Human Capital Risk in an AI-Driven Workplace

00:00:02 The IIA

The Institute of Internal Auditors presents All Things Internal Audit Tech.

00:00:06 The IIA

In this companion episode to Internal Auditor Magazine's Human Capital Risk in an AI World article, Tom Diamante talks with Manuel London and Richard Chan about how AI can help organizations identify behavioral, cultural, operational, and decision-making risks earlier, while also creating concerns around bias, surveillance, and employee trust

00:00:30 The IIA

and misuse.

00:00:31 The IIA

The conversation explores internal audit's role in auditing AI, supporting responsible implementation and helping organizations balance risk mitigation with innovation.

00:00:43 Tom Diamante

So maybe to get started, gentlemen, if it's okay, how would you define human capital risk and fold in, if you can, how that really is affecting how AI is being used today?

00:00:56 Manuel London

Richard, do you want to go or you want me to begin?

00:00:57 Tom Diamante

Please go ahead.

00:00:58 Manuel London

Okay, well, the human capital risk is the risks that are incurred due to individuals or teams in organization that are creating those risks.

00:01:10 Manuel London

They may be evident from other data like financial data, operational data, or directly from evidence of behaviors, whether it's misuses or in some cases fraud, bias, mistrust, and other factors that are high risk and high stakes for the organization.

00:01:34 Manuel London

And the advantage of AI

00:01:37 Manuel London

is that, of course, we know it's statistical methods for analyzing, integrating vast amounts of data that really could never have been done without it, at least not in terms of the amount of data that's possible.

00:01:52 Manuel London

And this could be financial data, it can be operations data, or indeed it can be behavioral data of different sorts, whether it's from emails or records of conversations, texts,

00:02:04 Manuel London

and so forth across the organization, not necessarily pinpointing one individual, but AI can pick up those risks early as an early warning system and provide a tracking mechanism to ensure that or to identify any unusual patterns as they are emerging before they become detrimental to the organization.

00:02:26 Tom Diamante

Thank you, Manny.

00:02:27 Tom Diamante

Richard, do you like to weigh in on that?

00:02:29 Richard Chan

Yeah, I think I definitely agree with Manny because

00:02:32 Richard Chan

Human capital risks cover various aspects as long as there are human elements of the organization where it creates uncertainties or potential risk aspects.

00:02:43 Richard Chan

And AI can certainly help providing analytical tool sets.

00:02:48 Richard Chan

At the same time, management scholars have really emphasized on the importance of

00:02:52 Richard Chan

the machine-human interaction, right, the conjoint agency, rather than using AI as a passive toolset to analyze it, but managers should really incorporate this toolset actively to prevent potential risk and enhance organizational performance.

00:03:10 Tom Diamante

Would you both agree that human capital risk really speaks to behavior in an organization that somehow is a threat to the business or the execution of that business?

00:03:21 Tom Diamante

Would that be a simple way to state it?

00:03:23 Manuel London

Right.

00:03:24 Manuel London

It also may reflect that the organization is not doing as well as it could do.

00:03:29 Manuel London

And it also can pinpoint, of course, positive aspects of when decisions are made well and they are good decisions and processes are outstanding that might not be evident unless they are brought forth from data that are analyzed on a regular basis.

00:03:46 Tom Diamante

So the organization's not performing at the level that it could be, is what you're saying, right?

00:03:51 Tom Diamante

Even though there's a level of success, maybe there's room for enhancement.

00:03:55 Manuel London

Right.

00:03:55 Manuel London

And of course, on the negative side, are decisions made too quickly?

00:03:58 Manuel London

Are they not aligned with what the organization's goals are or indeed its values?

00:04:04 Manuel London

Do they not consider socially responsible criteria?

00:04:08 Manuel London

You know, these are things we have written about in our article in the IA magazine.

00:04:14 Tom Diamante

AI seems to be getting mixed pressed, if you will, but there certainly isn't a lot of conversation these days around how AI is totally a value add to work and life in general.

00:04:26 Tom Diamante

Would you like to kind of just...

