Transcription

Just seeing Darryl Plummer do this talk. We worked on it for a year. I know he's disappointed that he couldn't be here with you. You've got little old me instead. That being said, when we were titling this talk, the year everything changed. Does that feel like it's hyperbole? Does it feel like we're making an exaggeration? I don't know. I mean, there is a certain kind of part of our business model that is to scare the heck out of you guys so that you'll buy more Gartner licenses. I get that. That's fair. But as I think about it, I think in 20, 25 years when we look back, we are going to think that this is the year that everything changed. I don't think that's an exaggeration. And my part of this story actually starts last year. I was a part of the keynote team for Gartner Security and Risk Conference in National Harbor, DC, where we had AI, fighting AI on stage in this live red team, blue team scenario that was just fabulous. The production values were amazing. The number one piece of feedback we got from that audience, it was too futuristic. It's too futuristic. Fast forward to November of 2022, open AI, release chat GPT. And I don't know if any of us feel like that future's too futuristic anymore. I don't think it feels like science fiction. In fact, I think for a lot of us, it might feel like we're this skier. We're on this hill and generative AI is this slippery slope. And we're concerned, are we gonna unleash this slippery slope on the village down below who are our customers, who are our citizens, who are our employees? And for us, I'm not gonna sow a lot of fear, uncertainty, and doubt with you here today, even though I'm a practitioner in our cybersecurity research practice. I know CISOs, that's what we exist to do. But that's not what I'm here to do today. I'm here to help us plot a course down that hill. Because often the softest powder is through the trees, not on the well-worn runs. And it is through that path, perhaps that more difficult path, that less worn path, that we're gonna find a route to the bottom where everyone prospers. Our citizens, our employees, and our shareholders. Now thinking about prospering, when we develop this talk every year, and it takes about a year for us to do it, we get about 200 submissions for possible top predictions. So we thought to ourselves, maybe we could make our jobs easier. Maybe we could ask generative AI itself what it thinks the prediction should be. So we did. And here are two. By 2026, virtual and augmented reality will be used to create immersive learning and allow more realistic learning paths. Or, by 2026, 30% of workers will leverage digital charisma filters to achieve previously unattainable advances in their careers. Who thinks it's the first one? Who thinks generative AI generated the first one? Who thinks the second one is a generative AI? All right, that's pretty good, that's pretty good. I think they're both pretty nice, but if I was gonna do the reveal. I feel like the second one's got maybe a little bit more data, a little bit more actionability to it, perhaps. That's really what we go for when we're trying to develop these. Not that every prediction's gonna come true, not that every prediction is right. Gartner predictions are really about understanding trends and velocities, not about looking at a crystal ball trying to anticipate what the future is. So, without any further ado, I'm gonna throw the top 10 predicts up on the screen so that y'all can take pictures of it if you like, and we're gonna roll on with our story. Here's the first five. And the second five. We're gonna unfold our story today in three parts. Part one is about how generative AI is gonna make us all individually better. Part two is how it's gonna help our organizations, our businesses and enterprise overcome their worst traits. And part three is gonna be about threats and opportunities and responsibilities, but really about the ability to develop new communities. So, for our first part, generative AI making us more powerful personally and professionally. We're at an interesting inflection point right now. We're just coming out of COVID. We've got a lot of remote work going on, and for the first time in human history, there's a technology innovation that's going to benefit individual workers. Sure, technology's taken a lot of the drudge work out of the work that our workers do every day, but the people who typically profit from that are management or the enterprises themselves. But with generative AI, with remote work, we have the ability to let individuals profit from innovations and technology, free up time, become better at what they do, maybe even spend a little bit more time with their families. They can realize the value, and that's a really unique opportunity for us. Generative AI has the ability to help us write better. It has the ability to help us engage with our customers more intimately. It has the ability to make us more charismatic. By 20, this prediction comes to us from my dear friends Rita Salam and Whit Andrews. By 2026, AI will make us seem better than we are, that 30% of workers will leverage digital charisma filters to achieve previously unattainable advances in their careers. What's