Alright. Good morning. Evening afternoon, whatever time it is wherever you are, I’m Malcolm Hawker, host of the CDO Matters podcast, And I am joined today by Wendy Turner-Williams. This is actually our second attempt at doing this.

We we tried to record a podcast a week ago I live here in Central Florida and we had one of these just amazing summertime afternoon Florida thunderstorms where it was blowing, and it wasn’t a hurricane. Although, you know, there was no hurricanes at that time. It wasn’t even a hurricane. It was just a really, really strong storm, took up our, took out internet, took out everything, And so our our conversation was cut sadly short. So this is our take two. So I am doubly indebted to you when taking the time to do this.

I just got extra Malcolm time. I’m happy with it.

Go ahead. Wow. Wow. Wow. Okay. Flattery will get you anywhere. Keep going.

Wendy, I’ll let you introduce yourself. We we’ve we’ve been we’ve been kind of swimming in the same pool for a long time now, although we’ve never really kind of I don’t think we’ve ever on one, but I’m pretty sure we’ve probably been at the same conferences. We know a lot of the same people. We live in the data world. So it’s a pretty small community.

But but when you I’ll I’ll I’ll pass it back to you in in in a nutshell, this could describe your your your experiences and and what brought you to where you are.

Of course. Well, well, thank you. I, you know, I I I appreciate the ability to to be on the show a second time. Yeah.

And to to meet with you and for those that don’t know me, you know, my background is basically, you know, twenty plus years in clouds and services. You know, I’ve been companies, like some of the original big tech telecom companies that are now Lumen or, you know, Sprint, etcetera, their their predecessors.

And then the last sixteen years or so, I’ve been very, very focused on kind of the the the the big data world and the crux of data plus software plus infrastructure and journey to the clouds for others. So that’s my deep expertise. As a part of that, I have done things like lead enterprise data strategy, architecture, and governance at Microsoft.

I did the same thing at Salesforce, including a lot of their data platform strategies.

And then finally, my my last official role, which we’ll get into here in a a little bit as to why it’s the official role. Was actually as the first chief data and AI officer for Tableau. So but at many of the big companies you are using on a day to day basis, to run your business or to perform your, you know, data and to drive value, all up. So were you at Tableau At the time of the acquisition for us by Salesforce?

Yeah. No. So I was at Salesforce at the time of the Okay. Exactly. Exactly. So, basically, I was running enterprise, data strategy and platforms and governance and, you know, strategy for for Salesforce. And then when the Tableau acquisition landed, I was approached by Mark Nelson to say, Hey, we we’ve never had a CTO and we need help integrating great as an M and A into Salesforce.

Our customers want to hear from a customer zero. They wanna hear from the thems of the world. I am them of the world. And would you come over? And I said, absolutely.

So I so I hopped over and, rest his history.

So I’ve got a long history with Salesforce. I managed a twelve hundred seat implementation of Salesforce once. I think I’ve had four, maybe three executive briefings at at the kind of the old headquarters, at the end of market street, but before the giant thing was built down.

Yeah.

And I took what I took away from my experiences at Salesforce is it it was an incredibly well run company.

Yeah. With a with a with a great culture. What what were some of your key highlights from working with that company? I, you know, I think that the biggest thing that I walked away from Salesforce was, the transparency they had in their v two mom process.

And I I’m sure you as engaging with Salesforce, you probably heard a lot of about this, you know, especially if you think about us in the data field, we are always trying to understand business strategy. Right? What’s the business strategy? What’s the business strategy so I can be proactive to provide either the datasets, the pipelines, or the infrastructure support the business strategy.

Well, what was beautiful about the Salesforce culture was the fact that they have this b two mom process which basically is a top to bottom down publication of biz of all the business strategies across the entire company. So what what is the Salesforce at the top level, Mark’s level, what is he focused on, what are the goals, what are the objectives, and even what’s the what’s the measures k that they’re trying to hit, then goes to his directs, which then goes to their directs, which then go so you get this kind of roll up of what every single person is working on in the company, you get a lineup of the people to that impact area know you’re bringing value.