00:04:28 Tom Diamante

to talk a little bit about how AI might be something that contributes to risk or has some negative implications if misused or improperly used, or how as a management tool, which is, as you know, is often being deployed as a management tool, can lead to maybe some concerns if misused or improperly used.

00:04:50 Richard Chan

So it really depends on how the AI is being trained, right?

00:04:54 Richard Chan

So essentially,

00:04:55 Richard Chan

If it's being trained on biased data, the derivation or its recommended solution could be biased as well.

00:05:03 Richard Chan

So that's one aspect where AI can result in, whether it's biased hiring decision, performance feedback, performance evaluation, et cetera.

00:05:11 Richard Chan

So that's one aspect we need to pay close attention to.

00:05:15 Manuel London

Yeah.

00:05:16 Manuel London

And that happens because AI is trained on decisions that are made by the organization or by many organizations.

00:05:24 Manuel London

And often it's biased because the input is biased.

00:05:27 Manuel London

And so the results are like that.

00:05:29 Manuel London

But another factor is that people can mistrust AI or be concerned that it's going to take away their jobs or won't be used correctly.

00:05:39 Manuel London

And so that can lead to dissension in the organization or fear or people not adopting it as quickly as they could or using it as effectively as they could.

00:05:50 Manuel London

So those are potential negatives that can occur.

00:05:54 Tom Diamante

Well, on that issue, can you speak a little bit to the data on willingness or openness to actually use AI as an employee?

00:06:02 Tom Diamante

Because my understanding is that sometimes there's some reluctance for employees to use AI because

00:06:09 Tom Diamante

There's a concern that one's manager might view that as a negative, not a positive, meaning it's showing a lack of judgment or the kind of reliance on AI to do your job for you.

00:06:22 Manuel London

Yeah, or lack of competence.

00:06:24 Manuel London

You know, and what do we need you for if you're just going to use AI to generate the results?

00:06:29 Manuel London

or whatever they're working on.

00:06:31 Manuel London

Let's say it's a marketing presentation or something like that, or they're putting together a presentation on whatever topic.

00:06:37 Manuel London

And so they're using AI to do it for them.

00:06:40 Manuel London

And so they say, well, what are we paying you for if all I had to do is press up and then they could have done it.

00:06:45 Manuel London

But I think we should be thinking about AI as tools.

00:06:49 Manuel London

Just like Excel is a tool, Excel has become a very important tool, I'm sure, for auditors and certainly people in finance and in many fields, because it does so many things so well and keeps track of data and provides analytic tools.

00:07:03 Manuel London

So of course, we're using it.

00:07:05 Manuel London

So AI is really very similar.

00:07:08 Manuel London

There are a variety of AI tools and large language models that have been applied and could be used in different ways to make the organization more effective and efficient.

00:07:18 Manuel London

And so we should be using it.

00:07:20 Manuel London

Organizations should welcome it, and employees should learn how to use it as a tool that enhances their field of expertise.

00:07:27 Tom Diamante

So as one tool, and Richard, please chime in, but as one way of using this tool, or one way this tool has been used, has been to monitor behavior inside the organization.

00:07:39 Tom Diamante

Would either one of you like to kind of lean in on that a little bit?

00:07:42 Tom Diamante

Is that a good thing?

00:07:43 Tom Diamante

Is that a bad thing?

00:07:44 Tom Diamante

Are there concerns?

00:07:45 Tom Diamante

What are your thoughts on that?

00:07:47 Richard Chan

That's a very good question, right?

00:07:49 Richard Chan

So in terms of when it comes to monitoring, it really depends on individual's perception, right?

00:07:54 Richard Chan

Depending how, it also depends on how organization is utilizing the monitoring mechanism.

00:08:01 Richard Chan

So although AI monitoring can create some kind of surveillance cultures, they really diminish morale, increase stress, and will result in attritions.

00:08:12 Richard Chan

And in fact, in more recent Pew Research survey in 2025, what they have found that after surveying around 5,000 U.S.

00:08:23 Richard Chan

workers, over half, 52% of them, they worry the usage of AI in the workforce.

00:08:30 Richard Chan

And earlier research also found that 61% against

00:08:35 Richard Chan

using invasive AI application tracking physical movement and digital activities of employees.