a charisma filter? You've been on Instagram, right? All right, well, that was super funny in my head, because I don't think anybody on Instagram or TikTok is anything other than filtered. And it's not just like blurry images of pretty people dancing in front of cute dogs. That's not what we're talking about. We're talking about the ability to increase your presence in the spoken word, increase your presence in the written word, increase your presence in your organization virtually. We're talking about, well, let me ask you. I think I'm a pretty charismatic dude in my native English. Would I get the same response, though, if this stage were in Japan, and you all were listening to me translated through a translator? No, I don't think so. But with charisma filters, that could become true. We're already seeing technology from organizations like NVIDIA, which will adjust your eye lines. You're always looking right down the barrel of the camera. That will skinny you up or make you look a little bit prettier. By way of research, I went out and got one of those cameras that'll make us look a lot skinnier and make us look a lot more attractive. It was unable to make any significant difference in my appearance, which I'm gonna go probably suggest that I'm probably just a little bit beyond any kind of real hope here. I don't know. Digital charisma filters are going to help us and our organizations achieve new sort of personal heights. It will help us achieve new levels of personal performance. It's also going to become an indicator of national performance. What do I mean by that? Well, let me ask you another question. Do you think Lichtenstein could ever rise to challenge China? China's great superpower has been people. There's 1.4 some odd billion Chinese and they have been amazing at leveraging talent over the past 60 or 70 years. This has genuinely been their national superpower is talent. Well, with AI, as long as you have enough GPUs and electricity, you have the ability to make unlimited amounts of talent. Unlimited amounts of talent. I don't know if that's gonna be true for Lichtenstein, but it could certainly become true for my home state of Texas. We could take all that place we tend to keep all of our cows, just cover it up in solar panels and GPUs and suddenly we've got an unlimited talent base that we can use. And I believe small states like Australia or what have you will be able to rise and become AI superpowers. This particular prediction comes to us from Julian Sun and Svetlana Sekular. By 2027, productivity value of AI will be recognized as a primary indicator of national power. We already use indicators of productivity, GDP, individual productivity, organizational productivity as a source of power. By making it a national benchmark, by making it something that we report on as nations, this will cause greater investment. It will speed this transformation into a world where we all prosper. Prediction number three. By 2027, 25% of Fortune 500 companies will actively recruit neurodiverse talent across conditions like autism, ADHD, dyslexia to improve business performance. Quick question if anybody out there, can anybody tell based on these pictures here who's neurodiverse? No, no, that's kind of part of the issue. By the way, just as an aside, I think every picture in this deck except for one was generated by generative AI. Your challenge is to go home and figure out which ones. But no, you can't tell who's neurodiverse just by looking at them. And I think this is an important part of the point is that really neurodiversity and cognitive diversity are superpowers for organizations. When you have cognitively diverse people, they see problems in different ways. They see opportunities in different ways and they will create different ways to engage with each other, to engage with customers, to engage with citizens, to engage with fellow employees, to unlock new sources of value. And to kind of put a little bit of a capstone on this point and speaking as somebody who's pretty profoundly neurodivergent myself and when referring to myself, I prefer the term neurodivergent. I don't know, maybe it's because I was a punk rocker and that sounds kind of hardcore or whatever. But as somebody who is very much neurodivergent themselves, I just wanted to say that I know that the whole idea of DEI has become somehow contentious, perhaps in the political sphere. Nothing I'm saying here today is about the political sphere. I don't wanna make this contentious. What I really wanna leave you with about DEI is this, that it is not about giving some group of people special privileges. It's not about shifting privilege around. It's about creating an environment where we can all take our masks off and be our authentic selves at work. And the value that that is going to unlock is tremendous. We know that there's certain forms of ADHD that just turn out great surgeons. We know that there's certain kinds of autism that enable people to become incredibly detail-oriented and those folks become great software control testers. If you heard Admiral McRaven talk about being a leader, being a significant part of being a leader is leveraging and maximizing the value of the talent that