And more importantly, for someone like us in the data field, this became a really easy way for me to start to quantify where we’re actually providing data value, whether it was to grow the market or it was around trust or it was around, you know, new customer journey experiences or whatever it was, I could then kind of align really easily into those business strategies. Because either it supported it or it didn’t. And if it didn’t directly support it, you’ve you’ve you’ve got a defensible position to say, hey, listen, sorry. This really doesn’t kinda fit into.

That’s right. That’s right. I mean, there’s always gonna be, like, think about it this way. There’s always, like, engineering for engineering, right, where we discover but but you could easily start to to identify exactly where those pockets were and why they were needed in order to support something like hey, search needs to do, you know, a real time, you know, search capability, which means I need to change certain types of pipes or infrastructure and either to support that. Where I need x y z inside, you know, acquisitions of data in order to get them what they need. So it became a way to base align end to end and to remove fat where you shouldn’t be focused.

Love it. It’s it’s interesting. I’ve I’ve got so many just like fun Salesforce stories, but one of them to me is that is that, you know, like, we all have these kind of these yardsticks that we use to measure time if you’re lives. Right? Like, for me, maybe it’s it’s music or for some people who’s music or or or it’s or it’s this or where were you where were you when x happened or why happened? For me, one of them is Dreamforce.

Yeah. And and and and what band was playing at Dreamforce?

Was that Metallica, or was that Bruno Long?

Right? Like, I’m just, like, yeah. I’ve been watching this week because memory Dreamforce is happening this week. So my my is it this week?

It’s been this week. And so my LinkedIn, because, again, I’ve been at the company, and I have so many contacts Like, it’s full of, you know, concert measures and everything else. I think a lot of people measure it that way. They they put on great events.

Right? I mean, I think the biggest thing about, about Salesforce that I learned outside I mean, I really took away that v two loan process as a way to me be more effective and how to guide almost like cultures and companies to align infrastructure and your strategies, in a in a business strategies in a better way. Right? Even if they didn’t understand that’s what they were actually doing, They were about transparency down to the bottom, but for us, it actually was a a a a big eye opener for me compared to other companies as to how to approach.

Right? But the other thing about this is that, when the other biggest takeaways, I I learned that my, at Salesforce was they they were a they started as a marketing company. Yep. Fair enough.

They’re they’re a marketing company. Right? Versus necessarily, like, a micro saw for a Google or, you know, an AWS who really focuses more firstly on the the technology. They’re an engineering company.

You know what I mean? So for me, that was also a lesson that not all big tech companies are all big cloud companies are the same as far as how they actually, you know, interoperate or how they focus their engagement with their customers. Salesforce is a very showy party throwing company.

But it but it worked. Right? Like, I would I would argue the explosion of SAS is in many ways, not in obviously, you can’t attribute it just to Salesforce, but a huge part of was Salesforce Because in at that time, like, I I implemented Salesforce at at America online in nineteen ninety seven. Yep.

Like, American AOL was one of the early customers in Salesforce before it became a thing. And the engine, the, like, the technology was seen as far inferior. Right? It was seen as inferior and it was seen as risky because at the time it was like, oh my god.

I’m not putting my data in the cloud. Alright. Right. But it was but it was the marketing, right, which was That’s what’s up.

Sell to you, like, chief marketing officer. You don’t even don’t don’t tell IT. Right? We can report on your credit literally put it on your credit card and monthly bill and expense back the cost for this thing, you know, chief chief revenue officer that your sales people might actually like to use and that’s how it was the ultimate land and expand.

That’s how it took off. Back to that marketing thing, what they did is they didn’t angle to the engineers or the techies of the world. Right? What they did is they marketed and they simplified into into layman’s term or, I mean, think like generative AI today, right, and and why generative AI is as has has has been so, like, oh my god.

Is because you don’t have to be a machine learning or a data scientist or a hard core engineer in order to to use it it it can speak to someone who doesn’t necessarily know the ins and outs or as an expert in the field, right, and it’s speaking to you in a way in your language that it can bring you some value for you to then move forward. And so they’ve became almost like the generative AI of marketing around SaaS early on in regards to how they approached the selling and who they approached to selling. Right. You know, going to the business teams over the engineering teams.

Well, that’s exactly right. Getting back to, like, even their like, they’re local with the, you know, like, you know, the the line through it, like, set, like, not forget about the technology. Love it. But, hey, the AI bit is a great dovetail into the things you’re working on now.