00:08:42 Richard Chan

So there are certain list of concerns.

00:08:45 Richard Chan

But ultimately, it really depends on employees' perception, right?

00:08:49 Richard Chan

How these mechanism is being used, whether they actually use to improve performance, organization really use it as a reward or punishment mechanism.

00:08:59 Richard Chan

That will change how the AI monitor would be perceived.

00:09:04 Manuel London

Right.

00:09:04 Manuel London

It's not unusual for organizations to monitor employees' behavior.

00:09:08 Manuel London

Certainly, it's not new.

00:09:11 Manuel London

And some organizations have been doing it for many years in areas of manufacturing and delivery and things of that sort.

00:09:18 Manuel London

Probably less so in office kind of work in terms of monitoring emails or monitoring conversations, looking at how much time people are spending on the computer and different types of software and so forth.

00:09:33 Manuel London

And that's something people aren't necessarily used to.

00:09:36 Manuel London

And it's not necessarily good, but how is it related to the performance of those individuals and the outcomes of the organization?

00:09:44 Manuel London

So it may not be, and it may be that that's part of their job too.

00:09:47 Manuel London

So it just varies.

00:09:50 Manuel London

But as Richard points out, people are very leery about that and concerned that they don't have agency themselves.

00:09:57 Manuel London

to determine what they need to do on their jobs and how they're going to do it to produce the outcomes that the organization expects.

00:10:04 Tom Diamante

So context really matters here when you're talking about data, its use, and its interpretation, correct?

00:10:10 Manuel London

Oh, absolutely.

00:10:11 Manuel London

You know, it's used in different ways, different approaches, not just one.

00:10:14 Manuel London

And I think auditors can put together systems

00:10:19 Manuel London

that help them identify what's going on in the organization, take advantage of AI, but do it in a way that makes sense for that organization in various departments.

00:10:28 Tom Diamante

So I'm glad you touched upon that.

00:10:29 Tom Diamante

So in terms of audit, if you will, as a profession, what thoughts might you have in terms of the responsibility or the, if you will, of the mission of internal audit as it relates to the use of AI in their organizations?

00:10:45 Tom Diamante

Do they own it?

00:10:46 Tom Diamante

Should they have a leadership role?

00:10:49 Tom Diamante

What's your view of the role of the function of internal audit in the use and perhaps management or mitigation of misuse of AI?

00:10:59 Manuel London

I would say that they have a valuable role and they do it using non-financial as well as financial data.

00:11:08 Manuel London

So it provides additional input.

00:11:11 Manuel London

and identifies problems that may not have been evident as early on as they are.

00:11:17 Manuel London

So, I think internal auditors especially should understand the various AI tools that are available to them, how the organization can incorporate them into their processes, and then work with leadership to discuss this and determine what the internal audit role should be, what results are being identified, and have a discussion.

00:11:38 Manuel London

So essentially, they can take a

00:11:41 Manuel London

a role along with the leaders of the organization to understand how the heads of the different disciplines or areas within the organization in the C-suite, if you will, as well as the head of the organization, the CEO, and be part, be at the table to provide those data and discuss how best they may be used.

00:12:02 Richard Chan

Yeah, that's a very good point because internal auditory can also not only need to understand all these frontier models,

00:12:10 Richard Chan

and its potential application.

00:12:12 Richard Chan

Having this understanding, it will allow them to become integrated, right?

00:12:16 Richard Chan

Really incorporate these AI toolset into the business practice, whether it's HR function, accounting, finance, marketing, et cetera.

00:12:25 Richard Chan

For example, what happened in recent years is that a lot of major large companies, often they really want to catch the AI wave.

00:12:34 Richard Chan

They essentially don't have any rule or regulation.

00:12:37 Richard Chan

They just tell

00:12:39 Richard Chan

and force their employees to ask them to use these AI tools without understanding how these usage can help them to enhance their workforce productivities.

00:12:50 Richard Chan

So I was talking to one of the major Fortune 500 firms, one of the director in technology.

