's possible.

[00:07:50] How do you see people embracing this at a leadership level to make sure that they're as

[00:07:54] stand that they have the opportunity here to really get ahead of this and lead by example

[00:08:02] and learn these skills and become AI literate themselves?

[00:08:07] Yeah, I think you're pointing to a really important requirement which is the C-suite,

[00:08:13] the top leaders.

[00:08:14] I like to think about the top two levels of leadership in your organization.

[00:08:19] They need to have AI literacy and that isn't just having gone in and use chatchipt once or twice.

[00:08:28] I call it bridging the knowing, doing, leading gap.

[00:08:33] You know about it.

[00:08:34] Are you actually doing it using it on in a way that it has transformed the way you actually work

[00:08:41] because until you can see the power of AI directly benefiting you, you can't begin

[00:08:48] to think about how to lead an organization in using AI.

[00:08:53] So I oftentimes speak to audiences or executive teams and I ask,

[00:08:57] how many of you know about it?

[00:08:58] And it's going up.

[00:08:59] How many of you said, hands go up.

[00:09:01] How many of you use it every day?

[00:09:03] All the hands go down.

[00:09:05] You cannot begin to transform the organization unless you have transformed yourself

[00:09:11] in the way you work at it.

[00:09:12] And so I have training for executives and do workshops

[00:09:17] and get them to use AI to do the things you already know how to do.

[00:09:21] And that's primarily creating content to do research.

[00:09:24] And very importantly, to use it as a sounding board.

[00:09:27] Because as a leader, one of those scaringest resources is appear.

[00:09:32] Somebody, you can say, well what about this?

[00:09:34] What about that?

[00:09:35] Here's my plan.

[00:09:36] You evaluate it.

[00:09:37] How could it be better?

[00:09:38] And using it as a sounding board to just up-level your work

[00:09:42] is a hugely strategic use of AI for executives and leaders.

[00:09:48] Yeah, absolutely.

[00:09:49] I think back to some of the transformations that I went through at IBM

[00:09:53] or we made sure that, you know, as people bought into the concept of design thinking

[00:09:58] and that methodology that it wasn't just the designers that went through that,

[00:10:03] it was all the product managers and product teams that

[00:10:06] go through that.

[00:10:07] And all the executives had to go through that.

[00:10:10] So they could start to rethink how they can make longer lasting change

[00:10:15] and make better strategic decisions and not just worry about tactics

[00:10:19] and, you know, quarterly metrics and things like that.

[00:10:22] And then even product management and some of the principles

[00:10:25] that would fundamentally support management and agile

[00:10:28] for important for people who were not product managers to learn how to do that.

[00:10:32] So I feel like this is just maybe that cranked up to 11 at least to learn how to use AI

[00:10:38] just because AI, I don't think of it as a tool but more a tool kit

[00:10:43] that can do a lot of different things depending on the use case and the domain.

[00:10:47] The design thinking approach that you talk about at IBM,

[00:10:50] what I loved about it is that I got trained

[00:10:52] on design thinking by IBM as an analyst covering the company.

[00:10:58] And so it, and I think that's what's happening with AI not.

[00:11:01] The best companies are training people on how to use AI responsibly.

[00:11:07] And so because they want to ensure that everybody inside of their ecosystem

[00:11:10] is using AI and, you know, responsible ways, treating customer and employee data in a responsible way.

[00:11:16] So they can then with full conviction say to customers, yes, we are protecting everything

[00:11:22] we're using AI and responsible in an ethical way up and down throughout the entire system.

[00:11:26] Absolutely. When we think about the opportunities with AI and I use AI more broadly than just

[00:11:34] generative AI, I know that's the top of mind for a lot of folks including many of my listeners

[00:11:40] but when you think of AI more broadly and the ways in which you can be used

[00:11:46] but the people that you've spoken to, the leaders that you've spoken to around

[00:11:50] how they've adopted it, are they still starting to

[00:11:55] small and not thinking big enough and boldly enough about how to do this or they scared that they

[00:12:01] they're not going to have to, know how to measure success. Before we move on, I need to let you know

[00:12:07] about my friend Mark Feffer and his show people tech. If you're looking for the latest on product

[00:12:14] development, marketing funding, big deals happening in talent acquisition, HR, HCM, that's the show

