Good morning. Oh, that's pretty cool. That's pretty cool. So every day we wake up with the challenge of bringing innovation to our organizations. And what's made it harder over the last 20 years is those waves of innovation come at us faster and faster every day.
So that made me think of an analogy that I would be using today for this presentation. We are all going to be surfers. We're going to decide what beaches we should surf at and what waves we should ride.
We're going to take a look at waves that are happening now, in one to three years, near, in three to five, and in the future, five years and beyond. But before I get started on that, I need to let you know how we got here today. How did we get to this list? Well, you've heard about the Gartner hype cycles and those innovation profiles on top of them, the little dots.
We have over 2,000 of them. We looked at the ones that are coming from the technology trigger to the peak of expected inflated expectations. Then we took a look and asked our analysts, over 2,500 of them, submit. So we had this huge list. We vetted it down and then had our chiefs of research vote on it.
Then finally, the team that worked with me to put together today's list came up with a list of technologies that we believe will shape the future with responsible innovation. The three beaches that we're going to look at today, the first one is AI risks and imperatives. Check, I had to say AI or else I don't get a bonus this year. right?
Two, new frontiers of computing. Oh my god, there is no more AI here. And then lastly, how things are changing between humans and machines.
Human-machine synergy. All of this so that we can be responsible, ethical, and trusted. So let's go to our first speech. Our first speech here is AI Imperatives and Risks, and I'm going to build on what you heard in the keynote around agentic AI. So we have this as really two to three years, but it's now in two to three years.
And I don't know about you, there isn't a day that I wake up where I don't have a list of a thousand things to do. And every night I go to bed worried about the things I didn't get done. And this is why we believe everybody needs an agent.
We need agents. Why? Well, what can they do for us?
The first thing is that agents are employees that never need benefits, they don't call in sick, they work 24 hours a day, and will do things for us that we often find mundane, or even more than that. They can do things with us or without us, because they have the ability to plan and sense and make decisions and monitor and much more. Also, they may make websites or applications unnecessary.
Now, I'm not saying this is the death of the website or the death of the application. But think about how many times people in your organization get onto a website to check something, then decide to do something based on what they saw. Same thing for an application.
We can have agents do those things for us. In fact, We believe that they're important because they can upskill your workforce. So you saw Mbula.
Mbula was able to become productive in less than six months and have the equal productivity of somebody with five years. But it can also enable new concepts of scale. So I want you to think of a list when you leave this presentation of things you would like agents to do for you in your organization.
and say, what if we actually created them? Lastly, they can create new co-workers. Now, I don't know about you, I've always wondered how Tony Stark could run a multi-billion dollar company and have time to be an Avenger.
He had Jarvis, multiple Jarvis's, Jarvis everywhere, Jarvis for you, Jarvis for everyone. So some of the things to watch for and do is that you're going to see your app. application providers starting to offer agentic AI in their applications. They may make big announcements, which you've had some this month, or they may just put it in there and you can start using it. Also, you'll need to know when this happens, it's a signal it's in your organization.
One of your developers walks up to you and says, hi, look what I created. Here's an agent that monitors all of our critical infrastructure, and it's going to manage it. while I'm on vacation. That's pretty scary. But this is that BYOAI scenario.
This can happen. You can have developers building agents right now and not be aware of them. Another thing to watch out for is that this is not the next generation of RPA.
This is not just stringing applications together through integration. Instead... We have the ability to make decisions and have action taken.
So when it comes to the next generation of shadow IT, it's agentic AI. And with that, how do we manage this new workforce? This brings us to our second trend, which also builds on things that you've heard in the keynote. And that's AI governance platforms.
And we believe this is happening in the next two to four years. So, we've already saw in the keynote cases of privacy being broken, discrimination could occur through bias, manipulation of markets, and many, many other things that can happen with AI. So, we need an AI governance platform that creates trust through transparency.
We need to know... what was the data used to train this model? What was the algorithm or approach used to train the model?
How did this prompt come up with the answer that it generated? Also, we need to have security and risk management, which is AI Trism. And then we're going to have guardian agents as part of this.
This is the evolving area of the AI governance platform. Also, it's going to ensure that it serves everyone equally. So this is where we're going to see technologies emerge that actually check for bias.
And you'll be able to do that as you're building your applications or agents. And then lastly, this is going to pave the way to build ethics into every AI that you have. So why is this important?
Well, we need to have ethics in everything we create. Because remember, we want to be responsible, ethical, and trusted. And that we want AIs to monitor and prevent anything bad so that we can have generally good outcomes. And of course we're doing this to protect our reputation. So some of the things to watch for is that you're going to see a surge in government regulations.
They continue to pop up everywhere. Every government is concerned about it and following those regulations will be important and you're going to need governance platforms to help you do that. Next, ethics is not going to be something that you just write down and say you do.
What do I mean by that? Ethics washing. So we're going to put out a policy that says we are doing these things to maintain ethicalness within our organization and we're governing our AI models and then have no tools to do it or prove it.
Also, your vendors, if they make those claims, you need to ensure that they can actually do what they're saying. Now. We're also going to have to pressure test all of our AI models to check for bias. Those governments'platforms'capabilities will help us do that so that we don't release any bias models.
Now, we believe that responsible AI will be as standard as cybersecurity and just as critical. You'll have to do this every day. On to our third trend.
Disinformation security happening in the next one to three years. Now, what is disinformation security? I just think of it as bad gossip.
It's misinformation. It's to be misleading. We saw this recently with the weather events here in Florida, where misleading information was propagated on the web through how people can get assistance after the hurricanes.
