2960: Navigating AI Ethics, Tech M&A and Innovation With Deloitte

[00:00:00] How can businesses responsibly adopt AI while also staying ahead of emerging trends and cyber security threats? Well today I'm joined by Deborah Golden, Deloitte US Chief Innovation Officer. We're going to dive into some of these crucial topics today and also explore the importance

[00:00:21] of embedding ethics into AI strategies from the ground up and also discuss anticipated trends like the space economy and sustainability while also examining the biggest cyber security threats that businesses face today. And Deborah is bringing a wealth of knowledge on converging technology mastery with industry

[00:00:42] expertise to create innovative solutions, solutions that solve real world problems. And her passion for responsible AI adoption and upskilling the workforce really shines through in our conversation today. A big thank you to my amazing sponsor who helps me keep exploring the world of tech

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[00:02:19] So buckle up and hold on tight as I beam your ears all the way to Washington DC as we undercover how businesses can leverage AI, quantum computing and space commercialization to drive future innovations. So a massive warm welcome to the show.

[00:02:37] Can you tell the listeners a little about who you are and what you do? Sure. Thank you for having me. I'm Debra Bolden. I am Deloitte's US Chief Innovation Officer. And in this role, I work at the intersection of innovation strategy and performance, focusing

[00:02:53] on encouraging innovation both within and outside of Deloitte. And before this role, I served as Deloitte's US cyber and strategic risk leader where I was responsible for driving and growing much of our technology related business and had

[00:03:08] the pleasure of driving a number of edge technology solutions for Deloitte. Well I'm really looking forward to learning more about your insights today because every day on this tech podcast, I always try and demystify technologies and talk about solving

[00:03:24] real world problems and the kind of things that every business is talking about right now. And when I say those words out loud, I know everyone automatically assumes AI. There's so much excitement and indeed caution around it as well.

[00:03:38] So to set the scene for our conversation today, let's dive straight in. How can businesses adopt AI in a responsible way while also focusing on ethical considerations and what steps should they be taking to ensure transparency in their AI operations?

[00:03:55] Because I've been to so many tech conferences this year and this is a topic that seems to be reoccurring at every single one of them. And I think, you know, building trust in AI is about both capability and human perception.

[00:04:10] And I think when you think about both of those capacities, you have to think about categories like humanity, transparency, capability, and reliability. And so in order to adopt AI responsibly, businesses must embed ethics into their AI strategy from the ground up, period. So it's not just about compliance.

[00:04:34] It's about defining the moral compass of your technological and your business future. And so when you think about that from a holistic perspective, in order to build trust, organizations need to really think about how do you build that approach and promote trustworthy AI?

[00:04:51] Now that word in and of itself founds candidly both everything and nothing at the same time. So let's break that down a little bit. And you think about the steps. Some of them may include things like establishing ethical frameworks and governance, like we have a trustworthy AI framework.

[00:05:11] So really coming up with that framework on how to be clear and concise across the enterprise. And in order to do that, you need to be able to build diverse and inclusive teams to be able to support that.

[00:05:25] And then as you actually evolve that, how do you conduct regular and rigorous bias audits throughout that timeframe? So it's not again a one and done type of capability. One of the things I think, as you mentioned, AI is everywhere.

[00:05:42] How do you actually make sure that there's transparency by design so that AI doesn't become a black box? So that as you're designing it, that transparency is in the design and the decision making, that it's understandable, it's explainable.

[00:05:56] And then I would say the next step is making sure that you're engaging with all of your stakeholders. So whether that community is your customers, your employees, your partners, all of that diverse stakeholder community so that they understand the measures that are in place,

[00:06:11] not just how the data is being used, what are the controls in place? What is being exerted over that data? What is the response that's being anticipated? What are the outcomes being anticipated? What are the incidents that are happening with that data?

[00:06:25] So that there really is some explainability that is actually occurring with that approach and with the mechanisms going on around the AI components. And I think ultimately, after all, what is the accountability that you expect and the measures that you expect against the AI components?

[00:06:43] So that again, you understand not just the capability associated with AI, but that human perception that is also associated with it. I think when you look at it end to end across the board, you start to then build that trust associated with it.

[00:07:00] And I think if you can build that framework around that, and again, not just a one and done, you can start to build that rigor that is necessary and that transparency across your operations. 100% with you on that.

[00:07:14] And another trend that I think we're seeing more and more of is an increase in mergers and acquisitions. And I was reading before you came on the podcast today that the M&A landscape is expected to increase in activity throughout the remainder of 2024 and into next year.