[00:12:22] you need to listen to. Go to the work to find that work, search out people tech, Mark Feffer,

[00:12:28] you can find them anywhere. All of the above, it's so easy looking at the productivity and

[00:12:36] efficiency gains from AI. So hey, if I can just take the productivity gains, you know, I get 10, 20,

[00:12:43] 30%, maybe even exponential levels of productivity, I'm going to use that, slow-hanging fruit. Why not do

[00:12:49] that? But I think you're missing an opportunity and this is the key question around where do you aim

[00:12:55] for and how do you measure the benefit. And I keep coming back to your existing business strategy

[00:13:01] and the reason why people don't think about it this way is because they typically are not thinking

[00:13:06] about business strategy on a daily basis. They have their heads down, they're doing their job,

[00:13:13] they have your OKRs that are very poorly written, very much department or team oriented,

[00:13:20] not business oriented. And so they don't really know how to think about the strategic

[00:13:25] opportunities because they don't think about strategy. And so it falls to a few people who are

[00:13:30] the least qualified to actually think about the AI because they're just thinking about the strategy

[00:13:36] and not necessarily the gaps that are between where you are today and where you want to be.

[00:13:43] And that's what strategy is all about. Like how are we going to get from where we are today

[00:13:46] to where we want to be in the future? And AI using AI very strategically is say,

[00:13:52] how do we plug those gaps? How do we use it to accelerate or defend our strategy? Our go-to market.

[00:13:59] And then the way you measure it is, are we getting to our strategy better and faster? So you

[00:14:05] use your existing most important KPIs to measure the effect in those of AI. And it's a highly,

[00:14:12] highly relevant to the organization because it's strategic. And again, it's just really highlights

[00:14:18] the fact that most organizations are not strategic in the way that they operate and the way they think.

[00:14:25] And so in order to use AI strategically, you have to be a strategic focused company.

[00:14:30] I'm guessing you've got some companies that you've spoken to that are just, you know,

[00:14:35] maybe not firing on all cylinders but they're at least doing better than most and have

[00:14:41] some best practices that perhaps you could share. Yes, one of my favorites is the AIRP.

[00:14:49] So it's really focused on serving its members. It's a membership nonprofit organization. That's

[00:14:55] focused on people age 50 and above. And then especially people who are in retirement thinking about

[00:15:01] that advanced age, health, financials, everything. And so they started thinking about how can we use

[00:15:07] AI to be more effective in our communications to them? How can we instead of having a couple different

[00:15:15] types of newsletters because it's a huge range of interests from 50 years old and onwards.

[00:15:22] Some people are still working. Other people have various family different situations. So how can we

[00:15:28] granularly communicate to people their needs and put in front of them all of the services

[00:15:33] and support that AIRP offers? And so they're using AI. And in the beginning, it was a small group of

[00:15:41] just three people setting the strategy but it all tied back to again their purpose and their

[00:15:52] productivity gains and efficiency gains. They were focused internally but it was always with the

[00:15:57] goal of serving its members better. So having that focus right from the very beginning directed all

[00:16:05] the other round-swell efforts from people because they had an opportunity to view one of you say

[00:16:10] I, fill out this form and review it and get back to you within a few days. And they would approve

[00:16:17] these things constantly because people were very given very very clear instructions use AI for this

[00:16:23] purpose. Use it to help us engage in our customers better. Help us find ways to do things

[00:16:30] more efficiently so we can engage with our customers better. So everything was focused on that

[00:16:35] so it would be your goal that they had. Yeah, I guess I'm a little surprised that that's the organization

[00:16:42] that's you know, showing everyone how it's done but yeah that's a great example.