That's sad. That's sad. So disinformation security, right, what's made it worse is that AI has given the technical means.
that your phishing attacks are so good you can bypass the patrol controls and harm your enterprise. So imagine I am I now can generate a phishing attack that's so good you believe it's me and you let me in your organization. Now disinformation security is an emerging category of technologies. There are several of them right now such as looking for deep fakes but it's aimed at discerning trust, assessing the truth, and the spread of information knowing where it came from and where it's going.
Now within this trend, there's a Pandora's box and it's opened. Red team hackers now have the ability to create video, audio, and imagery that is so good it can bypass the biometric controls in your organization. and they can get into real-time communications.
So imagine this. You're on a conference call, you're in your meeting, you see each other, and you think you're actually talking to your colleague, and it's not them. Next, why is this important?
So because the phishing attacks have gotten so good with AI, it's easy to use that as the way in than using synthetic media. I can help spread false information inside your organization and outside your organization. So some of the things to watch for and do here with misinformation is deepfake identification tools looking for synthetic media. Those are ones that you should be looking at now. Also, impersonation prevention tools.
So imagine a watermark at the... underneath my video as I'm in that conference call that says, this is the real Gene Alvarez. We've authenticated that. And we're doing this so that we can protect our brand and reputation.
What's really interesting about this trend is for the first time, this is a team sport that involves the business and cybersecurity. Marketing may be detecting that the sentiment analysis is dropping on your organization. And they'll have to get together with the cybersecurity team to figure out where is it coming from? What's the source? Is it true?
And if not, how do we correct it? So we're leaving the beach of AI now. That's it.
We're leaving. Bye. And we're now going across town to another beach, new frontiers of computing. Now, the next one is a hard one for me to pronounce.
Post-quantum crypt. cryptography. Now, post-quantum cryptography, we believe, will be bigger than Y2K.
Now, please, I know that's a big claim. Please stick with me while I work this out. So, quantum computing can break every asymmetric encryption out there. Now, every application in your organization that reaches the web uses asymmetric encryption. You may have that encryption used in applications that you don't even know it's embedded in there.
So when all the locks are broken, we need new locks. Now, post-quantum computing is a set of algorithms that can resist attacks from both classical computers and from quantum computers. Another trend within this trend that's happening is the harvest now and decrypt later.
So I get into your organization through a phish, I'm in, and I gather up all the encrypted data I can, I store it on my side as a red team hacker, and I'm waiting for quantum to come along to be able to unencrypt it. So why is post-quantum cryptography important? Well, it's important because it's not a simple patch.
It's not as simple as you can run your patch management tools and everything gets updated. It's more than that. You need to also have an inventory of everywhere you're using encryption because all of it needs to be replaced and these things can impact the performance of applications that you have running right now and i don't know if there's anyone in this room that has actually budded for it in 2025. So some of the things you're going to have to do get an inventory where you're using encryption move to a crypto agile approach where you can up those applications and any other things that you use. asymmetric encryption, and then also too you're going to have to look at upgrading your hardware and most importantly budgeting.
So now let's go to ambient invisible intelligence. Remember when RFID promised we could track everything and then we saw the cost of the tags, right, and the actual performance of them and the batteries that they needed? Well, no more information in the shadows.
We are now seeing because of the low price and form factors of the new tags, such as the ability for it to charge itself using ambient radium frequency and paper thin, that you can tag anything and now get way after that information in the shadows, such as how many chairs are in this room, where did they come from, and where do they need to go to next. So this means we're going to be redefining large-scale tagging and tracking and intelligence. And in the long run, these tags could be built into everyday products, which can lead us to a world of smart everything. So this is going to be important for organizations that want that real-time inventory of millions of items. And this includes industries like retail, food production, warehousing.
For example, the sweater table. How many sweaters and what sizes are on it? We could just scan it and know.
Or ice cream. We need to know ice cream has maintained its temperature through the entire supply chain. But we have a nefarious truck driver who actually raises the temperature to save fuel.
That tag would catch that. We believe in the next five years that those tags will hit 10 cents. So some of the things you'll need to do is when the tags hit 20 cents, is start looking for those opportunities where you can use the tags.
for these type of real-time information in the shadow challenges. You'll also have to prepare your infrastructure for all of this messaging go through it, because the volume is going to be incredible. And then next, privacy concerns. Remember my ice cream?
How do we turn the tag off when Gene gets it at home and he doesn't want anyone to know how much ice cream he really eats? Right? And yes, I had some last night.
Energy efficient computing is our next one. Anyone here in the room, other than those who put in solar, have their electricity bill go down for themselves or their organization? I don't think so. I know mine hasn't. However, our demand for computing is through the roof.
Through the roof. And we need to do more computing with less energy. So that means that we have to find some energy efficient way Because right now the rise of computing power is so unsustainable for us, we can't catch up to it.
So we're going to see an increased demand because of big items such as AI, simulation, optimization, and media, and driving the growth of compute consumption and driving our energy footprint. We're also seeing that executives, regulators, partners, and our customers are putting us under pressure to reduce IT's carbon footprint. So why is this important? Well, incremental improvement is not going to be enough.
Yes, you need to do them, but it's not going to be enough. We need to find long-term solutions and innovative technology that's going to help us meet the demand for computing while reducing our carbon footprint. And of course, we are seeing new technologies emerging here.
So in the short term, you're going to adopt such things as green cloud, moving things to green cloud. You may actually rewrite algorithms. Remember when we used to write them to save space? Now we're going to write them to save energy. And we may be shifting the load of our compute to different times in the day.
So you're going to have to monitor some of the new technologies coming out and look at the ones that are offering 10x or 100x improvements for big ticket items such as AI. And you're going to pilot such new technology like optical computing, neomorphic computing, and other novel accelerators that are coming about to take on this energy challenge.