[00:07:29] So what trends do you think we should be anticipating? And how are companies positioning themselves for growth throughout this digital transformation? Well, I certainly don't think that AI is going to slow down anytime soon.

[00:07:42] So at the top of the charts are certainly going to continue to be AI. And I think that the AI front is candidly just at the tip of the spear. I think what we've seen so far has been one portion of AI, and that's the gen AI portion

[00:07:59] of it. And so I think what we've seen so far is the hype cycle of that, which has been the gen AI portion, which has predominantly been on the operational efficiency side. I think we'll continue to see that.

[00:08:10] But what I think we'll see trending is into the actual business enhancement side of that. So I think we're going to see that really start to pick up, which is around AI automation acquisition. So focus on the cutting edge capabilities, not only the streamlining operations, but

[00:08:28] the start of how do we start to enhance customer experience and actually transformation of our businesses? That is, I think, going to really pick up steam and really start to eclipse into the rest of 2024 and beyond.

[00:08:44] I think you're going to continue to see what we've been seeing candidly over the last year or so around things like cybersecurity and cloud. I don't think those are going to go away, particularly as we see more and more cybersecurity

[00:08:58] threat continue to escalate around advanced capabilities and protecting digital assets. And certainly cloud is not going to go away. The continuation of service providers, it's not just a trend that is going to continue to be a shift in business operations.

[00:09:15] But I think as we start to look at another race to what is the next economy, I think M&A is also going to look at the activity around what is that next big shift in industry.

[00:09:27] So whether it's the next space economy or the next digital economy, sustainability, as we think about the green economy, I think we're also going to start to see and continue to see consolidation in those areas around fueling, no pun intended, our M&A activities.

[00:09:44] So seeing those emerging industry capabilities and industry convergence, I think it's also going to be quite a big pickup over the next three quarters in 2024. Another big topic right now is artificial intelligence in cybersecurity and how AI is

[00:10:04] being used by both the good guys and the bad guys, almost having good AI versus bad AI. So what do you think are the biggest cybersecurity threats facing businesses today? And what strategies should organizations be implementing to better enhance their defense

[00:10:20] mechanisms and protect against such threats as they continue to increase? Yeah, and cybersecurity threats obviously have been around for a long time. They're not going anywhere and they're going to continue forward. Certainly taking advantage of today's rapidly evolving digital landscapes as ransomware

[00:10:37] attacks grow more and more sophisticated, emerging technologies continue to expand the attack services. And obviously, AI is not only driving more and more capacity, but with misinformation, disinformation, foul information, we have new types of cybersecurity

[00:10:58] threats, inclusive of things like deep fakes, which are just giving us more opportunities, if you will, for cybersecurity threats. And so I think some of our biggest threats continue to be some of the threats that we've seen before. So things like ransomware attacks, phishing schemes, insider threats,

[00:11:17] typical types of vulnerabilities. But we also, because of the openness, if you will, of the way that we operate today, we have supply chain threats. So it's not just what's inside your own four walls. We continue to see, obviously, the continued ecosystem threats around the supply chain.

[00:11:35] And so as we think about the expansiveness of these evolving digital landscapes, how do we look at protecting not just our own individual landscape? Obviously, the supply chain or the value chain is going to continue to be more and more

[00:11:50] important. And so the strategies that we look at need to be multifaceted, underscore, underscore, and combining technology training, proactive measures and some examples again continue to need to be things like zero trust architecture, endpoint security,

[00:12:08] and I think even getting more and more advanced around things like AI enhanced multi-factor. So when you think about users required to authenticate with multi-factors, whether that be a password, mobile notification or biometrics.

[00:12:23] And again, I think when you start to introduce the world of AI, you can start to get more and more advanced as you look at anomalies. So do you have an AI driven tool to monitor behaviors and detect anomalies that can adapt authentication requirements?

[00:12:41] So you're now instead of being reactive, you're now proactively mitigating risks and dynamically fortifying defenses against emerging cyber threats. And so in that scenario, you can be very proactive and get much more adapt at being able to pivot against the risks.

[00:13:00] I think that's the kind of world we're going to be faced with in terms of being able to move so quickly to address the risks that are going to be in front of us.

[00:13:11] And I don't want to focus too much on the bad stuff because there's enough of that out there in the universe without us both adding to it. So in a bid to restore the balance of the universe, so what do you think is the most

[00:13:22] promising innovations in technology that you think will maybe reshape industry standards and indeed those consumer expectations that businesses must rise to in the coming years? Anything excite you there? Well, I'm forever the optimist.

[00:13:37] So as much as I am definitely aware of the threats that are in front of us, I am forever the optimist. And I am honestly, the promise of the future is really in front of us.