you have. And when we allow everyone to take those masks off and just be who they are, we unlock that for everyone. It is liberating and freeing for everyone. Story number two, the businesses will get better at overcoming their worst traits. As I was just saying about neurodiversity, we're not gonna focus on churning out cookie-cutter employees anymore with blue suits and red ties. We're gonna overcome those traits and generative AI is gonna help us do that. Prediction number four, we're gonna be able to overcome our worst traits Prediction number four, by 2026, half of G2 members will experience monthly electricity rationing, turning energy-aware operations into either a competitive advantage or a major failure risk. When I first heard the word rationing in this predict, my brain kind of exploded. I mean, when I think about rationing, right, I'm thinking like World War II, you can only have so much sugar, you can only bake one cake a month, like that's what I think when I think rationing. But I live in Texas, where we had a heat bubble over the state for three months and rolling blackouts. I have friends that live in Europe who've experienced electricity disruption as a result of the Russian invasion of Ukraine. This is real. This is real, and the real opportunity here is that we begin to think about as leaders the energy consumption inside of our organization as another resource. Why are Walmart and Target among the largest owners of solar panels in the world? Because when electricity generation costs become something that you actually measure on the balance sheet, optimizing that is a way to make money, to improve profitability, to improve the bottom line. And I want to say that generative AI is not going to be free. The amount of energy that it took to train chat GTP is just about a gigawatt, which is about the amount of electricity that 1,000 US households use in a day. The amount of energy that research indicates, they don't publish this information, but researchers into this have discovered or believe that chat GTP alone consumes 33,000 households of electricity a day. This is not going to be free. It is not going to be free. But we're talking about a value change here and a values change here. And I think that's something that's really important because when I think about the opportunity that generative AI presents to us, particularly in this realm, is the ability to really change the value equation. We've got to stop believing in the idea or the fallacy of unlimited growth on a planet of finite resources. That's not being political, that's nonsensical. The opportunity is in your hands because you are going to be the major consumers of electricity inside your organization. You're going to be some of the people who have to manage that risk for your enterprise. And I've never seen an obstacle that I can't manage to turn into an opportunity. So when we think about that, it is also an opportunity to win against competitors who haven't invested, who don't have the same ethos, who haven't thought about these problems. Now, I'm gonna ask you another question. If you had a genie in a lamp and could make one wish, what would that be for? I'm not expecting you all to yell it out in unison, but if I had to guess, if I could guess what I think you all are wishing for, it would be an end to technical debt, right? Just get rid of it, an end to technical debt. Oh my God, especially in civilizations, in societies that digitized early, right? I talked to many of you, you feel like you're suffocating under the weight of the technical debt, you're buried under it. Now, generative AI is not gonna make the technical debt problem go away, but it's gonna act as a Rosetta Stone. It's gonna become a translator. It's gonna give us the ability to extract the business logic. It's gonna give us the ability to extract the knowledge from these systems so that we can repurpose them, so that we can create new capabilities. It's gonna help us increase and modernize our applications faster. It's gonna reduce the replacement cost of these technologies, and if we do it really well, it will do, as a colleague of mine said in Australia just a few weeks ago, it'll prevent us from creating the next generation of legacy systems. It'll free us from that trap. Generative AI can become the Rosetta Stone. I remember when I was CTO of a bank, we were replacing our mortgage origination system. The three developers who managed our previous mortgage origination system, which was written in some ancient language called Primack, which I don't even know what that is, they all quit as soon as they knew that we were gonna do this, and they came back the next day as contractors doubling their salaries. That's a real threat. That's a real thing that happens, and with generative AI, we're gonna have the ability to extract that business knowledge. We're gonna have the ability to extract that information and make it far more portable. It may also help us avoid vendor lock-in. What I want us to think about here again is that generative AI used in the right way is gonna help us create better understanding, but just as I said back with the predicts, it's not gonna become the output. It's not gonna recode