Technology changes fast, and it can be tough to keep up. The McKinsey Technology Trends Outlook 2025 tries to make sense of what’s coming next for businesses. If you want to know which trends are worth paying attention to, this report is a good place to start. Here’s what you should know if you’re making decisions for your company.
Key Takeaways
- The McKinsey Technology Trends Outlook 2025 highlights the biggest changes coming to business tech.
- AI, especially generative AI, is expected to change how work gets done and how products are created.
- Cloud and edge computing are making it easier for companies to handle data and respond quickly to customers.
- Cybersecurity is more important than ever, with new risks popping up as everything becomes more connected.
- Keeping up with these trends means training your team and tracking progress as technology changes.
Decoding the McKinsey Technology Trends Outlook 2025
The business world changes fast, and it isn’t always easy to keep up. Every year, McKinsey puts out its Technology Trends Outlook—kind of like a weather report, but for tech. The 2025 edition covers what leaders need to pay attention to right now, whether that’s advances in cloud computing or new questions about AI.
Key Themes Identified by McKinsey
McKinsey’s report pulls out recurring topics that keep coming up across industries. These aren’t just hype—they’re shifts shaping the way companies operate and compete.
- AI and machine learning are supercharging automation in places we wouldn’t have expected just a year ago.
- Shifts in IT infrastructure, like cloud and edge computing, are making it easier (and sometimes more complicated) to run business in real time.
- Security is no longer just a tech issue—it’s now baked into every conversation about digital growth.
- Newer fields, like sustainable tech, are starting to affect decisions in areas you might not expect, connecting trends in commercial space travel such as Virgin Galactic’s new spaceship.
Trend Selection Methodology
How does McKinsey pick its trends? Turns out, it’s not just a group of experts sitting around a table. Here’s how they do it:
- They track new patents, startup activity, and funding flows across over 40 tech-related topics.
- Quantitative data—like adoption rates—gets paired with expert interviews.
- Not everything makes the cut. Trends have to be measurable, have proven impact, and show signs of accelerating momentum.
Here’s a simple overview:
| Criteria | Description |
|---|---|
| Impact | Is it changing markets or business models? |
| Adoption | Are real companies actually using it? |
| Acceleration | Is growth speeding up, not slowing down? |
Importance for Business Decision Makers
Some people read these reports out of curiosity; for decision makers, it’s about picking paths in tricky territory. The trends highlighted in the 2025 report shape decisions on where to invest, what skills workers will need, and even which industries might struggle next.
A few reasons it matters:
- Tech trends can make or break long-term strategy—timing is everything.
- Early attention to security and sustainability avoids headaches later on.
- Understanding these shifts sets you up for less guesswork and fewer missteps down the road.
It’s not just about knowing what’s on the horizon; it’s about acting early and acting smart.
Artificial Intelligence as a Catalyst for Transformation
Artificial intelligence is moving faster than anyone expected and shaking things up for nearly every business. Companies are finding that AI brings both big wins and new headaches to their daily work. Here’s what’s really happening with AI now, according to the latest McKinsey Technology Trends Outlook for 2025.
Emergence of Advanced Generative AI
Generative AI isn’t just for chatbots or writing emails—lately, its abilities have exploded. Businesses now use AI to create images, write code, and even help with financial predictions. For example, finance teams are seeing benefits from AI-driven analytics and automation, which help them make decisions quicker and more accurately. Generative AI is picking up speed in:
- Generating creative content and marketing materials
- Assisting with software development and quality checks
- Speeding up financial forecasting and reporting
AI-Driven Automation and Productivity
Companies aren’t just testing AI—they’re putting it in charge of actual tasks. AI can now automate routine work, sort through complex documents, and respond instantly to client requests. This means jobs are changing. People spend more time on decisions AI can’t make, while the software covers the rest.