So, fond fond memories of Salesforce and being the CEO of of Tableau. Yes. I I I talked to people still all the time. I, you know, I said Dream Dreamforce this year has been like, I know that person.

And, oh, I haven’t talked to them. I need to remember. And I’m not there, you know? Well, it’s to the point now where it, like, it just got so big and just kinda completely taking over downtown and, you know, like, it just it just got so huge.

But anyway, big pro good good problem now. So anyway, AI and the dovetail and the things you’re working on now. So let’s talk about this association that you’re founding. Yeah.

So I am so excited about this. And I I thank you. Thank you for, you know, giving me the opportunity to talk about this because I think your audience especially is totally gonna get. It should be totally excluded.

I am. I I asked someone who has been focused in infrastructure and software and clouds and been building AI services and machine learning for forever.

We’re at this crux, right, now that generative AI has really hit the market. And now that, again, the non us’s of the world understand the power and can use it. And so what we’re doing with the association is we’re doing something really, really different, and I think there’s just an incredible need for this. We’re trying to create, a more focus on bridging the disciplines of AI ethics.

Data, privacy, robotics, and security.

And we’re trying to create basically, like, a a powerful global big business organization of the practitioners in these fields, not just the executives. K? But Anyone working in these fields regardless of level or even students coming out of colleges and focusing on STEM who are gonna be working in these fields to basically create practitioner voice. And let me explain what I mean by that. Number one, we are the ones who hold the key to ethical and quality AI because if you think about those disciplines, It’s the people working in the ground on the ground and and managing these disciplines and doing the jobs of these disciplines who are putting in the data models and building the pipelines and managing the stores and or legs. Right?

Or managing, the the trust and the controls, do the governance.

We’re also the ones that are basically responsible for the data life cycle and operations.

So just like with GDPR or CCPA, you cannot have ethical AI without those disciplines working together.

And I think what if there’s lessons to be learned and and I’m I’m gonna share my personal lessons. Right? I was at Microsoft when GDPR was first initiated.

We had a whole working group and V team of legal attorneys, product managers, executives, the data management folks, etcetera, who are working together on approaches because we realize something like, you know, a privacy policy that is flashed on your page, etcetera. It’s just that. It’s a piece of paper. Right?

Until you can implement that into each one of your products and then into how the data associated to those products is actually stored and managed. And then, especially in the tech companies, then how the data from our products moves into our internal systems and and store to to manage our business, you can’t truly do something like right to be forgotten. K? It’s not just a product top.

It’s also your internal EVW or your snowflake system or your, you know, or or whatever those things are. It’s an end to end process. And it requires all those fields working together. But what happened with GDPR at a lot of companies was This is the rise of the chief privacy officer role.

Right? They get so focused on just the privacy privacy or they get so focused on the the lobbying aspect of the role around privacy up to the up to the the the the regulatory firms that and they don’t understand how they need to actually implement, like, tactically implement. They also don’t understand how to translate that policy and to those technical requirements or engineers or data leaders, etcetera, or software engineers or dataagers. Either way, to implement, and there becomes a gap.

Right? There becomes a gap. So we can’t do that with AI. K. Ai, when when we don’t have humans anymore that are controlling the the the the the output that are reviewing and controlling and kind of auditing the output of what’s coming from these stores.

This is where you get things like Samsung were, releasing their trust secrets, right, or this is where you get, hey, people are going to want to have options around if they want things like an AI diagnostic for a medical, you know, for for a medical purpose. Do they they have a option there? Can I say I want my doctor? Or can I say that AI can do it?

Right? People are going to get to a point like privacy where it’s not just right to be forgotten, right, where they wanna know who is using their data, and if it’s human or machine, and they will want to know how that interaction comes back to them. And that is all gonna require us. And there’s no foreign project even.

There’s no foreign version of it. So the association, if you think about it, is about you. K? I wanna help you do your job more effectively when I help you help your company, right, to have trusted ethical AI and I wanna arm you as the practitioner with the network, with the day to day interactive community.

With a marketplace of education services. So you can find all the education that’s out there that’s free. That’s not free. You name it.