all of this for us because we are still bound by one very basic phenomena of computing. Garbage in. Garbage out. It's not gonna be the answers that ChatGTP or BARD or Copilot give us that are gonna become the value. What we really need to be focusing on instead is the value of the inputs, getting really good at understanding how to give the right kinds of prompts, how to give the right kinds of information to these systems and extracting all of the value from what we built already. Prediction number six comes to us from Dwight Klappich. By 2028, there will be more smart robots than frontline workers in manufacturing, retail and logistics, not to replace people, just to fill labor shortages. One of the other phenomena that happened as a result of COVID is people started taking gigs. They started working for themselves based on digital platform enablement. And as a consequence, there are a lot of jobs that are just not being filled by humans anymore and can't be filled by humans. If you look at countries like Japan who are on the verge of demographic collapse, they are not making enough new babies. Their population is inverted. The triangle is inverted. The only solution they're gonna have to that particular problem is robots. And I don't think that 2028 is too far out to start imagining a future for robots. Too far out to start imagining that robots might start outnumbering us in the workforce. I don't know if you've been to a grocery store lately, but it's kind of hard to find a checkout clerk, right? It's all self-checkout now. It's robots everywhere, whether it's my Roomba cleaning my floors or the new pool robot I got that's got a camera that scans for plankton or whatever. It's not plankton, it's a, you know what I mean. These robots are not just gonna be about replacing workers. It's gonna be about augmenting us, helping an aging workforce. It's gonna become a major factor in GDP. And that's not just in highly advanced supply chains, right? This is everywhere across our ecosystem. We need to think just like what the opening keynote said yesterday, we need to start thinking about generative AI as a new user interface. Whether that interface is at a terminal that I'm talking to or whether that interface is in a robot that's making my coffee for me. It's gonna become a new user interface. And with this new user interface, that also begins to speak to the need to begin to build better machine-to-machine interfaces. Prediction number seven comes from my dear friends, Mark Raschino and Don Scheibenreif, who you heard from yesterday, that through 2026, 30% of large companies will have a dedicated business unit or sales channels to access fast-growing machine customer markets. What's a machine customer? Well, I don't know, I got a printer at home that'll automatically reorder ink for me. Is that a machine customer? Oh, kinda, kinda, it will reorder the ink for me. Do I ever let it reorder ink for me? No, no, no I do not. Because it will always order it about six months before I need it. It will always order it from the ODM and it will always charge me retail plus, plus, plus for the convenience of automatically doing that. That is not what we're talking about when we talk about a full machine customer. We are talking, if this was a full machine customer, it would be out scouring to try and find the best deals for me on ink. It would understand my usage patterns and know that I really only print come event season because I like to print out my things so that I can read them backstage before I come out here and talk to you all. But the rest of the year, I don't print anything, ever. It would understand those consumption behaviors. And that's not just gonna be in B2B channels. It's not just gonna be in advanced supply chains. It's gonna be in B2C too. We already see those little, you know, you could buy this from someplace else kind of ads that pop up in some browser add-ins. I ask you another question. Does anybody here suffer from like massive gear acquisition syndrome? There are no golfers in the room, come on. I suffer from massive gear acquisition syndrome, I really do. For me, it's not golf, it's synthesizers, it's drum machines. I have got a drum machine addiction and we are not too far from the future where I can just sort of send a bot out there and say, hey man, when you find an LM drum for this price, go ahead and get it. If you find one for 20% less than that, get two. Just don't tell my wife. I swear to God, anytime she sees a box like this shape come into the house, she's like, that's a drum machine, that's a synthesizer. And she's probably not wrong, but at least in this future, I'll be able to point to the bot, I'll be able to say, hey, listen, the machine got me the best value I could ever get on this thing, honey. She'll still be rolling her eyes at the back of her head, but at least we'll know that we got a good deal on it, right? We need to get good at starting to understand, we need to start thinking about what a machine-to-machine customer model looks like. Do we know how to market to machines? Do we know how to advertise? Do we know how to advertise our capabilities? Do we know what kind of SLAs or operational level agreements machines are