Thinking about what’s next in tech for 2025? It feels like every day there’s a new buzzword, but some things are really shaping up to be important. We’ve looked at what experts are saying about the top strategic technology trends for 2025, and it’s a mixed bag of smart systems, better security, and more efficient ways of doing things. It’s a lot to keep up with, but understanding these shifts can really help businesses stay ahead of the game. Let’s break down what you need to know.
Key Takeaways
- Agentic AI, systems that can make decisions and act on their own, is set to become much more common, handling many daily work decisions by 2028.
- AI Governance Platforms are becoming vital for managing AI’s ethical and security risks, with companies using them likely to see fewer AI-related problems.
- Disinformation Security is a growing concern, especially with AI potentially being used to create more convincing scams and fake content.
- Hybrid computing, which combines different types of computing resources, will help power complex tasks like AI, going beyond current limits.
- Energy-efficient computing is gaining importance as compute-heavy tasks like AI training consume significant energy, making greener solutions a priority.
1. Agentic AI
So, agentic AI. It’s basically AI that can actually do things on its own, without you having to hold its hand every step of the way. Think of it like having a really smart assistant who doesn’t just answer questions but can also figure out what needs to be done and then go do it. This isn’t just some far-off idea; it’s already starting to show up in how businesses operate. Leading manufacturers and logistics companies, for example, are using this tech to get better results in their day-to-day work. It’s pretty wild to think about, but by 2028, Gartner predicts that a good chunk of our daily work decisions could be handled by these AI agents. That’s a big jump from where we are now.
These agents are showing up in all sorts of places – built into software, running on devices, and even powering robots. They’re designed to be goal-oriented, meaning they can tackle a variety of tasks and adapt as they go. The big promise here is a kind of virtual workforce that can take on tasks, freeing up people to focus on other things. It’s all about making systems smarter and more capable of handling complex jobs. For businesses, this could mean a serious boost in how much work gets done.
Here’s a quick look at what agentic AI can do:
- Task Automation: Handles routine and complex tasks from start to finish.
- Goal Achievement: Works independently to meet defined objectives.
- Data Analysis: Processes large amounts of information to make informed decisions.
- System Interaction: Can manage and operate across different software and hardware platforms.
It’s a big shift from the AI we’ve seen before, moving from just answering prompts to actively managing processes. This kind of autonomous capability is what’s really going to change how we work with technology in the coming years. It’s not just about having smarter tools; it’s about having tools that can act on our behalf.
2. AI Governance Platforms
So, AI is getting pretty powerful, right? And with that power comes a need for some serious oversight. That’s where AI Governance Platforms come in. Think of them as the rule-makers and rule-enforcers for all your AI systems. They help make sure the AI you’re using is playing by the book, ethically speaking, and not causing any unintended problems.
These platforms are designed to manage the legal, ethical, and operational performance of AI, making sure it’s used responsibly. It’s not just about having AI; it’s about having AI that you can trust. They help explain how AI models make decisions, which is super important for building confidence and knowing who’s accountable if something goes sideways.
Basically, these systems help you:
- Create and enforce policies for how AI should behave.
- Keep track of AI’s performance, looking at things like fairness and accuracy.
- Provide transparency so you know what the AI is doing and why.
It’s predicted that companies using these platforms will see a significant drop in AI-related ethical slip-ups. So, if you’re serious about AI, getting a handle on governance isn’t just a good idea, it’s becoming a necessity.
3. Disinformation Security
It feels like every day there’s a new way someone’s trying to trick us online, and it’s only getting more complicated. Disinformation security is all about building defenses against that. Think of it as the digital equivalent of fact-checking, but on a massive scale, trying to stop fake stuff from spreading and messing with businesses or people.
The main goal here is to make sure information is real and hasn’t been tampered with. This is becoming a bigger deal because AI tools are making it easier to create convincing fake content, like deepfakes or fake news articles, that can really damage a company’s reputation or trick employees into giving up sensitive data. We’re seeing a big jump in how many companies are looking for ways to deal with this. Gartner predicts that by 2028, about half of all businesses will be using specific tools to fight disinformation, which is a huge increase from just a few years ago.
Here’s what’s involved in keeping things secure:
- Spotting fake content: This means using technology to figure out if videos, audio, or text have been faked or altered.
- Tracking the spread: When bad information does get out, it’s important to know where it’s coming from and how it’s moving around so you can stop it.