00:12:58 Richard Chan

What he has shared is that oftentimes without understanding how these AI tool set could help them to

00:13:06 Richard Chan

perform their day-to-day functions, employees simply use it on various purposes.

00:13:11 Richard Chan

It's not very effective usage of AI tools.

00:13:14 Richard Chan

So internal auditors can really become more effective integrators, ensuring there's a strong alignment with AI tool and how they can accomplish.

00:13:24 Tom Diamante

So essentially, audit should audit AI?

00:13:28 Tom Diamante

Would you agree with that?

00:13:30 Manuel London

Sure, that's absolutely a way of looking at it.

00:13:33 Manuel London

Are the tools being used effectively and how, certainly.

00:13:37 Manuel London

But also the auditor can have a role with leadership in understanding how well the organization is operating.

00:13:44 Manuel London

Are decisions being made?

00:13:45 Manuel London

Are costs being overrun?

00:13:47 Manuel London

Let's say they're implementing a new

00:13:49 Manuel London

system are people working together effectively from the different departments to do the integration that's necessary, essentially focusing on organizational dynamics and how well they're working.

00:14:00 Manuel London

So that may be a broader role than internal auditors are used to, provide some expansive value to create that value and maintain it in the organization.

00:14:11 Tom Diamante

So are there any principles or rule of thumb or something that you might advise internal auditors or leadership in general in terms of deploying AI as a management tool?

00:14:22 Tom Diamante

Are there any kind of do's and don'ts or any guidance comes to mind to make sure that it's deployed in a value-add way and then doesn't bleed into becoming, you know, like a surveillance type of a culture, you know, which everyone is concerned about?

00:14:39 Tom Diamante

how can that be done, or what assurances, or what role can internal audit play to make sure that when and if you deploy AI, it's done in a way that is, you know, have a...

00:14:50 Tom Diamante

a positive influence and not contribute to, or added to, unwanted, unhealthy risk.

00:14:57 Manuel London

Yeah, well, I suppose identifying how it's being used and track that, track out potential outcomes that portend problems like lower morale or people leaving the organization, attrition that results from that, evidence of stress, people not coming into work when they're supposed to, or being online when they're supposed to, depending upon if they're working hybrid or whatever.

00:15:18 Manuel London

they're working, are they identifying those potential problems that are essentially conflicts that can occur or culture risks, if you will, that can emerge?

00:15:29 Manuel London

And so the internal auditor can have a role in thinking about that and helping leadership think about that.

00:15:36 Tom Diamante

Would you agree that the leadership should be able to explain to their employees what data they actually are collecting and perhaps even

00:15:45 Tom Diamante

statewide that's so, if that's a problem or if that's problematic, would you say that maybe we haven't thought this through?

00:15:53 Richard Chan

Yeah, I think it's very important for the managers or the leadership to be transparent in the type of data being collected.

00:16:02 Richard Chan

And furthermore, how these data would be utilized, right?

00:16:05 Richard Chan

One of the reasons why people have these type of fear of being a monetary, being surveillance all the time is simply because

00:16:13 Richard Chan

they really do a lot of uncertainty, right?

00:16:15 Richard Chan

People don't know what type of data are being collected and how these data will be used to, whether these data will fundamentally change their performance evaluation or promotion opportunity, et cetera.

00:16:27 Richard Chan

So having clarity and showing responsible usage and transparency would be helpful.

00:16:34 Tom Diamante

Because that would erode trust, would it not?

00:16:36 Richard Chan

Yep, definitely.

00:16:37 Tom Diamante

And not just trust in the tool, but I think guilty by association, as they say.

00:16:42 Tom Diamante

But if your manager is using a monitoring system to manage you, then your monitoring isn't necessarily the same as management, correct?

00:16:51 Manuel London

Well, certainly it's a balance.

00:16:52 Manuel London

The idea of using AI to control and monitor is to avoid risk, of course, or to identify it as it's emerging.

00:17:01 Manuel London

But at the same time, the systems can promote

00:17:05 Manuel London

effective working relationships that can promote.

00:17:08 Tom Diamante

Social identification of high potentials, identifying positive outliers, right?