[00:16:47] I think a lot of what you just described is actually falls into this umbrella

[00:16:53] of responsible innovation right so it's you know I spent a lot of time in responsible AI which is really

[00:16:59] about you know the governance it's almost in some ways sort of this like defensive strategy but

[00:17:07] it doesn't have to be that way. You can be responsible adhere to you know legislation and

[00:17:15] guidelines and you know ethical expectations or whatever and still innovate like you can walk

[00:17:20] into gum at the same time people have been doing it for a long time. There's more to think about

[00:17:26] but there's also a ton of of opportunity and if you educate part of this sort of upskilling

[00:17:34] and educating people to advance their ability to work with AI and understand how to use AI

[00:17:40] properly you're undoubtedly going to get a lot of ideas and now you got to figure out which ones

[00:17:47] of these you know make sense which ones are relevant within a particular domain or particular role

[00:17:53] and which ones could be adopted more or broadly or even commercialized. You've got this

[00:17:59] dual benefit of not only mitigating risk within your war and organization by having people use

[00:18:06] the technology properly for your own operations but you're also going to ignite a lot of

[00:18:13] promising ideas and some of them might be far fetched and some of them might be sort of incremental

[00:18:18] innovation but this a lot of value in every direction by making your people more aware of what's

[00:18:27] possible and guiding you in a strategic direction that makes sense and maintains some competitive

[00:18:35] edge. Yeah I see a lot of companies so banning the use of AI in the organization

[00:18:42] and when I talk to people in those organizations they're all using it. This is not using

[00:18:47] an in-sansion way which is a problem because by just saying no to everything's presumably turning

[00:18:54] it off you're pushing it underground and you have no visibility. You're much better off making

[00:18:59] invisible making sure that people are using it in a responsible way which means giving them training

[00:19:05] giving them guidelines and more importantly using it in a strategic way to say use AI to do this

[00:19:11] don't use it to do that like you may want to go do that because it's interesting but it doesn't

[00:19:17] really help us focus and set on using it this way and here's the training here are the tools

[00:19:22] like focus on here and and I remember one organization that says said we're going to become AI ready

[00:19:30] we're going to become AI first this is an imperative for us as a fairly large organization about

[00:19:35] 600 people and the CEO came out and said we're going to give you all training here's a list of

[00:19:41] other true tools if you want new tools as a process and we try to streamline that and then we're

[00:19:46] going to have a dashboard with every single person's name on it and next to each name will have a

[00:19:51] light there'll be a green light if you're using these tools all the time there's a yellow light

[00:19:56] if you're using them still trying to figure it out but at least you're in the game and get a red

[00:20:01] light if you're not using these usually any of these tools and he threw it on the gauntlet at that point

[00:20:07] he said in six months time there would be no more red lights employed at this company

[00:20:13] and he would say look you have to learn how to use these tools it is a given to the future success

[00:20:19] of not only our company but for you as an employee anywhere you work and if you're not really

[00:20:25] to do this and advanced to become at least a yellow light then we're going to have another conversation

[00:20:30] that this may not be the right place for you right but no matter what there'll be no more red lights

[00:20:34] at this company in six months well I guess it would be after the six months and there's no more

[00:20:40] the light's probably won't be that many yellow lights either right because you don't want to

[00:20:45] get a move there go first and it's not you know what's going to want to fall behind and yeah below that

[00:20:50] line yeah well I mean the reality is there are some jobs where Jennifer I doesn't really help you that much

[00:20:56] and it may be already built into the tools and you just use it but it's not something that

[00:21:01] everybody will be using all the time necessary but at least you're familiar with it and when you

[00:21:10] in it you know how it works you're appreciate to know if something was created by AI what to do

[00:21:17] with it too as well so it's just becoming AI literate the way I like to think about it is

[00:21:23] if you have a new employee you wouldn't just necessarily trust everything that they put out you'd want

[00:21:28] to review it and AI is like that you don't want to just necessarily take it at face value you

[00:21:33] want to review it and at some point you begin to trust it even more and just going back to your

[00:21:39] whole point about responsible AI this is not about slowing things down AI regulations all these

[00:21:45] things that in governance is sort of a dirty word inside of our sensations it really is about

[00:21:52] speeding things up because if you have clear guidelines on what quality means what safety and

[00:21:59] security means what it means to build trust in this technology once you have that trust then

[00:22:07] can move much, much faster. If you're constantly doubting does everyone know how to use this is being

[00:22:13] are there any hallucinations in here do people have the critical thinking skills to use this in the

[00:22:19] right way then you're you're not trusting either the people or the technology but if you have a

[00:22:26] foundation of responsible and ethical use of AI then trust that's being built in the organization

[00:22:31] and you can move much, much faster. Absolutely organization needs to set the policy but I just feel

[00:22:37] like it's a matter of time before this is just part of your onboarding and annual or whatever