Here’s a simple breakdown of what companies see from AI-powered automation:
| Impact Area | AI’s Effect |
|---|---|
| Operations | Faster processes |
| Customer Service | Quicker replies |
| Data Analytics | Fewer errors, quick shifts |
Ethical and Regulatory Considerations
With all this new power comes fresh worries. AI doesn’t always get things right, and sometimes makes mistakes that can hurt people or lead to bad decisions. Companies now face huge questions:
- Making AI use clear and honest for everyone
- Following new rules from governments and regulators
- Avoiding bias in AI’s predictions or actions
Lots of business leaders are pushing for clear guidelines, and the pressure to "do the right thing" is growing. As AI spreads, everyone—tech teams, managers, and even customers—will need to pay attention to both its upsides and its limits. This is a moving target, and there’s no easy fix yet.
Cloud and Edge Computing Redefining Digital Infrastructure
For 2025, the landscape of IT infrastructure looks pretty different than it did just a few years ago. The way companies use cloud and edge computing is turning traditional systems upside down. Fast change means new ways of working, and there’s a lot to consider—all the way from cost to security.
Hybrid Cloud Strategies Gain Traction
Hybrid cloud isn’t just a buzzword anymore; it’s basically the new normal. In short, businesses are using a mix of public and private clouds to balance flexibility and control. It’s not just about storing files or backups—companies are running a mix of applications in different clouds and on local servers (on-premise), all at once.
Some reasons why hybrid cloud setups are growing:
- Freedom to choose where data and apps live
- Cut down on expensive hardware upgrades
- Handle sudden spikes in demand without slowing down
- Meet local data laws or privacy needs
A quick look at adoption rates:
| Year | Percentage of Enterprises Using Hybrid Cloud |
|---|---|
| 2022 | 45% |
| 2025 | 68% (projected) |
Edge Computing for Real-Time Insights
Edge computing pushes data processing closer to where things actually happen—like in factories, stores, or even cars—instead of sending all the data back to a central cloud. This means:
- Faster response times for mission-critical stuff
- Less network strain, as only useful info is sent to the main servers
- Feeds into IoT devices and smart sensors that need "instant" answers
A store could use edge computing to update prices and watch for shoplifting, all in real time without waiting on a slow connection. In health care, smart sensors at the patient’s bedside can alert staff to problems within seconds.
Implications for IT Security
Expanding cloud and edge systems isn’t without headaches for security teams. You’re not just protecting a few servers in one building anymore—you’re dealing with lots of devices, data sources, and connections everywhere.
Things to watch out for include:
- More entry points for hackers
- Keeping data safe while it moves across different networks
- Making sure updates and patches reach every device, even at the far edge
The big takeaway? Old-style security just doesn’t cut it anymore. Companies have to think differently about risk, constantly update their defenses, and stay alert to new kinds of threats coming from outside and inside their organizations.
The Evolution of Next-Generation Software Development
Rise of Low-Code and No-Code Platforms
There’s been a big wave of interest in low-code and no-code tools lately. These platforms let people without traditional coding backgrounds create apps and solutions much quicker than before.
Some points to keep in mind:
- Business teams can now build simple tools themselves, without waiting for IT.
- Speed: You get to test new software ideas faster, which means faster feedback and fewer headaches.
- Maintenance is easier, but there are some limits on what these platforms can do compared to hand-coded solutions.
DevOps and Agile at Scale
For teams working on lots of software projects, organizing the process better can save time and money. That’s where DevOps and Agile methods really shine, yet doing this at a big company takes some work.
Here’s what’s involved:
- Everyone needs to communicate more—no more "throwing code over the wall" to another team.
- Updates to software can roll out daily or even hourly.
- Mistakes get caught and fixed faster because testing happens all the time.
Companies using DevOps and Agile at scale see these benefits:
| Benefit | Usual Outcome |
|---|---|
| Faster releases | Up to 60% quicker |
| Fewer bugs at launch | 30% decrease |
| Happier teams | Better morale |
Software Quality in a Rapid Innovation Landscape
Innovating quickly is exciting, but it brings risks too. Rushing sometimes means mistakes slip through—nobody wants that. So, companies are changing how they think about building and testing code.