You wanna taste something. You gotta one stop shop, whether it’s LinkedIn or Coursera or Microsoft or You can find it all here, k, because it’s geared towards you, where you can find the jobs, k, because not everything is posted on LinkedIn. And when we create a community of hundreds of thousands of us working in these explicit disciplines, You can find those next opportunities a lot easier because these are who you work with and will work with. Okay?

We’re also gonna do things like a vendor and third party marketplace. So think how many of us are spending so much time even on AI, even now going what do I implement? What technology do I choose? What do I mean now to govern AI?

Right? What do I need to do in regards to just internal GPU chat, generative AI services. There’s a million of them now. It’s not just a GP chat.

What do I choose? How does this fit into the rest of my data architecture or my my, in my enterprise architecture.

We’re gonna produce a marketplace where everything’s available for you to find in one store and you can actually get feedback from your peers around the value or not value associated to those things. So we’ll save you time. But more importantly, I know. I’m going on and on. I’m so excited. You could tell. More importantly, here’s the biggest crux.

When we created this community, and we give voice to us that are in the fields. K?

Back to what’s happening on the hill. Right? Just yesterday. All over the hill, lots of big guys coming, setting a table, talking about how do we break the prices?

Yep. I know. I know. That was the head that was the headline I read today.

It’s like they vol they they they volunteer to do the right thing. Great. We volunteer to commit to do the right thing. Here here’s where we come in, the association.

We are the ones who hold the keys to actually doing the right thing because we are the ones who actually do the jobs associated to that thing. Okay? And so we’re gonna produce and create the first cross discipline global ethics and policy committee to drive the policy and standards that we agree to align to into the tech companies and into the regulatory bodies. K? Again, we’re the ones on the on the ground. We’re the ones doing the implementation We also know where we can do it and where we can’t, and we should have a voice in that. So that’s the whole point of the association, it’s a nonprofit to help you do your job and more impactful, have more career opportunities have more of a voice in what’s coming in the future.

I I love it. Says the guy who’s I love it. Says the guy whose mission it is to prolong CD O tenures. That’s why I’m doing what I’m doing. So it seems like you and I should keep talking and continue this offline and figure out ways to get to get me engaged and others engaged because I can I can tell you that there is an absolutely there’s a huge need here? And the evidence for that need, the the evidence for that need is all over the place.

I saw this when I was at Gartner. So I was I was Gartner analyst for three years. And I love Gartner, and it is an amazing company with amazing people, but it tends to be pretty academic.

Totally. It’s pretty high level. If you wanna roll up your sleeves and put a shovel in the ground, Gartner is not the place for you. It’s it’s it’s not gonna help it’s not gonna help a strategic thinker be more operational.

That’s right. That’s right. It’s just it’s just not. That’s right. There are I’m I’m active on LinkedIn, and it is super surprisingly good community.

Yeah. But it tends to be a little more operator centric and even then how in the world are you gonna get the guidance that you need out of, you know, it’s not like and a hundred and forty characters, but you get my point. Right. It’s like these little tiny little little sound bites and maybe there’s white papers, maybe there’s blogs, and it’s and it’s good, but there’s certainly more that that that can be done there. And then there’s industry conferences.

And and and what I see again is that certainly, it’s either you gotta kinda pick your swim lane in the data world. Right? Either you pick the strategy swim lane and you attend something like the CDO IQ that I just did in Boston, which is a fan fantastic conference. Don’t get me wrong.

Amazing conference for Right. If fantastic stuff that doctor Wennings is doing there. Tends to be a little more on the strategy side, the big thinker side, and that’s good. But then there’s another set of conferences for more of the operators.

Of the kind of the people who are actually doing the stuff. Right? And that tends to kind of align to the enterprise data worlds and the diversities of the world and IRM over in the UK. And he’s, again, fantastic stuff.

Great conferences, but we need to find a way to bring all this stuff together. In the middle. Right? So back to the bridge.

Right? Like, I don’t I’m like you. I go to first of all, these conferences. Right?

It’s always executives that go. You know, you can’t word three thousand dollars or five thousand dollar entry to send your entire data to this. Right? So the a, there’s a vacuum between those who are working in the strategic areas and those who are on the ground.

