3254: Inside the Accenture Tech Vision 2025 Report and and the Future of AI-Driven Business

[00:00:03] What happens when AI stops being a tool and becomes your co-worker, your creative partner, even your brand ambassador? Well today I'm joined by Mary Hamilton from Accenture and we're going to unpack the 25th edition of the company's technology vision report. This year's theme? It's AI-powered autonomy.

[00:00:27] And my guest today is going to share how generative AI is no longer confined to screens and keyboards. It's breaking into physical spaces, reshaping customer experiences and transforming the workplace. The browser may have become the gateway, but now AI is becoming the brain. So we explore what that means for enterprises navigating a world where trust is the true enabler of scale.

[00:00:54] Where generalist robots learn on the job and where employees are expected to collaborate with intelligent digital sidekicks. So whether you're wondering how to inject personality into your AI agents, especially when most customers out there will be saying they all sound the same. That's why we don't like these. Or if you're thinking about what is it you need to measure when your workflows are powered by machines that learn. Trust me, this episode is packed with many cracking insights.

[00:01:22] But enough from me. It's time for me to introduce you to my guest, Mary Hamilton. So thank you for joining me on the podcast today. Could you tell everyone listening a little about who you are and what you do? Hi, it's great. Great to be here. I am the global lead for Accenture's connected innovation centers. And so we have created a global standard for engaging experiences in our innovation centers around the world.

[00:01:49] I'm responsible for helping our clients do strategic visioning, design, co-creating, learning, connection with our ecosystem partners, and doing that through our physical platform in our innovation centers. Awesome. And not only that, before you came on the podcast, I was reading that the 2025 technology vision marks a milestone. 25 years of forecasting tech disruption. That's quite some average you've got going on there.

[00:02:16] But what makes this year's theme around AI powered autonomy particularly significant? If you look back throughout those 25 years, what makes this one so significant, would you say? Yeah, I mean, it is truly a milestone. And it's notable, right, that our technology vision has actually proven to be fairly reliable and, you know, an accurate predictor of what business and technology leaders need to think about and to be expecting in the future years to come.

[00:02:44] And how they should be preparing for that. We don't focus on, you know, individual one-off technology trends really, but it's the bigger, impactful technology trends. And so I do think we are absolutely at an inflection point of rapid acceleration. And it's really around how we're looking at AI and generative AI technologies, gaining more human-like capabilities. They're gaining intelligence. And that comes in a few different ways, right?

[00:03:12] In vision, in language, and in reasoning. And because of that, we're really approaching a moment of that technology becoming embedded everywhere, right? It's embedded into everything we're doing. And if you think about the overall theme that we've got for our tech vision this year, it really is about a declaration of autonomy. And that autonomy comes in a couple different forms.

[00:03:39] One, it's the autonomy of the agents themselves, right? And it's being able to act on its own behalf and to do things without much human intervention, right? So that's the technology side. But the flip side of it is that AI is also powering autonomy for people, right? For human beings. And it's giving access to the skills and capabilities that they wouldn't otherwise necessarily be able to have. And I can give you some examples of that.

[00:04:08] You know, if you think about a really sophisticated tool set like Adobe Photoshop, right? Yeah. It's a really detailed way, you know, to go in and edit and work through a photo. So I'm not an expert designer. I don't really know how to use all those tools in Photoshop. But now that they have launched their gender of AI platform on top of that with Firefly, I can go in and I can say, you know, I want to see a dog under a palm tree wearing a purple Accenture shirt.

[00:04:37] And suddenly I can become a designer. And it abstracts away those tools and it gives me the autonomy and capabilities that I've never had before. So I think seeing that proliferation of accessibility and AI becoming ever present, we're seeing instead of a drive towards artificial general intelligence, more drive towards the generalization of AI. And I think when it comes to AI, we've been on somewhat of a journey as individuals to begin with.