[00:13:50] So I look at what I call the AI plus plus plus, which is everything that we're going to be able to put on top of AI. And so it is nothing more than going to fuel the fire of opportunity in front of us.

[00:14:02] So when you think about what AI is going to enable for us, so merging AI with all the other emerging technology is going to be able to unlock the exponential potential, seamlessly providing us with so much other opportunity, not only to give us things we

[00:14:20] never thought about, but it's going to shift both demand patterns and industry standards. So take, for example, putting quantum computing on top of AI. So when you actually put combining the power of AI with the power of quantum on top of

[00:14:36] biotechnology, as an example, we could actually accelerate the creation of new agro tech products to feed more communities, to create new biotech capabilities while bringing time to market and R&D costs down in a matter of minutes and days and weeks that predominantly

[00:14:54] before took months and years, if ever were capable. So that would have never been able to happen if not for the combination of AI, quantum and machine learning. So not one thing singularly, but again, the AI plus, plus, plus.

[00:15:11] And so for me, that is one promising innovation combination, if you will. That is, again, for me, super exciting. Another one that I think of that I think is going to fundamentally change the way that we

[00:15:24] think about the world of tomorrow is the space economy or space commercialization. And while I think space tourism is going to be exciting, that's not entirely what I'm talking about. The advancements in space infrastructure. So when we think about satellites and rockets and operating systems around launch and

[00:15:42] communications are maturing possibilities for how we think about space applications. So think about Earth observations and ultimately what Earth observation means for us here on Earth. And they're going to ultimately reshape the potential for business outcomes across

[00:15:58] so many different industries for us to think about supply chain visibility or value optimization and resilience. We're going to be able to enhance our capabilities on Earth based on what we can see and do and evaluate with space.

[00:16:13] And so the future of in-space manufacturing, as an example, or even consumer space travel or low Earth orbit activities and the fact that the cost of that and the efficiency of that and the value of that is just evolving faster, quicker, better is truly

[00:16:30] fascinating. And so for me, space economy and commercialization and the promising innovations in tech around that is also, I think, just going to evolve at speeds that we will have never seen before. So those two, I think, are just going to move leaps and bounds over the next.

[00:16:48] Honestly, I think they're going to come here faster than we know it. But I'll say, you know, 12 to 18 to 24 months, I think they're going to make big moves. Exciting times ahead. And of course, with the hype surrounding AI and any emerging technology, it's often easy to get

[00:17:04] away or get swept away by it all and make the mistake of approaching business problems with tech first and problem rather than problem first and tech. And I know at Deloitte, this is something that a responsibility that you take very seriously.

[00:17:18] So how do you approach the challenge of blending technological mastery with industry acumen to create those innovative solutions that redefine market landscapes and ultimately solve real problems? So we like to take a converged or applied approach aimed at addressing outcome driven needs.

[00:17:36] So we've used the latest future focus technology with industry to help us and our clients look beyond what it is to see what could be. And I'll give a couple of examples here to really highlight the truth around bringing those pieces together.

[00:17:53] So one is converge health, and that really combines deep health care experience with advanced technology like AI, data analytics, cloud computing, cyber, all of the things we've been talking about. But focusing on patient care by tailoring treatment plans and providing instant health

[00:18:13] updates. We use extensive data networks and systems that work well together, convening that with a vast ecosystem and alliances, converge health helps bring healthcare providers and coordinate better leading to improve to health care patient with smoother operations. And to your point, really looking at bringing that external expertise.

[00:18:34] And so we have doctors and nurses and communities here in health. So having that expertise of the problem, understanding that problem and that expertise to build platform capabilities, applications and networks, leveraging alliances and ecosystems and capability to seamlessly bring those two things together, technology,

[00:18:55] mastery and industry acumen to create solutions and capabilities that have never been established to really look at a shared global community. And that is one example of how we brought that together. Another one is around what we've termed industry advantage, which is merging specialized

[00:19:13] industry knowledge in a very similar way with state of the art technologies, which again includes things like AI, ML and predictive analytics where we've embedded technology solutions with, again, very specific industry specialty for highly customized strategies. And that really addresses the nuanced challenges of what

[00:19:35] businesses are faced with. So really putting that business problem first. So we harness that extensive expertise, proprietary data, understanding those algorithms. What is actually the importance of the problem? Understanding that and then how can we accelerate the actual technology to help you solve

[00:19:55] that problem? And that really is, I think, kind of the secret sauce of looking at that access of understanding. It's not just one thing, right? It's the how do you take the tax problem and the consulting problem and the ecosystem

[00:20:09] problem? Because technology, by the way, is one part of the problem. Understanding all the pieces of the technology applied to that in the component of the complexity is actually where we help to solve for actually the client's problem and get to the outcome that they're solving for.