[00:22:44] frequency you know training that everyone should be going through just like they went through with

[00:22:49] harassment and data privacy and cyber security I mean what you're let's do take I mean doesn't

[00:22:55] just matter of time before the zatted to that list. Yes again I know that one organization HP

[00:23:01] does a regular training for all its people on safety security use of data especially if you have

[00:23:07] access to information and built into that is the use of AI into that training too as well so

[00:23:13] when you have a regular training cadence and education cadence for people then this becomes an easy

[00:23:19] way to build it in isn't just me on board but it's a regular part of just your access to

[00:23:25] in order to be certified to use things like customer data, employee data you have to be trained

[00:23:31] and reminded this is how you take care of things. So again the power of AI is very much based on

[00:23:38] what data you have access to but also what you do with it and so do you pass it off as

[00:23:44] you don't do we review it what are the safeguards that you have to put in place to make sure it's

[00:23:49] being used well and those are things again that can this some degree get created from the bottom

[00:23:55] up but it needs to have some sort of consistency and alignment across your organization and that

[00:24:01] can only happen from the top down. No absolutely great I know you've written about setting up like AI

[00:24:08] ethics committees and things like that which of course I'm a huge proponent of did you just unpack

[00:24:14] that that thought a little bit and just talk about like who should be on that committee and

[00:24:20] you know what their possibility should be I mean it's part of an AI center of excellence or

[00:24:25] is it just completely you know independent because I think people will be concerned about you know

[00:24:31] another yet another sort of gatekeeper to get something deployed or what have you.

[00:24:37] I tend to say away from an AI center of excellence because it says that there's a

[00:24:43] single way to do things we're way too early for that in some ways and so I separated and call it

[00:24:49] the minimal viable team that you need to put together your AI strategy and that's very

[00:24:55] difficult then when you're operating and executing but to pull together that strategy you want

[00:25:00] somebody clearly from the digital and technology side not necessarily IT because IT typically is

[00:25:07] keeping the lights on maintaining things not necessarily innovating with things so the most

[00:25:11] innovative technology thinkers in the organization you want somebody who is the most strategic

[00:25:16] person you can get to be on this team I do the CEO the head of strategy somebody who understands

[00:25:24] your strategic objectives you want somebody who can represent your customer and commercial interests

[00:25:30] so has a view for how customers needs and expectations are changing because of AI and what the

[00:25:36] impact of anything that you do you could include somebody from product so you can start

[00:25:40] understanding what's going to be required and very importantly you need somebody from HR

[00:25:46] because this is a people transformation you're talking about do you have the skills

[00:25:50] how are you going to be changing jobs how are career ladder is going to change now notice

[00:25:55] who is not on this team legal risk and the reason is because they play a very important role

[00:26:03] but unless they can be in the room and say in temper there need to say no to think

[00:26:10] if they're in the room and can say yeah we can do that and here are the things we're going to have

[00:26:16] to do and ensure to make sure it's safe if they can be a proactive partner then they can be in

[00:26:21] the room otherwise from the most part I encourage people to keep them off of that initial team

[00:26:27] and to keep them absolutely informed get them to write the responsible AI and ethical approaches because

[00:26:34] absolutely need to do that and as you come up with a strategy keep them involved bring them in

[00:26:42] to say well these are the safeguards we have want to have how do we include that and actually

[00:26:47] put that into execution so the concern is that you have to get legal and risk and security

[00:26:55] involved by from the very beginning and the reality is if you can demonstrate that you are approaching

[00:27:01] in a responsible and ethical way with some basic guidelines to say we are not going to execute

[00:27:07] anything but always going to come back and we'll keep these guidelines in mind as we go through this

[00:27:13] and we're constantly saying in touch with you but we need to think very openly very much

[00:27:19] in a brainstorming fashion without saying no to opportunities and that is your job is to say no

[00:27:25] to put these safeguards in and we don't need that in the room right now yeah now as a strategy

[00:27:30] comes together then you absolutely have to include them but in that initial group give yourself some

[00:27:37] breathing room and instead of constantly thinking about all the things that can go wrong think about

[00:27:43] how you can be curious how you can have imagination brought into the process to imagine a very

[00:27:47] very different future yeah I really like your kind of thought there this is different