[00:05:05] Many feared it was just a human replacement. That was the first natural reaction to the change. Then people started to say, no, it's not that it is just a tool to empower the humans. But one of the biggest shifts highlighted in the report is AI is now evolving again from a tool to a partner. So how do you see this transforming enterprise technology development and day to day workflows for everybody listening? How do you see this journey continuing? Yeah.

[00:05:32] I mean, I think it goes back to that point I made about creating that autonomy and making things easier. And it really comes down to breaking the language barrier. That's the shift. That's the change that we're seeing here. That's allowing this specific technology to take on that partnership with humans, right? Because it can now do those more human-like capabilities like vision, language, and reasoning.

[00:05:55] And you combine that with the ability to actually have that conversation, to be able to interact in a natural way. And suddenly we're now looking at a tool that is taking on those human partnership capabilities. And so I think it's all, the future is going to be about how do we not worry about having our job taken over by AI, but it's how do we make sure that we are learning to partner with and use AI.

[00:06:23] That's where we're going to see the gains in productivity, the actual return on investment around putting this technology in place. And I think that continuous learning of how to work together is so important. And we've seen this in the past of technology systems failing because they weren't able to have that communication layer, right?

[00:06:42] You put in a robotic arm that flips hamburgers into a line in the kitchen and things actually break down, even though it's doing exactly what it's supposed to do, because there's not that cross-communication, that ability to work together. And when we see this shift today in how things are changing and how we're able to have those communication, that rational communication and insight, that's what's changing the game here.

[00:07:08] And unsurprisingly, I guess, trust emerges as another significant factor in the report. So people listening, how can their organization begin to systematically build and maintain that trust in AI as it becomes more autonomous, more embedded across their operations? Anything you can share around that? Because I think the culture and the trust within an organization, that's possibly even more important than the technology sometimes.

[00:07:34] Absolutely. And look, to realize the promise that of everything I just described about partnership, it really comes down to one critical factor, and that is trust. And we've done some research behind this. So our research finds that 77% of executives, the majority of executives agree that the true benefits of AI require a solid foundation of trust.

[00:07:58] And even more, 81% agree that a trust strategy must evolve alongside any technology strategy. So this is absolutely critical. And when we think about trust, we break it into two pieces. The first is around cognitive or rational trust. And the second is around emotional trust. And so there's a great analogy to, you know, thinking about your kids and how they grow up and how you build trust with them.

[00:08:25] And I've got a 10-year-old and I always talk to them about trust, right? And when he becomes a teenager and he wants to learn to drive, I'm going to have to have, you know, some emotional trust that, you know, I believe my child is going to try their best to be safe and responsible and do the right things.

[00:08:43] But it has to be complemented by cognitive trust that's going to develop over time as my kiddo develops and demonstrates competence, that he's learned the rules of the road, that he's making good choices, right? That he can handle unexpected things being thrown at him. And so if you apply that back to AI, right, the emotional trust is about, you know, trusting our leaders and organizations to get it right. Think about all those things, you know, that we think about from a responsible AI perspective.

[00:09:11] But then the cognitive side of it is really about trusting that these systems are going to give us the responses, the interactions that we expect, right? They're going to be built on the right kinds of data and building that trust in the small moments so that it can gain traction over time, right?

[00:09:31] And I think that's really what our enterprise leaders are going to have to think about is how do we build trust that these systems are going to be partners and they're going to help the workforce and also on the customer side, right? That they are creating the right identity and interactions that we expect and need to count on. And Accenture also talks about creating cognitive digital brains using multi-agent AI systems.

[00:10:00] And I'm conscious that some people listening outside of the tech industry might think that sounds almost like a Black Mirror episode. And one of the things I always try and do on this podcast every day is demystify technology. So just to clear up any confusion, can you just walk me through what cognitive digital brains means in more practical terms, everyday life terms, and how it will impact entire industries? Sure.