[00:20:27] 100 percent with you, and I also think as the pace of technological change continues to gather pace, ensure that nobody gets left behind has never been more important. So with that in mind, what role do workforce training and development play in

[00:20:43] enabling businesses to leverage AI both effectively and ethically? And how can companies ensure that their teams are ultimately equipped with the necessary skills? Because there seems to be almost a tech skills gap at the moment.

[00:20:55] Yeah, and I think at the end of the day, all of AI requires a reimagination of workforce training and development. And so as we think about again, I'm going to be the forever optimist. What Gen AI allows us to do is actually democratize access.

[00:21:14] I mean, that is truly what Gen AI, so one portion of AI allows us to do. So if you think about what Gen AI is allowing us to do, it's allowing everybody to have access to AI. So traditionally, if you think about traditional developers, you ought to

[00:21:30] have a developer background or an engineering background to be able to code or understand how to develop capabilities. In the world of AI, what Gen AI allows people to do is you don't actually need to have a development capability. And so anybody can actually have the ability

[00:21:47] to play with, learn with, code with AI. And so tech skills are no longer a barrier to entry. Gen AI has actually democratized technology, broadening access to advanced tools and capabilities. And so when you think about the optimistic side of where we are and

[00:22:04] what data interpretation means and collaborative problem solving means, we actually have a really promising view of facilitating upskilling of both non-technical and technical employees. But with that comes the need to actually reimagine then how we look at workforce training

[00:22:22] and development and then what we need, because it's not about learning a single technology, but how do we look at platform agnostic agility? And I think with that, we actually need to look at how to actually build advanced combinations of technology and novel application.

[00:22:38] And again, the forever optimist for me, it's the art of the imagination. I have a harness human potential. And so when I think about that, I mean, we really have endless opportunity. And given your experience and everything that you're seeing and hearing at the moment,

[00:22:55] how do you see that relationship between technology and industry evolving? And are there any unconventional paths or opportunities that you think many might be overlooking at the moment? Is anything that's catching your eye there? I have everything inclusive of unconventional.

[00:23:10] So, yes, I absolutely believe that to be true. And I think what we're seeing is increased verticalized innovation. So what I'll say is, you know, really looking at there continues to and I think there will always be an industry lens to this.

[00:23:26] But I think reduction in barriers like we were just talking about will align better to customer experience and value. I think what we continue to see in AI is only going to continue to enhance this is a

[00:23:37] customer centric view of, I don't want to say everything, but just about everything. Right. So we know more and more is going to be customer driven. And so as things become and continue to be more customer driven, I think the barriers

[00:23:53] of industry are not necessarily going to define how solutions are actually solved for from an outcome perspective. So while historically, take for an example, a health care solution was solved for in health care industry.

[00:24:07] I think you're going to see less and less of the industry itself solving for that particular industry solution. And then previously when I gave the example of space, space may not solve just space problems. Right. We know Earth observation can solve agri tech problems.

[00:24:23] And so similarly, health may not solve health problems. Health may solve other problems. So as you start to look at accessing and the cohesion and collaboration between multi types of industries, I think you're going to start to see, like I said, verticalized

[00:24:38] innovation where there's a crossover of not only industries, but technologies. And I think this is going to cause what I'll call open innovation across types of industries, types of technologies and types of customer strategies.

[00:24:55] That's going to have us really shift our thinking, not just around new types of revenue streams, but new types of business models. And I think we're already starting to see a shift in focus from perhaps ownership and

[00:25:09] IP to outputs and what we expect from different types of outcomes when it relates to solving really complex problems. And looking to the future, what's your vision there for a future of tech innovation? Any advice on businesses and leaders and anybody listening on how they could maybe

[00:25:28] better prepare to embrace and drive this next wave of technological advancements? Any tips or advice you can share on that? Yeah, I mean, I think, you know, three maybe a core piece of the deal are really harnessing creativity with innovation.

[00:25:44] You know, being able to really foster a culture of agile thinking, I think is really going to be critical as you think about how do you champion a culture that blends creativity with innovation while empowering teams.

[00:25:58] Obviously, it's going to be important, I think navigating this content issue while leading with clarity and vision is going to be important. I think it's really easy to become overwhelmed with innovation and information and what to do next and how do we look at all this complexity?