00:17:14 Tom Diamante

Special events, things that have occurred that might get under the radar if the radar wasn't on.

00:17:18 Tom Diamante

Very often we think about early warning systems or in terms of identifying a negative event, right?

00:17:25 Tom Diamante

But Manny, what you're saying is that, hey, we can also identify really unusual positive things that have taken place and take note of that as well.

00:17:33 Tom Diamante

right.

00:17:33 Manuel London

Exactly.

00:17:34 Manuel London

This is what we mean by a healthy risk culture in the AI world.

00:17:38 Manuel London

And the internal auditor and the staff can help promote this and understand its value to the organization.

00:17:46 Tom Diamante

Right, which might contribute directly to things like product development and reducing cycle times and just an innovation in general, right?

00:17:53 Tom Diamante

So identifying when things go right, when things go efficiently, and

00:18:00 Tom Diamante

product development comes to market very rapidly, products are commercialized more rapidly than expected, ahead of budget, under budget, ahead of time, like delivery is there, and taking notice of these things and be able to share that enterprise-wide, which also might be something that may not have happened unless AI was involved.

00:18:20 Richard Chan

Right.

00:18:20 Richard Chan

So that's a very good point as well, because in terms of research, people actually have found that the use of AI toolset is actually

00:18:28 Richard Chan

result in more creative ideas.

00:18:31 Richard Chan

One of the reasons is because humans tend to be biased and utilize their own judgment experience when you come up formulate with creative ideas.

00:18:40 Richard Chan

But AI would be able to enable...

00:18:43 Richard Chan

workers to look beyond their comfort zone, right, and resulting in more creative solutions.

00:18:49 Richard Chan

However, it's also very important to ensure that there's some way to safeguard somehow blind acceptance.

00:18:56 Richard Chan

Innovation is great, but internal auditors or employees also need to look at whether such innovations will result in useful result.

00:19:07 Richard Chan

Otherwise, it's just

00:19:10 Richard Chan

random combination of wild ideas, right?

00:19:12 Tom Diamante

So it's a great way to overcome just traditional silos or organizational barriers.

00:19:17 Tom Diamante

So this is a good example of technology kind of coming through bureaucratic impediments, if you will, by use of technology.

00:19:25 Tom Diamante

You know, another thing I've come across use in practice is that no one is ever against innovation, right?

00:19:30 Tom Diamante

The innovation word.

00:19:32 Tom Diamante

So AI is always put forward typically as, new innovation and they anthropomorphize, the AI agent, give it a name.

00:19:40 Tom Diamante

They do all these sorts of things to speed implementation.

00:19:43 Tom Diamante

Often that it makes it more difficult culturally for anyone in the organization, perhaps including internal audit, to tap the brakes and say, hold on a second.

00:19:52 Tom Diamante

You know, what are we doing?

00:19:53 Tom Diamante

Why are we doing this?

00:19:55 Tom Diamante

What data is being collected?

00:19:57 Tom Diamante

What if we're wrong?

00:19:58 Tom Diamante

what if everyone uses this data as a validated output when really it's just input for decision making?

00:20:06 Tom Diamante

Have you seen or what advice would you have based upon your experience and research in it where how it's implemented and the mechanisms used to implement it can kind of get in the way of doing it correctly, you know, for the sake of innovation and speed and kind of, you know, bringing in the, you know, the next best thing?

00:20:23 Tom Diamante

You know, there's such a rush

00:20:25 Tom Diamante

to implement AI.

00:20:26 Tom Diamante

And it's, probably, most people would probably agree that you don't want to get in the way of new technology and certainly don't want to get in the way of AI coming in to make us, more efficient and to improve operations.

00:20:41 Tom Diamante

Like nobody wants to do that.

00:20:42 Tom Diamante

You don't want to be accused of the person tapping the brakes.

00:20:46 Tom Diamante

But in fact, someone needs to ask these difficult questions.

00:20:49 Tom Diamante

You know, should we do it?

00:20:50 Tom Diamante

Why are we doing it?

00:20:51 Tom Diamante

What data are we collecting?