[00:10:24] You know, the cognitive digital brain is really about, you know, how do we create this backbone and the brain behind it? And to put it simply, if you think about previous technologies, they were very much instruction led, right? We had to program, we had to use programming languages. It's all bits and bytes. Sometimes there's some decision making criteria, which we predefine. AI is different by nature. It is not instruction led.

[00:10:52] It's intention driven, right? So that means that based on the data it's trained on, it's going to follow intentions, not direct instructions. And so that's really what the game changer is. And that's what we need to be architecting around when we think about how to build a digital brain for an organization as a platform. You know, and it can be, you know, connected brains, right? These brains don't need to operate in a silo.

[00:11:20] It's really about how we're connecting those brains to other human brains, to other, you know, other aspects of the ecosystem. So, you know, I really think there's a great example in how Accenture is starting to build out what we're calling the AI refinery. And it's really about creating that digital cognitive brain in multiple layers. So there's the data layer, right? And that could be structured or unstructured data.

[00:11:47] There's a layer around the models, right? How do we actually interact? And that's part of the intelligence layer. And then you have the action layer, right? What are the agents doing? How do we actually take action on those things? And all that's powered by the backbone of the digital core. So if you put all those pieces together, that's what makes up a digital cognitive brain, right? It's the data and information you've got.

[00:12:12] It's how you process the intelligence, how you take action, and how does that all come together into a system. And there's an old quote, the last best experience anyone has anywhere becomes the minimum expectation for that experience that they want everywhere. And over the past few years, we've seen one-click baskets at Amazon. We've seen the Netflix, Spotify-style experiences. More recently, we've seen those new expectations in how we search and receive information.

[00:12:40] Maybe some people listening are moving away from Google to AI. And, of course, if we look further down the line, the rise of personified AI experiences, they look inevitably to reshape how customers interact with brands. But what advice would you give to leaders looking to inject brand identity into AI-driven customer touchpoints? Because it's, I don't know, uncharted waters for many brands. They might be a little bit nervous about it. So any advice you would offer around that? Yeah, absolutely.

[00:13:09] When we think about brand, I mean, this is something that companies spend significant time on, invest, you know, sometimes billions of dollars on. And it's critical. And we have to make sure that if AI is becoming the front of that brand, that it reflects the brand values, the brand personality, and it is consistent across channels, right? And that it can address some of the personalization.

[00:13:35] But at the same time, there's a risk if you're not being thoughtful about these AI agents that are going out in the world on your behalf. If you're not being thoughtful about it, they all start to sound the same, right? If we're all using the same back-end AI-powered interactions, there's a risk, right? That they could all start to have the same kind of interaction, the same kind of back and forth with your customers that another brand is having.

[00:14:02] And so it's really critical that you think about how do you inject that personality, the knowledge of the business to avoid that risk of monotony and really building your face of the enterprise. And so when we think about things like chatbots, so we've got some great stats around this.

[00:14:22] The first is around 80% of executives have expressed concerns that chatbots that all sound the same are creating differentiating challenges for organizations. And the second is that 95% of executives, so almost all executives report that establishing or maintain a consistent personality will be important or very important to their customer-facing AI agents over the next three years.

[00:14:47] So companies are thinking about this, and they're really thinking about as search changes, right? As a customer start to interact through new channels, how are the embedded AI capabilities reflecting that brand consistently, but in a unique and personalized way? So many big stats there.

[00:15:10] Yeah, and also if we dig a little bit deeper on some of the things that were coming our way, we have general purpose robots that are quickly becoming specialists. So can you share how that shift might further influence things like logistics, manufacturing, or even the healthcare space for that man? Absolutely. You know, I love this. This is around, you know, AI agents getting their bodies, right? And what does that mean to navigate in a physical space?

[00:15:38] And we are seeing a significant shift in this area. As we see the evolution of robotics and gaining, you know, those robots gaining the visioning and the reasoning capabilities, we're starting to see a shift in risk around applying robotics to different business use cases. So if you think about historically where robotics have been used, they were very purpose fit. They were trained in a specific area.