Right? Do you even understand what’s coming? Right? Also, the people on the that, on the strategic side, option are not operators.

Do you know what I mean? Right. So Abel don’t know how to translate what they heard or learned or whatever into that. The other thing about those conferences or these forums and events they they’re dog and pony shows.

Right? They don’t tell you the reality of what it takes to implement And as you and I know, as we both have kind of served in evangelist types of roles or chief strategy types of roles towards customers, When I sit down with CDOs and CIOs around the world in my role at Tableau, we don’t talk the tech.

We talk how do we get dedicated funding envelopes from the board because we have so much to do in our our our, our our areas are so large and so complex that we can’t hire or we can’t get the technology we need to actually be able to deliver against what we need to do. Nonetheless, still with ten, eight, twelve, whatever business units that all have competing priorities that we have to feed because we’re a shared service that’s in a servant role, right, back to these things in order to do that. Or we’re talking about the politics of data. It’s political as hell.

Or you know what I mean? Again, back to the CDOs, right? CEOs are not happy. And CTOs have this the shortest tenure in of all the C suite for a reason.

A, they’re not happy, b, the companies treat data like a cost center. Often, these videos aren’t even sitting at the table at the business strategy, and that should be, in my opinion, to first person you set at this at the table? Because how do you actually define a strategy if you can’t measure a strategy?

I mean, if you can’t measure to debt manage it. Yeah. Yeah. How do you do any of that?

Right? But but beyond that, you know, you’ve got just accountability issues around data. K? Where we’re in a servant role, but yet we have no authority to actually drive from an influence perspective, which is that need to happen, that actually enable things like r p you know, RPA or AI to actually work because you need a a level of quality in your data in a level of consistency of your data to be able to do any of that.

Okay? And we’re not at the table. K?

So it’s it’s it’s just there’s a vacuum and there’s a need And I think data people feel like we’ve been put in the corner whether it is the executives or the ICs because the executives can’t help you get that promotion or whatever because that goes to the business team. So I actually got that business strategy to land, even though we did all the data work enable them to actually be able to operate that. Right? Or, you know, so we I this needs to change.

And I wanna change it. And I need every CTO out there. I’m working this almost like a franchise. This isn’t about me.

This has nothing to do about me. I can go walk into another job making figures at any point in time. Right?

I don’t want to do that anymore. I I want to help our field in our discipline.

I want to help what’s coming with these transformations to land in a good way, in an ethical way and I want to help as many companies as possible to transform as quickly as possible and to support the people doing the work in these fields as best we can. And that requires all of us working together.

Couldn’t agree more. Love it. Love it. More po more fanfare more this is this is, you know, this is where the fires go off. Couldn’t agree more. There’s huge demand here, and I think there’s so much to be offered by creating a community of data leaders where there is frank and honest and candid exchange, about some of these issues.

Yeah. What I’ve seen in the last And tactical is high. Is that true? That too.

Yes. Yes. And tact and tactical when it’s needed. Right? Like some some in our in our community are extremely tactical who can can can write r and Python and no sequel statements and know all that stuff They those folks from a tactical perspective, they got it.

Right? Check. But having the conversation with the CFO about business value or about breaking the mode away from being a cost center to your point and and becoming a profit loss, becoming a real P and L, Like, if if if your if your background is is, you know, r in Python, you’re probably not gonna wanna have that conversation or you feel like you don’t have the tools. To have it.

Right? But you can be. I trust me on this because you can be taught. Everybody can learn it.

Everybody can do this. This is the process. I learned how to as print is a burning. Yes.

I didn’t know anything about engineering, and I, and I successfully led an engineering team, and I didn’t know anything about it. All I needed was a shot and I, and I just needed to learn some stuff and and to be extremely incredibly unbilled in people humble.

But I’m we we can do these things. And this is why I’m kind of excited about association because I I I think a lot of this has to do with learning. A lot of this has to do with information sharing. A lot of this has to do with community and supporting others who are similar roles When I was in Boston a few months ago, I was struck by how many new CDOs there are.

I mentioned this on a previous version of the podcast. When I was talking with, Joe Rees recently. There are federal government agencies that are like mandating the role. Yeah.

No. It’s absolutely actually, I had several of them. I was an executive sponsor for at Tableau. So I know.