[00:27:54] and what we need here are to your point people from different domains different lines of business

[00:28:01] and with the cognitive diversity to understand where there might be some implications to

[00:28:08] protected category of workers or whatever you need to do to make sure that you're thinking

[00:28:15] you know deeply and broadly about adverse impact and fairness and transparency and things of that

[00:28:23] nature so I think what I tell people and and what you describe I think are complementary

[00:28:29] one of the things that has come up is around the phrase responsible AI kind of entered my

[00:28:38] at least my vocabulary around the time that generative AI came in people have those two things sort of

[00:28:45] linked together but responsible AI is much bigger than any particular legislation that is just

[00:28:52] now coming out and it's not only generative AI, I responsibly I is how you're using any

[00:28:59] autonomous algorithmic or artificial intelligence system to help make decisions and

[00:29:08] draw conclusions right so are you seeing a similar observation or people are sort of

[00:29:14] conflating you know or inappropriately directly associating with responsibility I did generative AI

[00:29:20] yes and again it's it's completely understandable because it's the most visible, relatable,

[00:29:26] usable example of AI that we can actually use an access without being a technologist

[00:29:31] and so if you think about the true power of AI is when you have generative AI as a front end

[00:29:37] the end from the interaction point of view and then be able to access all this powerful traditional

[00:29:42] is what I call it AI like machine learning or natural language processing all those things

[00:29:49] become much more accessible and even more powerful with generative AI later than top of it so

[00:29:54] it's it's this melding of all these AI together we don't say responsible generative AI we say responsible

[00:30:00] AI because it's encompassing everything but the real focus right now is because it is so much

[00:30:06] accessible because it is now democratized it's a different level of responsibility and care that needs

[00:30:14] to be in place because anybody anybody with a mobile phone anybody with a browser can kill uses

[00:30:21] and it's sort of like I remember it's mine in me of the early days of social media

[00:30:25] anybody can set up a Facebook account anybody could go out there and start a blog

[00:30:30] and you can do a lot of damage if you're not careful I'm glad you brought that up because I know

[00:30:36] people have been sort of bouncing around what is the proper sort of analogy you know I guess

[00:30:43] innovations from a technology standpoint I mean is it is generative AI like you know the internet

[00:30:50] is it like social media I happen to think social media is a really powerful one that sounds

[00:30:56] like you do too just because I feel like the the guard rails that were set for social media use

[00:31:02] within organizations and the fact that some of them did the same thing with the of them

[00:31:07] doing with AI which is you know you're not nobody's going on Facebook or whatever your

[00:31:13] work right they just didn't even see the beat of he now use case for it back in the early days so

[00:31:20] I think social media is the more appropriate analogy yeah agreed agreed again people are

[00:31:27] asking me how do you tell that this is a technology trend that's going to be a big deal

[00:31:31] and I go well I can tell you that things like blockchain or augmented reality or web three

[00:31:39] were not going to be that big because they didn't have this component of transformation with them

[00:31:43] they're going to be very important underlying technologies but they don't fundamentally change

[00:31:48] the power dynamics and the relationships before each other in the technology that it happened

[00:31:55] with the internet absolutely power structures were completely obligated same thing with social

[00:32:01] to somebody agree with mobile and then especially with AI the fact that we have this incredibly

[00:32:07] powerful tool now at our fingertips anybody can use it anybody can write programs now I can write

[00:32:16] apps and programs for the first time in my life it's an incredible powerful sense of capability

[00:32:23] and being able to have agency that just didn't exist before we can now set up companies and

[00:32:30] launch new products and services so much faster than we could before and the people who are benefiting

[00:32:37] from those are the ones who are agile enough to your point before agile agility being able to work

[00:32:43] in a very different way is probably the most important character risk that comes success for AI

[00:32:49] if organizations already gone through digital transformation and I mean not just digitized

[00:32:54] their transactions but actually work in a transformed way they're in a much better position

[00:32:59] to be able to take advantage of this new gender AI technology yeah absolutely um I also think

[00:33:05] the company is when it comes to data and you talked about hallucinations before and being able to trust

[00:33:10] these systems I think that organizations that are more mature from a data and analytics

[00:33:16] perspective are also in a much better position especially as you build proprietary