[00:16:07] And if that didn't work out, then there was a loss, right, of using that application. In changes, we're starting to bring the cognitive capabilities to robotics where they can handle more dynamic situations, where they can communicate in different ways to the workers that are working with them. And even if you, you know, bring in the aspect of digital twins and how they navigate the 3D world,

[00:16:35] when you add those capabilities together, it starts to bring a flexibility to the robotics landscape that we've never seen before. And it allows companies to apply them in different ways. So, you know, one, reduce the risk. If that robot didn't work out in the original purpose, it can be repurposed, right? And also, you know, applying them, thinking about multipurpose from the start. And so the investment in robotics has shifted tremendously,

[00:17:00] especially thinking about some of the humanoid robotics that are gaining traction in the last couple years. And I'll give an example of where we've been working with some of our clients and partners. Shaffler is a great example. They're a leading motion technology company. And we're helping them look at how humanoid robots can perform various tasks that occur in warehouses.

[00:17:24] And they're looking at, you know, how do they create a platform where robotics and humans can come together seamlessly and the flow between the process and how that might work. We're also working with Kion, which is a leading supply chain solutions company. We're working with them alongside NVIDIA to create digital twins powered by physical AI. And again, it's that embodiment and, you know, working in these 3D physical spaces, it's creating these digital twins of its warehouses, right?

[00:17:54] And that's allowing facility operators to design the most efficient and safe warehouse configurations without interrupting operations for testing. So now that starts to optimize how you use robots and humans and the automated equipment altogether seamlessly. The report also talks about a virtuous loop between people and AI.

[00:18:17] So how should leaders listening approach skill building and mindset shifts to ensure AI adoption delivers that long-term organizational value? Because we can't just throw technology into the workplace and expect it to deliver everything that it can do. It needs that buy-in. It needs that culture change, right? Absolutely. And I'll say one thing about this technology, right? We are giving people not just a new technology, giving them a new learning technology.

[00:18:46] And that's really what's critical here if we think about the trust, because the technology doesn't matter if people are afraid to use it, right? And if they don't trust it. So as we think about applying this technology, helping our enterprise employees, helping consumers really understand the benefits that this technology can give them,

[00:19:11] but also helping to build trust in the more you use this technology, the more it learns, the better it adapts to the way you work, the way you like to interact. And the more we use the technology, we start to understand its capabilities better and become more advanced in how we're using it. So it becomes what we call a virtuous cycle of learning through this technology.

[00:19:35] And so I think, you know, if you really want to drive adoption around this stuff, it has to be, there's three areas that I would say you need to focus on. One is giving your employees time to actually experiment with AI, right? Allow that virtuous learning loop to happen. You know, allow people to experiment and explore what it can do for them. And also allow the technology to learn about the workforce and employees.

[00:20:02] The second is around don't use AI to take away the work that employees enjoy doing, right? It's about up-leveling people, letting them have access to the kinds of work, the creative work, the skilled work that they really prefer to do. And let the technology take care of the autonomy of things that, you know, especially in the robotics place, we call it the 3Ds, the dull, dirty, dangerous work that isn't well-suited for humans, right?

[00:20:30] And even apply that back to knowledge work as well. And then the third piece of advice is around making people part of the engine of change, right? So if they feel like change is happening to them, they may push back on it. But if they were part of that change and understanding how that virtuous cycle is happening, they're much more likely to adopt it. And the belts and braces mantra in business has always been you can't improve what you don't measure.

[00:20:59] So what would you say are some of the key signals or metrics business leaders should be watching this year? And especially to ensure that they're on the right track in turning AI autonomy into real-world impact. We saw a bit of a focus at the beginning of this year around the importance of ROI and how when a lot of businesses got caught in the hype, they kind of went into AI for maybe the wrong reasons. But we're seeing maturity now. That is changing. So any tips or advice on what they should measure?