00:20:53 Tom Diamante

Who is making

00:20:55 Tom Diamante

decisions based upon that data, right?

00:20:57 Tom Diamante

All of that.

00:20:58 Tom Diamante

And one of the implications of all of that.

00:21:00 Tom Diamante

So I guess, what I'm trying to, the question I'm trying to pose here is, what are the cultural impediments or what are the cultural considerations that need to be taken into, you know, into consideration before AI is fully deployed?

00:21:16 Tom Diamante

And how can AI maybe, how can internal audit play a role

00:21:22 Tom Diamante

in making sure that when it is implemented, timing is right, the outcomes are anticipated, and there are checkpoints or guideposts or guardrails in place so that if a fix is necessary, they actually have the capacity to improve it and make it better.

00:21:40 Tom Diamante

Big question, I know.

00:21:42 Manuel London

Yeah, that was going to say, that's a very big question.

00:21:45 Manuel London

Generally, I think what you're saying is that the internal audit staff can work together with people who are responsible for major operations.

00:21:55 Manuel London

Let's say integrating a new software system that cuts across departments and disciplines and doing it in a way that is going to be effective and efficient.

00:22:04 Manuel London

As data are collected, let's say relative to the goals, the per chart they have for

00:22:12 Manuel London

what's supposed to happen when, understanding not just the data and where problems are occurring, but helping to pinpoint why they occur and what can be done to improve the situation or avoid it in the future?

00:22:24 Tom Diamante

In terms of value to the board and leadership in general, kind of high level, where do you see the value of AI that contributes directly to improve governance or to the efficacy of the board?

00:22:38 Tom Diamante

What would they become aware of?

00:22:40 Tom Diamante

Maybe it's early warning systems, maybe risk escalation, competitive issues.

00:22:46 Tom Diamante

where do you see AI being as influential in terms of being useful for board decision making and board efficacy and governance in general?

00:22:56 Manuel London

Of course, it's all of those things.

00:22:58 Manuel London

And one can sit down and look at how AI is being used across the organization or within each area of the organization.

00:23:05 Manuel London

What's being done in the financial area, for example, to ensure risks are being avoided, let's say fraud is being identified or avoided, of course, how this is affecting the reputation of the organization.

00:23:19 Manuel London

They can identify

00:23:22 Manuel London

irregularities of things going on.

00:23:24 Manuel London

The same thing in operations in terms of safety, in terms of quality, all sorts of quality controls.

00:23:31 Manuel London

And how is AI being used to implement those controls?

00:23:35 Manuel London

Are those being done in ways that are effective rather than making people wary of what's going on and so reticent to move forward with innovation?

00:23:45 Manuel London

and being active.

00:23:47 Manuel London

Customer relationships, another area, of course, where there are all sorts of data that are being collected and provide early warning systems for a whole host of potential problems.

00:23:59 Manuel London

And then as we've been discussing a lot about organizational dynamics and the way decisions are being made, people are interacting with each other, whether it's they're doing so collaboratively or conflicts are emerging.

00:24:11 Manuel London

And so AI can help identify those

00:24:15 Manuel London

issues as well and try to fine-tune and improve communications.

00:24:20 Manuel London

So really, AI has potential value across the organization in each department.

00:24:28 Manuel London

Internal auditors will be using the results of AI to pinpoint problems as they occur, but also to show how it can be of value and then to work with leadership throughout the C-suite

00:24:40 Manuel London

to improve the way it's being used and ensure it's being used effectively in finding areas where it should be used and where it can do more for the organization where it's not being used perhaps right away.

00:24:53 Richard Chan

Yeah, that's a great point.

00:24:54 Richard Chan

And also, essentially, how organization should treat AI is ensured there will be human in the loop, right?

00:25:02 Richard Chan

Internal auditors or top management teams should really be integrators.

00:25:06 Richard Chan

And while at the same time, not only understanding the latest technology and how they can effectively improve performance, at the same time, they also need to safeguard against blind acceptance.

00:25:19 Richard Chan

Otherwise, garbage in, garbage out, right?

00:25:21 Richard Chan

We all know the what type data we receive will dictate what type of output we generate.