[00:33:21] you know models or you know you bring something in now so you build with it or it's just

[00:33:27] getting additional you know training with your you know proprietary data you're just going to

[00:33:32] be in a much better position if you have better data quality and data governance and things like that

[00:33:37] and it's not only data quality and data governance it's also do you have data literacy

[00:33:43] because data used to be the main of an interesting team of pointy headed

[00:33:49] analytics people right and if you wanted to get some analysis you were going knocking

[00:33:54] very quietly on the door I can be bothered you can be bothered you to like there's

[00:33:58] piece of report for us and now with these tools you have a potential giving anybody access

[00:34:05] to these tools to be able to run the data but but with that it comes great responsibility also

[00:34:10] so who has access to what data to do what with it and make what decisions and if you already

[00:34:17] have a culture of responsible use of data and access a data and training on how to do that

[00:34:22] it's a lot easier than if you people have never been able to access data before

[00:34:28] and don't know what to do with it it's incredibly powerful could be incredibly dangerous

[00:34:33] but again not having a PhD in data analytics in data science is it's not a requirement anymore

[00:34:42] to be able to draw insights and said the biggest requirement is that you have an interesting

[00:34:46] question that data could potentially answer so can we train people on how to ask these interesting

[00:34:53] questions that will make a difference in them making better decisions on behalf of the

[00:35:03] because I think the other thing about like when I think about the learning curve the journey of

[00:35:08] AI and like you said this is the first time people have actually been able to interact with it

[00:35:12] that like you know the UI is the AI right but it's also the user manual and you know the

[00:35:17] help section the community for a mall rolled into one right so so you're running out of excuses

[00:35:23] to start to get in there and get your hands dirty because if you're if you're stuck you can

[00:35:29] immediately get on stock right without leaving your keyboard in the screen as is in there's

[00:35:36] some point it's not to be able to ask right questions exactly so I was just curious just you know

[00:35:42] this could be you know for personal use or in your work are there any particular you know tools

[00:35:49] or use cases besides the usual you know chat GPT and or whatever that you're finding particularly

[00:35:56] useful or interesting yes I like using the my GPT features within chat GPT also cloud has

[00:36:04] something similar called projects and the ideas that you can customize and and we oftentimes use

[00:36:11] this idea prompt engineering to make the results better so there's all sorts of tutorials on how to

[00:36:18] get that get the most out of your LLM hours of models but if you find that you're doing a certain

[00:36:24] amount of tasks over and over again so for example I'm constantly writing content and I want the AI

[00:36:31] to understand my writing style my past writing content so I upload all of my content I upload of my

[00:36:38] last book I give it all of the articles I've written every newsletter I've written over the past

[00:36:43] four years it's all in there and as a result it understands a full picture of me and the instructions

[00:36:51] I give at are very specific to what I'm looking for so I have a couple different versions of this to

[00:36:56] do different things and it's a nice way to customize the LLM but use its base trained model it's

[00:37:05] very powerful model to do things very specifically to you so sometimes I'll go in with an executive

[00:37:10] team and we'll create models custom models for each member of that team with their writings with

[00:37:17] teachers plans the way that they talk and present again using publicly available information nothing

[00:37:24] proprietary and then becomes instantly usable for them because of rights in their voice it thinks like

[00:37:30] them it understands all its prior thinking so it can be that great thought partner and so I think

[00:37:37] it's one of the most powerful things you can do with this don't don't settle for the same GPT that

[00:37:42] everyone else is using make your own yeah now let's try to test the advice I know I've tried to do

[00:37:49] in customization even just for my August episode some rays I certainly don't want to repeat

[00:37:55] titles or you know some rays and things like that even if we've touched on some of the topics

[00:38:00] with different guests I mean there's always a different perspective and a different angle to take

[00:38:06] but yeah I can imagine for someone who such an habit you know blogger and writer that that would

[00:38:12] be extremely helpful to have that sort of writing copilot with you but even that's an executive

[00:38:18] I think for you again assuming that you have a version that is not being used to train the model

[00:38:25] you have all those safety and privacy controls set up correctly then you might feel very comfortable

[00:38:30] uploading your strategic plan a competitive analysis your marketing plan your latest presentation

[00:38:36] to the team various correspondences or brand stories and guidelines so that you have