- Protecting against impersonation: Bad actors often pretend to be someone they’re not, like a boss or a trusted partner, to get people to do things they shouldn’t. Disinformation security helps prevent this.
Email is still a major way these attacks happen, so having good email security systems that can spot phishing attempts and other tricks is super important. It’s not just about stopping viruses anymore; it’s about stopping lies that can cause real harm. We need to get better at verifying information and making sure our digital communications are safe, especially as new technologies emerge. Protecting against things like business email compromise is a big part of this cybercrime threat landscape.
4. Multi-Agent AI Systems
You know, it feels like just yesterday we were talking about AI as this single, smart thing. Now, the conversation is shifting big time to multi-agent AI systems. Basically, instead of one AI trying to do everything, you have a bunch of smaller, specialized AI agents working together. Think of it like a team of experts, each with their own job, all coordinating to solve a bigger problem. This approach is really changing how businesses tackle complex issues, helping them break down old barriers and make smarter choices faster.
We’re seeing these systems pop up across different industries. For example, in customer service, you might have one agent handling initial queries, another pulling up customer history, and a third suggesting solutions. This teamwork allows for much more nuanced and efficient interactions. The real power comes from these agents communicating and collaborating, leading to outcomes that a single AI simply couldn’t achieve.
Here’s a look at how they’re making a difference:
- Improved Problem-Solving: By dividing complex tasks among specialized agents, systems can tackle problems that are too big or intricate for a single AI. Each agent focuses on its area of strength, contributing to a more robust overall solution.
- Enhanced Efficiency: Agents can operate in parallel, speeding up processes significantly. This parallel processing means tasks that used to take hours might now take minutes.
- Greater Adaptability: As situations change, different agents can be deployed or their roles adjusted, making the overall system more flexible and responsive to new information or requirements.
It’s a pretty exciting development, and it’s going to be interesting to see how companies continue to integrate these collaborative AI teams into their operations. It’s a big step forward from the simpler AI applications we’ve seen before, and it really opens up new possibilities for automation and decision-making. We’re starting to see this trend impact everything from software development to managing complex supply chains, showing just how versatile these multi-agent setups can be. It’s a fascinating area to watch as it matures, and it’s definitely shaping the future of how we work with artificial intelligence. You can find more on how AI is changing the world in areas like autonomous vehicles right here.
5. Democratization of AI
It feels like everywhere you look, AI is being talked about, and for good reason. It’s not just for the big tech companies anymore. We’re seeing AI tools become much more accessible, which is a pretty big deal. Think about it – things that used to require specialized knowledge or expensive software are now available to a lot more people.
This shift means that smaller businesses, individual developers, and even hobbyists can start using powerful AI capabilities. We’re seeing this happen through things like open-source AI models and platforms that are easier to use. It’s like the technology is finally catching up to the idea that more people should be able to benefit from it.
What does this mean in practice?
- More people can build AI-powered applications: You don’t need a massive team or a huge budget to get started.
- Innovation can come from anywhere: When more people have access, you get more diverse ideas and solutions.
- Existing jobs might change: Tasks that were once manual could be automated, freeing up people for other work.
This trend is really about spreading the power of AI beyond the usual suspects. It’s about making it a tool that a wider range of people can use to solve problems and create new things. It’s a pretty exciting time to see how this plays out.
6. Hybrid Computing
Hybrid computing is basically about mixing different types of computing power to get the best results for tough jobs. Think of it as combining the strengths of regular processors (CPUs), graphics cards (GPUs), specialized chips, and even newer tech like edge and quantum computing. This blend is what allows us to tackle really complex problems, like crunching massive amounts of data or training advanced AI models, in ways that weren’t possible before.
This approach is becoming a go-to strategy for businesses looking to push the boundaries of what their technology can do. It’s not just about having more power; it’s about using the right kind of power for the right task. For instance, AI training might benefit from GPUs, while certain data analytics could run better on specialized hardware. This flexibility is key to innovation in today’s fast-moving tech world.
However, this interconnected setup isn’t without its challenges. When you link up all these different computing resources, you create more potential entry points for security threats. Keeping sensitive company information safe, especially when data is moving between these various systems, becomes a big deal. It means making sure every part of your hybrid setup is secure, from the cloud to the edge devices. Protecting against things like business email compromise is just one piece of the puzzle. It’s a complex environment, and keeping it all safe requires careful planning and ongoing attention to security measures. You can find more information on how the global technology landscape is changing due to these innovations at evolving technology landscape.