[00:21:28] Yeah, I think you're exactly right. You know, we went from a place of experimenting with technology to now we're shifting into more scale. And as we move into that scale, it really is about making sure that you're getting that return on investment. And it goes back to, you know, there's a couple pieces of this. One is making sure that you've done all the transformation and, you know, got the right aspects of the cognitive digital brain in place, right? Your data is working. Your models are working. Your agents are working to help drive to that scale.

[00:21:58] But then it's also working on the business side to think about those levers of return, right? And those could be things like adoption rates. So how quickly are these solutions being adopted across the enterprise? Employee engagement. How well are people actually integrating AI into the work that they're doing? It could be, you know, if it's a consumer customer facing solution, what is customer satisfaction, right?

[00:22:26] How do you monitor customer feedback and satisfaction levels with AI driven interactions? It's thinking about, you know, the actual return on investment from budget, you know, cost savings, revenue growth, operational efficiencies, and really being able to put a fine nose lens on that to really understand where, you know, where are budgets being reduced because of this? Where are, you know, external third party contractors being reduced so that you can bring costs down from a cost saving standpoint? And where is it helping to grow revenue?

[00:22:55] And then the last metric I would say is also thinking about the ethical compliance, right? Ensuring that these AI systems are operating within the ethical guidelines that you've established and that there are not negative consequences, you know, as a result of the application. So, you know, I think it's absolutely key.

[00:23:15] If you think about those things, a lot of them are tied back to that aspect of trust and making sure that employees, customers are trusting or adopting or seeing value and giving positive feedback around the application and scale of AI. Wow. Wow. So many great points throughout that report. And I suspect that many people listening will want to dig a little bit deeper, look at some of the other stats and some of the insights from the report.

[00:23:43] For those people listening, where would you like to point them if they want to find out more information? Sure. Easy answer. Accenture.com slash tech vision, all one word. And, you know, I'm so excited about this. You know, I mentioned my role when we started here that I'm running our connected innovation centers. So much of this we're bringing into our centers and trying to bring to life and making it real for our clients that are sort of struggling to figure out what do we do with this.

[00:24:11] My goal is to take this tech vision that you've seen in the report and really uplevel it and help our clients understand how to work through it. So I'm super excited about this year's vision and I hope everyone goes out to Accenture.com slash tech vision and checks it out. And I would urge everyone listening to check that out because it feels like AI is increasingly acting as a technology development partner, a personal brand ambassador.

[00:24:34] And it's also going to be powering robotic bodies in the physical world and foster a new symbiotic relationship with people to bring out the best in each other. However, one of the big themes of the report, people's trust in AI. That is ultimately what it will dictate whether AI has a broad and positive impact as it's anticipated. Any business leaders should check that out. I would urge them do that. I'll put links to everything to make it easier. But just thank you for shining a light on this today, Mary. Really appreciate your time.

[00:25:04] Absolutely. Thanks for having me. So a big thank you to Mary for walking us through Accenture's Tech Vision 2025 report and painting a much clearer picture of the AI-powered enterprise of tomorrow. And the idea that AI will act with and on behalf of humans isn't just a future concept. It's unfolding right now. But Mary offered us a timely reminder there that autonomy without trust isn't progress. It's risk.

[00:25:33] It's the organizations that invest in responsible innovation, foster employee experimentation, prioritize consistent human-centered AI design. That is the standard that we need to be setting. But what do you think? Are we truly ready for AI as a business partner? Is your business ready for AI as a business partner, not just a productivity tool? Do you dare to think bigger than that? Love to hear your thoughts on this.

[00:26:00] Please email me techblogwriteroutlook.com, LinkedIn, Instagram, just at Neil C. Hughes. A lot to think about then. And I've got a few more episodes lined up coming your way. So send me a message if you've got any thoughts or any concerns or any questions or different vantage points that you'd like to add to this conversation. And if not, I'll be waiting in your podcast feed with another guest. Speak with you soon. Bye for now. Bye. Bye.

[00:26:34] Bye.