gonna want to agree to with each other? Do we have answers to those questions? No. But we need to start building them. Or else we're gonna miss out on one of the fastest growing channels in the world. The human channel only grows at about 4% a year. The machine channel is gonna grow at a factor of that, times 10, possibly even more. Possibly even more. The third part of our story is that new threats create new responsibilities and new communities. Prediction number eight comes to us from my brother from another mother, Dave Aaron and myself, that malinformation is gonna become a multi-front threat. By 2028, enterprise spend on battling malinformation will surpass 30 billion, cannibalizing 10% of markets and cybersecurity budgets to combat a multi-front threat. What is malinformation? Malinformation is algorithmically groomed and targeted disinformation or even the truth, which is out of context and designed to change mental models. What do we mean by changing mental models? That is causing you to make decisions that you would not make if you had the correct fact base. Today, malinformation is already a $78 billion threat and that's just people-to-people malinformation. That's just dealing with activists and other malinformation and disinformation that exists out there. If you wanna know the ball that I had my eye on, it's AI-based malinformation. It's malinformation that is designed to do prompt spiking. That is not prompt injection. That is causing your AI to have a hallucination or causing it to ingest data that causes it to hallucinate, spiking the prompt. And that has the potential to grow to enormous sums. It will also create new opportunities for our CISOs. By 2027, 45% of CISO remits will expand beyond cybersecurity due to increasing regulatory pressure and attack surface expansion. This comes to us from my dear friend, Andrew Walls. Today, you guys have been great at digitizing. You guys have been amazing at creating the digital future. And for the past 13 or 14 years, I've been in CIO or CEO research. I moved to CISO research about 18 months ago because all of the amazing digital transformation opportunities that I have talked about from this very stage don't become real if we don't get the cyber right. And today, every business process is bounded by cyber. It's limited by cyber. Even the most manual thing you could do, getting an oil change in your car, you can't do it. If the work order system doesn't print the work ticket, if they can't collect the credit card on the other end, and oh, by the way, if they can't tell my car, which is a network of supercomputers rolling on wheels, that it has had an oil change, none of that process works if the cyber doesn't work. In addition, we have the SEC, which has said recently that there must be an officer in charge in the enterprise of cybersecurity. As a consequence, we see the role of the CISO evolving into one, into full, holistic, broad-spectrum digital business defense to include cybersecurity, to include privacy, to include even possibly physical security. Prediction number 10. Unions of people will form to combat machines. We've seen the writers strike in Hollywood. We've seen the actors strike in Hollywood. We know that our employees are feeling the pressure, they're feeling uncertain, they're feeling concerned about their future and generative AI and what that means to them. This prediction comes from my teammate Nader Hainan, Helen Plonfen and Helen. And really, I think what we're seeing here is a reaction to that. That we're experiencing anxiety around layoffs. We've seen lying flat. We've seen quiet quitting. And yeah, sure, maybe the tech layoffs shook stuff up so we got people back to the office a little bit more often. We've maybe improved productivity with a little bit of fear, uncertainty and doubt. But that's not going to be the answer. That's not going to be the answer. I think the answer lays again in what the opening keynote talked about. It lays in everyday AI. It lay in allowing your employees to bring the AI to work, allowing them to experiment with it, allowing them to reap the value that they get from AI in the terms of time savings and the ability to do better or more interesting things. And in closing here, I just wanted to say one thing to you, bringing us all the way back to the beginning. I don't think the year that everything changed is hyperbole. In fact, I want to double down on that. And I wanted to say that I'm imploring you to take the decisions that you make today and into the future about generative AI very, very seriously because we are literally the last generation of managers who will get to make those decisions. We are making decisions about buying, acquiring and building decision-making machines. And after those decisions are made, that will become a one-way door, which will become very, very difficult to reverse after we've made those decisions. So do we decide that our strategy is simply to continue to allow wealth to aggregate or do we decide to empower employees, empower our citizens and empower our coworkers with this amazing new technology? And if we make the right decision, folks, the future's ours. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.