Here are a few things to keep in mind with hybrid computing:
- Integration Complexity: Making different computing systems work together smoothly can be tricky. Each component might have its own way of doing things, and getting them to communicate effectively takes effort.
- Security Management: As mentioned, managing security across a diverse set of computing resources is a significant task. You need a unified approach to protect everything.
- Performance Optimization: While the goal is better performance, it requires careful tuning to ensure you’re actually getting the most out of the combined systems. It’s not always plug-and-play.
- Cost Considerations: Implementing and maintaining a hybrid computing environment can involve significant investment in hardware, software, and skilled personnel.
7. Energy-Efficient Computing
It feels like everywhere you look these days, people are talking about sustainability and cutting down on waste. Turns out, the world of technology is no different. Energy-efficient computing, or green computing as some call it, is really starting to get some serious attention. It’s all about trying to lower the carbon footprint that comes with all our digital stuff, especially those really demanding tasks like training AI models or rendering complex graphics. These processes gobble up a lot of power, and companies are starting to notice the impact on their environmental goals.
So, what are people actually doing about it? Well, there are a few ways to tackle this. Some are looking at the simpler stuff, like making sure they’re using power from renewable sources or switching to hardware that just uses less electricity. Others are digging deeper, thinking about how the software itself runs. This means looking at application design, the actual code, and the algorithms used – basically, finding ways to make them run with less energy. It’s a bit like trying to make your car more fuel-efficient, but for computers.
Looking ahead, things are expected to get even more interesting. We’re talking about new types of computing platforms that are still mostly in the research phase right now. Think optical or neuromorphic computing, which are designed for specific jobs and should use way less energy than what we have today. These could really change the game for tasks like AI and optimization. It’s a big shift, and getting these new systems ready and secure will be a whole project in itself. The push for greener tech is definitely a major part of the tech landscape now, and it’s only going to grow as we think more about our planet’s health.
8. Low-Code Application Platforms
It feels like everywhere you look these days, people are talking about how hard it is to find good developers. Seriously, the numbers are pretty wild, with predictions of millions of unfilled tech jobs just around the corner. This whole situation is pushing companies to really look at tools that can help speed things up, and that’s where low-code application platforms, or LCAPs, come in.
These platforms are changing the game by letting more people build software without needing to be coding wizards. Think of them as toolkits with pre-built pieces and visual ways to put things together. Instead of writing thousands of lines of code from scratch, developers can use these platforms to skip a lot of the tedious work. This means apps get built faster, which is a big deal when you’re trying to keep up with the competition.
It’s not just for the pros, either. A growing number of people who aren’t traditional developers, sometimes called "citizen developers," are now building their own applications. Gartner even thinks that in big companies, there will soon be way more of these citizen developers than actual software developers. It’s pretty neat how these tools are opening up software creation to more people.
We’re seeing a huge jump in how much these platforms are being used. The market for low-code solutions was expected to hit billions in 2023, showing a big jump from the year before. Companies like Mendix, which was recognized as a leader in this space, are being used by thousands of businesses worldwide. It’s clear that with the ongoing need for faster development and the increasing accessibility of these tools, LCAPs are going to keep growing and shaping how software gets made. If you’re interested in the broader tech landscape, you might want to check out some of the latest tech news.
9. Quantum Computing
Quantum computing. It sounds like something straight out of science fiction, right? For years, it’s been this big, theoretical thing. But guess what? We’re actually getting close to seeing it do real stuff. Traditional computers use bits, which are either a 0 or a 1. Quantum computers use qubits, and these can be both 0 and 1 at the same time. This might not sound like much, but it means quantum computers can do calculations way, way faster than anything we have now. We’re talking about problems that would take today’s best computers millions of years being solved in minutes.
It hasn’t been an easy road, though. There have been a lot of technical and money problems. But things are picking up. Last year alone, startups in this area got about $1.7 billion in investments. IBM seems to be leading the pack with its quantum computers, like Osprey, which has 433 qubits. They’re aiming for a 4,000-qubit machine by 2025, though some experts think we’ll need millions of qubits for them to be truly powerful, maybe by 2027. Other companies like Alphabet (with its Sandbox AQ spin-off) and even smaller ones in China and Australia are also making big moves and getting significant funding.
So, why should we care? Well, the potential impact is huge. Think about it:
- Life Sciences: Simulating complex chemical reactions for drug discovery, designing better medicines, and personalizing treatments based on your genes.