[00:26:14] I mean, there's a lot of noise in the system. So how do you actually navigate and find clarity and vision and really focus on what's strategically important and impactful to drive meaningful change?

[00:26:26] And I think, you know, last but not necessarily least important, but would be to how do you actually redefine what leadership means? I think embracing flexibility and continuous learning. I think we've always looked for visionary leaders.

[00:26:43] But how do you look to be visionary while flexible and committed to continuous learning and being prepared to pivot rapidly while embracing new technologies? And oh, by the way, inspiring and thriving amidst change without having a playbook,

[00:26:57] because I think the notion of having a playbook is long gone. And before you came on the podcast, I was doing a little research on you and I was reading about your reputation as someone who boldly explores the unconventional leading with insight and provocation.

[00:27:12] And this got me thinking, she must have picked up more than a few stories in her time. So can you share the funniest or most interesting story that has happened in your

[00:27:22] career? I'm sure there's quite a few of them, but is there any you are able to share? Well, sure. There are definitely quite a few. And one that I'll share is, you know, obviously amongst my travels, I've been to many,

[00:27:36] many places and all of the places I visited and all of my stories are always ones I remember. But in one that is near and dear to my heart, I was able to actually go and visit NORAD, which is the North American Aerospace Defense Command.

[00:27:51] And it is for anybody who is ever able to go and visit, it is truly an astonishing, just state of the art in awe. I mean, I am a self-proclaimed nerd if you haven't figured that out yet.

[00:28:08] But for me, it is a showcase of many things, inclusive of pioneering technology, resilient infrastructure, innovation under pressure. I was able to learn so much about the people and their resilience and what it means to secure and be there for our country in times of need.

[00:28:31] And honestly, how technology and human resilience works. And for me, not only that, when I left, I was able to pick up the phone and also talk about how proud I was about being there and just learning so much about things and

[00:28:47] learn that also my father actually helped to engineer part of NORAD. So for me, it was also a moment to be able to be like, really? You also helped to engineer part of the architecture that was built for NORAD.

[00:29:02] So that was also something that was endearing to me as I sat back and marveled that we basically have the capability and the capacity to bring forward such innovation and technology. The other thing that is also quite near and dear around, things that are

[00:29:17] super interesting when we have missile defense systems that exist in such unique ways. The other interesting and most innovative thing about it, every year at Christmas for Christmas Eve, NORAD also tracks Santa around the world, but what's most innovative

[00:29:30] about that. And it actually started as a misprinted phone number that accidentally directed a child to actually their phone number. And instead of disappointing children, the officers on duty decided to play along. And that tradition actually holds true today.

[00:29:48] So I like to say it truly is innovation at its best. So I will leave you with that. And aside from being, like I said, a self-proclaimed nerd, it probably was one of my most memorable trips of watching, truly, truly learning both humanity and innovation

[00:30:05] tech at its best. Wow, what an incredible story. Great moment to end on. But finally, for anyone listening, wanting to find out more information about everything we discussed today, obviously Deloitte is a huge website.

[00:30:17] People want to find out more information or maybe ask yourself or your team a question. Is there anywhere in particular you'd like to point everyone listening? They can certainly follow me on LinkedIn is probably the best way they could follow me

[00:30:31] on LinkedIn. And that's probably the easiest way to get to us or on Deloitte. Excellent. Well, we've covered so much in 30 minutes today from how businesses can adopt AI responsibly, the rise in tech M&As, cyber security's biggest threats, but also adding so much positivity into the future.

[00:30:51] Innovation in tech. What is next? How can these innovations reshape industry standards and consumer expectations and beyond in the coming years? I'd love to stay in touch with you, get you back on the podcast later in the year or early

[00:31:03] next year to see how things are still evolving. But thanks for joining me today. Really appreciate your time. Thank you so much for having me. It was great. I think as we conclude our conversation with Deborah today, it's evident that embedding

[00:31:15] ethics into AI and staying vigilant against cyber security threats are paramount for future success. And her insights into the anticipated trends and the convergence of technology with industry expertise provide a roadmap for businesses aiming to innovate responsibly.

[00:31:34] But what are your thoughts on the role of ethics in AI, the future of tech innovation? What excites you? What concerns you? I'd love to hear from you. So email me tech blog writer at outlook.com, LinkedIn, X, Instagram, just at Neil C.

[00:31:49] Hughes, easiest person in the world to find. But that's it for today's episode. So thank you for listening. Keep questioning, keep innovating and stay tuned for more thought provoking discussions like this on Tech Talks Daily as I return again tomorrow with another guest.

[00:32:06] Well, hopefully you'll join me again tomorrow. See you then.