I’m like, I’m happy to see it. I love it. Well, and but and and this is there’s a good news bad news situation here. In the in the it’s good news because you’re you’re you’re, you know, increasing the notoriety and visibility of the role.

I think the last survey done by by Randy Bean said that, like, eighty percent of companies had the CDO role now in some way, shape, or form, which is fantastic. These are all good things. We want more CDOs Yep. But what we’re seeing is a lot of instead of late career, right, who, like, people with me, like, Right.

Right. They’re more mid career, and I love I love the vitality. I love the energy, and I love I love all of that. But when it comes to you know, some some of the bruises that that you and I gained kind of naturally over the years, a lot of these folks don’t have.

I know where you were going. We need to admit I mean, it’s it’s it’s it’s it’s, you know, how how do we help those folks succeed? How do we help them you know, learn, what works, what doesn’t work. I mean, there there are such things as best practices.

Yes. These are novel times that require unique and innovative solutions. Don’t get me wrong. I’m I’m all about breaking away from same old same old.

Trust me on that. But, yeah, that’s why I love, like, I love I love the idea that I think there’s there’s a massive demand for it and we can certainly be helping each other. Right. There there’s the thing about best practices, right, is that best practices require you to a document, right, but also require you to have situations or, you know, that that are standardized at that or that are that are happening over and over that you can create the document against.

Right? The reality is that technology is so complex between soft skills about how do you influence, right, how do you influence change? Or how do you influence the business, or how do you get to that board, or how do you how do you actually start to influence, like, RPA or AI or even infrastructure strategies, right, based on where we have data gaps or where we can actually automate the data to improve operations to move on to that next business layer that we need to kind of focus on to define the processes that need to be, standardized. Do you do you know what I mean?

Yep. Those are things that we can’t necessarily document because it’s it’s so much experience and knowledge share. And so back to, like, the association, right, there’s so many angles between helping the next generation of leaders to helping the tactical implementers to let’s let’s get out of the data world.

I spent part of my, like, three years of my time at Salesforce. I reported to the CSO. K? I was one of these data leaders.

I’ve been in this space for forever. So you can almost call me a first gen leader, but I’ve always been in cloud, and I’ve always been in software. Okay? And in Intel Salesforce, I was never focused on defense.

I was always focused on business value and office always. Okay? And so when I came to sell scores, because they’re a trust, their number one value is trust. And because they Yep.

And because they had never had an enterprise wide data strategy or governance group or both their first policies They’ve never had that. And so they didn’t know where to put something like me. Okay? Or my organization.

So they put us with security. And if you think about that, it was it was weird.

Because we’re opposite side Not on Coleman, not on comment, weird, but not uncommon.

We’re opposite sides. We’re two sides of a coin. I wanna help people get as much information as they need to do their jobs, and they’re very risk focus and put data in the closet until all the controls are in. But, like, here, here’s why it matters with the association.

I learned a lot of things there, okay, that that helped me be more effective as a data leader and more importantly help me be more influential to a board or to the the the discipline partners that we work with, the the audit or the GRCs or the risk groups or whatever, because here’s the reality, cyber teams and security teams cannot do their jobs without us. They have their own infrastructure sure they have their own priorities, but here’s the difference. Okay?

If you’re doing something like patch, patching, you know, monitoring. Right? People should have all their patches deployed within x amount of time so we can ensure availability is elibility and trust. Right?

Well, to do that, number one, they have to know where those applications are, where that hardware is. But more importantly, what they need is they need to understand the data layers running across those those applications so they actually can understand where that risk is in regards to that threat, okay, or that breach. Okay? So understanding that is something that helps the C cert teams, it helps the threat detection teams, it helps all of them be more focused on where do we actually have risk and where do we need to apply?

Most companies, as we probably all know, or in my experience, a big tech, is hard to get the teams who actually own those applications to patch in time based on what you’re defining as a standard SLA. K? So that’s why there’s reports out that come out. But this allows you to understand which one of those actually matter.

Okay? Or again, if we had some type of breach, say we have a breach at a company.