Ideas making an impact right now:
- Automated testing catches more errors before real users see them.
- Continuous updates let teams fix things as soon as they spot trouble.
- Real feedback from users gets baked into future releases instead of just once in a while.
Balancing speed with quality isn’t easy, but finding the right mix is worth it for everyone using the software.
Cybersecurity Priorities in a Digitally Connected World
The explosion of digital devices and the constant stream of information mean that cybersecurity isn’t just an IT issue—it affects everyone. As more aspects of our lives and businesses move online, the risk of cyber threats keeps growing. Staying on top of cybersecurity priorities is the only way for companies to protect themselves and their communities.
Integrating Security by Design
Building security into technology from day one has never been more important. Instead of treating it as an afterthought, companies now:
- Include cybersecurity features at the start of product development.
- Train teams across the business—not only IT—to spot and report threats.
- Regularly test defenses through realistic exercises to spot weaknesses.
A strong ‘security by design’ approach means fewer emergency fixes and less downtime if something goes wrong.
Managing Cyber Risks Across Ecosystems
Today’s businesses rely on connections—partners, suppliers, customers, and even smart devices in everyday things. These digital ecosystems can create weak points. Here’s what organizations do to lower the risk:
- Carefully check security practices of every partner and supplier.
- Map out all digital connections and data-sharing routes.
- Share threat information with trusted partners so everyone’s on guard.
New technologies, like those fueling the growing Internet of Things, make it even more important to understand and manage these risks.
The Role of AI in Threat Detection
Machine learning and artificial intelligence are changing the way we spot cyber threats. Instead of just waiting for alerts, companies can now:
- Spot strange patterns, like odd login times or unexpected data flows.
- React faster, since AI tools sift through thousands of signals at once.
- Adapt easily, learning from each new hack or weakness.
But it’s not out-of-the-box magic—AI security tools need to be set up, trained, and watched by people who know what to look for.
Here’s a quick comparison of traditional vs. AI-based threat detection:
| Feature | Traditional Detection | AI-Based Detection |
|---|---|---|
| Detection Speed | Minutes to Hours | Real-time or Seconds |
| Accuracy | Frequent False Alarms | Higher, Learns Over Time |
| Human Involvement | High | Lower, Needs Oversight |
Cybersecurity will keep changing as tech grows—so keeping up is not optional, it’s a must.
Emerging Technologies Shaping Industry Disruption
Quantum Computing on the Horizon
Quantum computing isn’t science fiction anymore; it’s already starting to impact research and industry strategies. Unlike classical computers, quantum machines can process massive calculations at speeds we haven’t seen before. Businesses are watching companies like IBM, Google, and startups in this area, with most breakthroughs coming from materials design and optimization problems.
What to expect soon:
- Cloud-based quantum services making experiments possible without huge in-house investments
- Increased focus on hiring quantum specialists
- Changes in cybersecurity planning because quantum could break some common encryption schemes
Impact of Advanced Connectivity
The rollout of 5G and even talk about 6G isn’t just hype—these faster networks are already changing how industries connect devices, collect data, and automate systems. For example, remote robotics and real-time equipment diagnostics rely heavily on advanced connectivity. As networks mature, edge devices can exchange information instantly, supporting everything from smart factories to self-driving vehicles. Stay updated with developments in latest technology news to see how swiftly these changes are moving.
Main outcomes include:
- More reliable connections for remote work and IoT
- Quicker rollout of new products in healthcare and manufacturing
- Expansion of services in places that were hard to reach with older networks
Sustainable Technology Initiatives
Sustainability is no longer a side project; it’s top of mind for tech leaders. More companies now track their environmental impact, shifting toward greener computing and responsible sourcing. Circular economy models—where old gadgets get refurbished or reused—are starting to get traction as well. Here’s what firms are focusing on right now:
| Initiative | Example Action | Business Benefit |
|---|---|---|
| Reducing Data Center Emissions | Use of renewable energy | Cost savings; better PR |
| Device Recycling and Reuse | Refurbishment programs | New revenue streams |
| Sustainable Supply Chains | Sourcing eco-friendly parts | Improved supplier relations |
So, the next time you’re hearing about quantum leaps or 5G rollouts, remember—these aren’t just buzzwords. They’re real shifts that might change how your business operates in the coming years. Keeping up with these trends can set you ahead, as long as you know where to look and what questions to ask.