[00:38:43] the phone knowledge of everything you would want somebody to know to help you be a better leader

[00:38:49] so it's almost like having this this sort of personal board of directors to help you do your job better

[00:38:55] and it's sitting right there and you can call on it to do anything from writing to researching to

[00:39:01] sounding off on various ideas you may have in full context of what you are trying to accomplish as a

[00:39:08] leader so I think the value here is for any leader who is constantly thinking strategically

[00:39:15] and it's not just to create content it's to help you think in new and better in different ways

[00:39:21] not totally great awesome so Charlene I know you have a couple exciting things coming up you've

[00:39:29] a keynote coming up for HR tech and then of course as you mentioned your seven book which we

[00:39:35] are eagerly anticipating but inside info are you going to share it for either of those stuff

[00:39:42] I'm almost afraid to say because I'm going to jinx myself I'm trying to create a digital avatar

[00:39:48] digital twin of myself in that will help me present at HR tech and if all goes well I will connect

[00:39:55] hopefully to my private database my private chatbot and it'll also be able to answer questions

[00:40:03] in real time on its own so just having that kind of technology and showcasing it right

[00:40:10] it applies where you can now really create training for example inside an organization

[00:40:15] that's highly customized to each person we've all gone through just really long tedious training

[00:40:22] inside of our organizations and there's no reason why learning can't be more compelling

[00:40:27] the more engaging so if you could create customized training with a live instructor or even

[00:40:34] within a digital instructor and have it even tell jokes and add humor which is very very

[00:40:40] difficult for AI to do it would be a really interesting engagement and provide scale in ways that

[00:40:47] would be possible and the new book is much more workman like it's step-by-step taking you through

[00:40:54] what do you do for a second third fourth to have a compelling strategy for january i

[00:41:00] and we'll focus specifically on january i just too because it's a newer thing that's out there

[00:41:05] it's a layer that sits on top of any a-sucing a-i it's the one that has most transformational

[00:41:11] power inside of your organization because anybody can use it so requires a strategic approach to

[00:41:17] and we start with everything from just literacy and creating a foundation with responsible AI

[00:41:23] to auditing your strategy to nuts and bolts of how to set up your data and technology so

[00:41:28] that it can scale so nuts and bolts everything you need to know from beginning to end to at least

[00:41:33] get you started on on the path to having a coherent strategy yeah i think a lot of people are

[00:41:40] struggling to figure out they're already overwhelmed and they don't know where to begin

[00:41:44] and so it sounds like a really important you know practical guide that people get a lot of

[00:41:50] value from so congratulations on that and looking forward to reading it and definitely looking

[00:41:56] forward seeing your day chartek i did just book my trip so we'll be there in person then thanks

[00:42:03] did surely in any any other final thoughts about elevating your your AIQ i think we covered

[00:42:09] that pretty well on this conversation we covered a lot of stuff to your day i think the only advice

[00:42:16] I give to people is that the biggest impediment to using AI and specifically journey of AI

[00:42:23] is a lack of imagination so get really curious with it try a lot of different things with it

[00:42:30] and it is constantly changing and if you don't see the technology working in the way you want

[00:42:37] go and advocate and say i really wanted to do this and most likely i there somebody will show you

[00:42:43] how to do it that way or vendors will like oh i'm gonna start paying attention to this and

[00:42:48] actually deliver that way i think the smartest thing that organizations to do is to build to buy

[00:42:54] meaning they're gonna start building some of these custom tools with the intention of being able

[00:42:59] to buy it from a vendor in the future but because they know they're gonna buy and not build the

[00:43:03] ones from scratch it's being a more thoughtful, thorough buyer more knowledgeable buyer simply

[00:43:11] because you're starting to use these tools and build them too as well so i think it's fantastic

[00:43:16] advice i mean i think once the buyers are smarter about what they want they'll make sure that

[00:43:21] those you know the vendors you know build things that solve real problems and not just

[00:43:26] but chini objects out there to distract us all so that's the great closing thought

[00:43:31] Charlie thank you so much for checking time to educate me and my listeners

[00:43:37] really really appreciate it and look forward to seeing you at a guitar track.

[00:43:42] Thank you so. Thanks again Charlie thanks everyone for listening we'll see you next time