Well, once we know where that breach is, If you understand the data lineage of how that data flows across other downstream systems and it does, out of software products. It doesn’t just stay in the product. The businesses who operate that software consume parts of that data in order to debug or, you know, hinder your incidents or to understand your journey in the future use and what they need to do, So there’s parts that flow down. We have to understand what potential breaches happened as a part of that, right, or what other data they made of how to access to in order to do proper Cesar.

K? And and get back to customers about the potential risk of where that flow. Okay? So there’s a there’s so many cross dependencies between these fields.

It’s it’s ridiculous in what tends to happen in the companies And, again, I only until, Salesforce did I ever really know this. It’s not like I haven’t worked with security teams when I was at Microsoft, etcetera, but Pending it so focused on each one of our priorities and the delivery of our priorities, we don’t have those types of conversations.

K? So back at like Salesforce, for example, you have at big tech companies it’s very complicated when it comes to infrastructure. Okay? At software companies, IT does not own end to end infrastructure.

Your product organization is actually building your products and storing the data for your products, usually operate on a completely different infrastructure stack than your groups who are more focused on to run the business teams, right, just the the traditional business, you know, finance sales, marketing, etcetera. And then there’s this layer that happens in between where some of that data goes back and forth. So we didn’t even have consistently asset list to actually really know if the if the patchy had an appropriate list of even who shows up on it. Then the list of the data underneath it. So even designing a system that actually gave them that end to end mapping ended up coming to my organization to help security because it’s all master data management.

And it’s all like in queries for them to be effective.

Everything I’m hearing. I I’m I’m I’m, like, I’m going back to my days as an IT leader.

When I was having conversations about, okay, wait a minute. What wait a minute here. What do you mean you can’t link data out of service now into sales force. Right?

Like, you can’t you can’t understand, like, this was for a sauce, a SaaS software company who where they could not understand the connection between the literal infrastructure that is that is hosting the SaaS platforms and and the customers that are riding on that SaaS platform, hard wall sitting in between the two. Thing was true with network security. You brought this up. I was like, okay, wait a minute.

What do you mean you don’t actually use customer demand patterns? You don’t any use any data on the on the sales side of task or even like sales to to to to help you predict when there’s gonna be an intrusion event on the network side. What do you mean you don’t even use that data? That’s right.

Finding a way to break all of these walls. I I’ve signed signed me up because there is so much goodness there, and this is where AI comes in, I think.

So this is why so back to you again, the point I’m like, I wanna start with the data people coming in just because data is the foundation for secure and security doesn’t exist without data. Privacy doesn’t exist without data. It’s a it’s a domain. It’s a it’s a dimension of data.

Right? Ethics is a is a philosophy versus right now an actual discipline. Right? And and how do you then implement it?

Right. So back to the AI and ethical AI, we need to bring the date of practitioners in first because frankly there’s more of us to fire any all all the other pieces.

Then we need to create, again, these bridges into these other, other debates because we can make them more effective. We can make them more we can bring more value to them and their roles and to their companies all up. And that’s going to create that ethical quality AI experience, trusted experience that people want as well. Again, where are the keys?

Like, these domains are the keys. They they hold the keys to those things. And we’re we have to work here from person coming out of college in college, their first job up to the c suites in these roles. We have to come together and start having these types of conversations that we make sure we put the right controls, the right processes in that actually lead to the outcome that we need for generations to come.

K? And faster, why do it alone as a company? Why figure this out one by one by one? Do you know how I Now you’re talking my language again.

It’s it’s you’re you’re totally speaking my language.

I I talk a lot. I did I did this when I was a gardener. I talk a lot about the the concept of data sharing.

Yes. Now I’ll give you a I’ll give you a concrete example back to my days of of running an IT shop. Yep. In in the world of network security and and and intrusion detection and trying to understand when when there’s when the bad guys are at the door.

Right? Companies are sharing they are sharing the footprints of these hacks. They they share all of this information. This is what this hack looks like.

This is what this pattern looks like. Right. So that everybody can be better at keeping the the bad guys away. Right?

That’s one example. Why aren’t we doing that?

On more shall we say mundane?

Wait. We should. Like, we should. Right. Like, if I can Google acme incorporated, And that’s commodity data.

Like, the the acme the like, that’s commodity data. If I can get it out of Google, it’s not a competitive advantage to me. Why are we hoarding that data not not not sharing?