Leveraging Insights from the McKinsey Technology Trends Outlook 2025
Staring at a list of technology trends can feel overwhelming. The McKinsey Technology Trends Outlook 2025 pulls together a huge amount of data and future-focused analysis, but what should companies actually do with these insights? Making the transition from research to action is where things get interesting.
Developing a Future-Ready Workforce
You can’t expect employees to transform overnight, but you can build up their skills over time. Investing in a workforce that’s prepared for tech changes is one of the most practical moves companies can make.
Here’s a straightforward approach:
- Identify which tech skills have the most impact for your business.
- Offer tailored training (think in-house bootcamps or external certification).
- Incentivize ongoing learning and curiosity.
If you’re looking for perspective, consider these three skill clusters that McKinsey highlighted:
| Skill Area | Current Demand | Projected Growth 2025 |
|---|---|---|
| Data Literacy | High | Higher |
| AI & Automation | Moderate | High |
| Cybersecurity | High | Very High |
For more on how businesses can use insights to spot relevant tech, check out these frontier technologies for their companies.
Aligning Strategy With Technology Innovations
You can’t just hop on a trendy technology and hope for the best. Matching your company’s game plan to tech innovations is about picking what actually works for you—and letting go of things that don’t. Here’s how companies are tackling this:
- Setting technology priorities based on expected value to business goals, not hype
- Building in plenty of room for experimenting and testing before scaling up
- Reviewing strategy with tech leads and business units together (no silos)
Metrics for Tracking Technology Adoption
Just rolling things out isn’t enough—you’ve got to keep tabs on what’s working (and what isn’t). Pick a couple of real numbers to track, not twenty. Some common picks include:
- Uptake rates for new digital tools or platforms
- Measurable productivity changes across teams
- Employee or customer satisfaction changes post-adoption
Making sense of these trends isn’t about being flashy—it’s about pulling out what matters. The companies that regularly review and act on these insights will probably stay a step ahead.
Wrapping Up: What’s Next for Businesses and Tech
So, after looking at McKinsey’s tech trends for 2025, it’s pretty clear that things are moving fast. Businesses can’t just sit back and hope things stay the same. Whether it’s AI, new ways of working, or changes in how we use data, there’s a lot to keep up with. It might feel a bit overwhelming, but taking small steps and staying curious can make a big difference. No one has all the answers, but paying attention to these trends now could help you avoid headaches later. In the end, it’s about being ready to try new things and not being afraid to change course if something isn’t working. That’s really what will help companies stay in the game as tech keeps changing.
Frequently Asked Questions
What is the McKinsey Technology Trends Outlook 2025?
The McKinsey Technology Trends Outlook 2025 is a report that looks at the most important technology changes likely to affect businesses in the near future. It highlights new tech trends and explains why they matter.
Why should companies care about these technology trends?
Companies should pay attention to these trends because they can change how businesses work, help them stay ahead of the competition, and make smarter choices for the future.
How is artificial intelligence changing businesses?
Artificial intelligence, or AI, is helping businesses by making work faster, automating simple tasks, and finding patterns in data that humans might miss. This can lead to better products and services.
What is the difference between cloud computing and edge computing?
Cloud computing stores and processes data in big data centers far away, while edge computing does this closer to where the data is made, like on your phone or a local device. Edge computing is good for things that need quick responses.
How can businesses keep their data safe with new technology?
Businesses can protect their data by using strong security tools, making sure security is part of every step when creating new technology, and training workers to spot risks.
What should companies do to prepare for these technology changes?
Companies should teach their workers new tech skills, update their plans to include new technologies, and keep track of how well they are using these new tools.