- Finance: Spotting market risks much faster, catching fraud more effectively, and speeding up how new customers get set up.
- Everyday Life: Imagine charging your electric car in just three minutes, or even seconds at a special station. That’s the kind of change we’re talking about.
The biggest challenge right now is making these systems stable and error-free. Companies are working on software to help manage this. Another big concern is security. As quantum computers get better, they could break the encryption that protects most of our online data today. This means we need to start thinking about and moving to new types of encryption, called post-quantum cryptography, sooner rather than later. It’s a big job, maybe even bigger than the Y2K scare, and many companies haven’t even started planning for it yet.
10. Cybersecurity
Cybersecurity is getting more complicated, and honestly, it feels like a constant game of catch-up. With all these new tech trends popping up, like AI and hybrid computing, the ways attackers can get in are changing too. It’s not just about firewalls anymore.
One big thing is how AI is being used by both good guys and bad guys. While AI can help spot threats faster, bad actors are using it to make scams, like fake emails (BEC attacks), way more convincing. We need to get smarter about spotting these AI-powered tricks. Think about it: if a scam email looks exactly like it came from your boss, and it’s got all the right details, it’s easy to fall for.
Here’s a quick look at some key areas:
- Disinformation Security: This is all about making sure the information we see and use is real. Bad actors spread fake news and use it to trick people into giving up sensitive info. By 2028, Gartner thinks half of all companies will be using tools specifically to fight this kind of fake info, which is a huge jump from today.
- Post-Quantum Cryptography: This sounds super technical, but it’s important. Right now, our online security relies on codes that future, super-powerful quantum computers could break. We need to start switching to new types of codes that even quantum computers can’t crack. This is a massive undertaking, way bigger than the Y2K scare, and companies need to start planning now.
- Multi-Factor Authentication (MFA): This is one of the simpler, but really effective, steps. It means you need more than just a password to log in, like a code sent to your phone. It makes it much harder for someone who steals your password to get into your accounts.
It’s clear that staying secure means keeping up with these changes. We can’t just set and forget our security measures anymore. It requires constant attention and adapting to new threats as they appear.
Wrapping It Up: What’s Next for Tech in 2025
So, we’ve looked at a bunch of tech trends that are set to make waves in 2025. From AI getting smarter with multiple agents working together to making sure our digital stuff is secure, it’s clear things aren’t slowing down. Companies are really leaning into AI, but they also need to keep their basic tech systems strong and secure. It’s a lot to keep up with, for sure. But by understanding these shifts, businesses can get ready for what’s coming and maybe even get ahead of the game. It’s going to be an interesting year for technology, that’s for sure.
Frequently Asked Questions
What is Agentic AI and why is it important for 2025?
Agentic AI refers to smart computer programs that can do tasks and reach goals on their own using AI. By 2028, it’s expected that these AI helpers will handle about 15% of daily work decisions, which is a big jump from almost none today. This means AI will become more like a virtual helper, taking on more jobs and making businesses more efficient.
How do AI Governance Platforms help businesses?
AI Governance Platforms are like rulebooks for AI. They make sure AI is used in a way that’s fair, legal, and works correctly. These platforms help companies keep track of AI’s actions, especially in security, and follow important guidelines to avoid problems and make sure AI is used responsibly.
What is Disinformation Security and how does it relate to cybersecurity?
Disinformation Security is all about protecting information from being twisted or faked. In cybersecurity, this means stopping bad actors from pretending to be someone else, spreading false information, or tricking people through emails (like phishing scams). It’s important to have strong security to keep information truthful and safe from these attacks.
What are Multi-Agent AI Systems and why are they becoming popular?
Instead of just one AI program doing a job, Multi-Agent AI Systems involve several AI programs working together. This helps businesses tackle complex problems by breaking them down, making smarter choices, and finding new ways to make money. It’s like having a team of AI experts collaborating.
What does the ‘Democratization of AI’ mean for everyday people and businesses?
The ‘Democratization of AI’ means that AI is becoming easier for everyone to use, not just big tech companies. With more affordable and simpler AI tools available, like those that can be used without needing to be a coding expert, more people and smaller businesses can now use AI to help them.
Why is Energy-Efficient Computing a growing trend in 2025?
As AI and other powerful computer tasks use a lot of energy, companies are focusing on making computing more energy-efficient. This is important for the environment because it helps reduce the carbon footprint. Finding ways to use less power for these demanding jobs is becoming a key goal for the tech industry.