00:25:27 Richard Chan

So it's important for internal attitudes to have a practical checklist.

00:25:33 Richard Chan

understanding what tools are being implemented and how these tools will impact the different functional areas, and also understanding where the data are coming from and whether these data will be objective and non-biased, et cetera.

00:25:49 Richard Chan

And all those to ensure that they are human in the loop, human in the AI loops.

00:25:55 Richard Chan

That would be important.

00:25:57 Tom Diamante

And so what in your mind is the perhaps one or two things that an organization must attend to?

00:26:03 Tom Diamante

in order to ensure that AI is implemented in a positive way and not necessarily a negative way.

00:26:09 Tom Diamante

So how can we make sure that AI is something that mitigate risks and doesn't irritate risk?

00:26:16 Tom Diamante

What comes to mind?

00:26:17 Manuel London

I'll just repeat what I've said a few minutes ago, and which we have written about in this concept of the internal auditor thinking about what constitutes a healthy risk culture for the organization generally, and AI contributes to that.

00:26:32 Manuel London

It doesn't mean that whatever the audit

00:26:35 Manuel London

staff has been doing has got to change.

00:26:39 Manuel London

But how does AI facilitate that as a tool that can guard against bad risk and move toward a more effective and innovative organization?

00:26:49 Tom Diamante

So you want to get rid of the bad risk, but also nurture, if you will, the entrepreneurial positive risk and not do one for the sake of compromising the other.

00:26:59 Tom Diamante

I think that's probably a

00:27:01 Tom Diamante

difficult balance.

00:27:03 Tom Diamante

Richard.

00:27:04 Richard Chan

Yeah, that's exactly what I thought as well.

00:27:06 Richard Chan

I totally agree with Juan.

00:27:08 Richard Chan

Both of you have to mention.

00:27:09 Tom Diamante

In terms of wrapping this up, you know, I appreciate the time of both of you.

00:27:13 Tom Diamante

And again, obviously it was a pleasure working with both of you to produce the article.

00:27:18 Tom Diamante

I just kind of think we all agree that AI, like you said earlier, is a very valuable tool.

00:27:23 Tom Diamante

But like any other tool, how you use it really matters.

00:27:26 Tom Diamante

One thing we touched upon is that if an organization cannot explain what data it is collecting and why it's collecting that data and how it will use that data to the workforce, then they probably haven't thought it through and probably should kind of go circle back and get the answers to those questions so that when they do implement it, Mandy, as kind of you put it, we're encouraging the innovation and the entrepreneurial behavior

00:27:51 Tom Diamante

while also using the tool to mitigate and prevent unwanted, unhealthy risk.

00:27:58 Manuel London

Right, and to think about human capital risk in particular as perhaps an area that internal auditors have not thought as much about.

00:28:06 Tom Diamante

Right, and perhaps they should play a role there.

00:28:10 Tom Diamante

one thing, interesting, and I know we're trying to wrap it up, but, and without backgrounds, most of us come out of HR kind of types of backgrounds.

00:28:18 Tom Diamante

No, HR typically kind of owns the human capital space.

00:28:22 Tom Diamante

So maybe one thing we've touched upon here, even though lightly, is that maybe AI should not be, if you will, completely owned by HR.

00:28:32 Tom Diamante

but maybe should share the wealth and internal audit should play a role in the use and ensure guidance and navigation of how AI is being used effectively with HR.

00:28:42 Tom Diamante

Would you agree?

00:28:44 Manuel London

Absolutely.

00:28:44 Manuel London

And especially in times of change and in organizations that are going through change, let's say a merger or acquisition of some sort, where they can really identify human capital risk and try to understand how that's influencing decisions.

00:28:59 Manuel London

and to ensure that risks are not incurred unnecessarily.

00:29:02 Tom Diamante

Well, thank you both.

00:29:04 Tom Diamante

I think that wraps it up.

00:29:06 Tom Diamante

I appreciate your time, and I look forward to our next research article together.

00:29:12 Manuel London

Absolutely.

00:29:13 Manuel London

Thanks, Tom.

00:29:14 Manuel London

It's Richard.

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