We we we should so back back to you back. So, hey, I’m a hundred percent on on on page with you. In fact, I wrote a blog. I’ve been writing a blog, trying to share like, my journey from an an an a history major to a c suite at tech companies and being focused on tech for for long and how I did that. Right? And one of the things I gave as an example, and it’s why why is started thinking about the association in regards to not the mentoring or community need, which we know we all need, but the ability to actually truly drive, a regulation in shares around ethical AI is because I spent my first ten years in telecom.

And for those that don’t know this, telecom cannot operate independently.

When you’re using your cell phone to call someone across the US, you it’s hopping networks. Even though you might be on AT and T or you might be or whatever, And so they have a whole forum and I used to be a part of this and I used to support their systems in the nineties who basically defines access carrier, processes, provisioning the technology. When they’re talking five g, soon six g, seven g, whatever, they all have to agree to it and actually align to what that means and they have to agree to how they exchange some of the information and the billing around these things or the access to these things because they can’t operate by themselves.

K? We can do this. The only reason it hasn’t happened is because no one has focused on doing this. K?

And ten lawyers Yep. There there’s big enough of some things. Like, I think again, the the international association of privacy attorneys. They’ve got they’ve got fifty five out of I mean, every time in the past, when I’ve when when I’ve been in a position of, like, evaluating, hey, maybe we should be sharing our data with with, you know, valued member of our supply chain a or valued customer b because there’s economies of scale are largely like, no.

No. So this is why That’s what I meant by buyers. Yeah. This is why we need the privacy folks in.

Right? Because Yes. Because think of it this way. And I know we’re getting close on time, but think of it this way.

Even when it comes to bias. Okay?

Why can’t we have a nonprofit of professionals who actually do something like, I forgot what call. You know, with the third parties that serve, data that’s available for, like, for a lot of people. I can’t think of the technical term, but Why can’t we create a store of of data that is non bias that people can bring in and you can subscribe to it to basically help biased scenarios. And it’s dummy data.

K? So we have this happy real real data, but we can do male, female, you know, anything on, you know, the l b g t q, you know, type of re we can do different races. We can do different types of pick we can create that, and we can bring that into our models as we are working on these things to solve the bias problems and we can do it in a way that is not privacy oriented. K?

And we should do this because no one else is going to. Okay? Yeah. Aside I mean, this is this is how this is largely how cookies came into existence is is that there was a need early on, within the online advertising world to create these anonymized and aggregated data sets to allow marketers to understand what their users kind of looked like.

And there were there were supposed to be non bias, you know, aggregators and providers of the state, and they they still largely exist. But the answer to your question is rhetorical. Yes. We can be doing these things when we act together.

Stars who have done lots of things on these things that we offer that it needs to be we. Again, the tech companies, it does not behoove their model to do that. But the people in the fields, we need to do this. So it’s just Yes.

I’m we we need to peer to peer. I mean, I’m I’m a peer community because there are corporate entities that do this. Arguably, my ex employer done in Brad Street kind of does this. They create standards and then they sell them for a margin.

Is not is not cheap. And I don’t I don’t loan them the margin, but we can be doing this on a more peer to peer basis. I firmly to bring this down, bring the others, figure out the gaps, then we create the gaps. But we have to do this as a peer to peer association of practitioners for practitioners by practitioners in those fields.

Those those disciplines have to have to have that. There is no better place to stop this fantastic conversation that think could go on well into the evening here if we let it. But, that’s that’s a great way to to end Wendy. I’m I’m excited about the things you’re doing.

I’m looking forward to learning more through LinkedIn.

What’s what’s your URL? No. It is the, the association, dash a I.

Alright. No. V association dot ai. V association dot ai. Okay. So you’re in the dot ai domain.

But that Yeah. Donnie, I domain, and all one word, the association by the way.

Yeah. We’re in process of moving to our next version of this. So don’t look at it till, like, next week. We’re about to go live with R and D, but it’s out there.

Keep an eye out and not we’re gonna get more time because I need to get you involved. So Awesome. Thank you so much, Wendy. And to our listeners, to our subscribers, thank you much for tuning into another episode of the CDO matters podcast.

I hope to see you on another episode very soon. Thanks, Wendy.