The technology story of 2026 has moved off the screen and into the physical world. Innovation is accelerating in the power grids and chips that underpin the data center boom; in the intelligent robots that embody AI; in the agentic systems discovering new chemical compounds; and in the launch pads sending thousands of satellites into orbit.
AI needs energy to scale. That’s one reason energy technologies alone drew nearly $200 billion in investment in 2025, among the highest capital influx in any technology domain. And spending on AI infrastructure doubled in a single year. These developments show that the defining questions today are not only about what technology can do. They are also about who can build the hardware and assemble the skilled workforce to deploy AI in the real world. At the same time, huge leaps were made in cybersecurity and software development—illustrating that AI is accelerating the digital frontier, too.
McKinsey’s Technology Trends Outlook 2026 examines 14 technology trends that define 2026, expanding our coverage from last year to include two new fast-emerging domains: agentic software development and AI for scientific discovery and engineering. For easier navigation, we group the trends into three broader categories: AI revolution, compute and connectivity frontiers, and cutting-edge engineering. The lines between these domains are blurring, and much of the innovation is happening in the gaps
Machines are being given more autonomy
AI has already transformed screen-based workflows—generating answers, drafting documents, and summarizing calls—and is rapidly advancing into an agentic era, in which it will complete many end-to-end digital tasks on its own. Agentic AI is becoming the connective tissue of the enterprise, with agents working alongside humans, changing not just tools but operating models. Physical AI is the next frontier. Making the jump to the real world, AI is adding perception, reasoning, and action across robotics, mobility, and wearables. General-purpose robots are being trained to learn about their environments so they can execute complex tasks and navigate unpredictable environments. Vehicles can make real-time decisions without drivers. Industrial systems can produce complex goods inside “dark factories” with no humans present. And immersive-reality headsets are interacting in real time with both wearers and the outside world. Physical AI is arriving first in manufacturing and logistics, where the economics are clearest. But the trajectory points well beyond the factory floor, toward hospitals, construction sites, farms, and city infrastructure.
Hardware and software are being codesigned for differentiated AI workloads
General-purpose chips have long powered everything from laptops to data centers. AI changed that. Training models and then running them at scale (what’s known as inference) demands something more specialized: chips optimized for specific workloads. Inference is overtaking training as the dominant AI workload. As model architectures continue to evolve, new application-specific chips are being designed to deliver inference on those models more efficiently, providing more output per watt at a lower cost. This is critical, as data centers’ energy demand is increasingly straining power grids. Hyperscalers are investing heavily to build data centers and have much to gain from faster, higher-performance chips. Thus, Amazon, Google, Meta, and Microsoft are increasingly partnering with semiconductor firms to codesign custom silicon tailored to their AI models—and some are exploring ways to offer these chips to outside customers as competitive products. (In the chip industry, the customer is becoming an alternative supplier.) But these new-format chips are not just affecting the semiconductor sector. They are changing how physical AI infrastructure is designed and transforming the business models of the equipment makers and energy suppliers that support these build-outs.
AI is hungry, and the grid is not ready
The race to deploy AI at scale has run headlong into a constraint that hyperscaler ingenuity cannot entirely solve: power. US data centers running AI workloads alone are projected to consume as much electricity by 2030 as California does today.3 Globally, the numbers are even larger. The problem is not just how much power AI needs but how hard it is to deliver. Data centers can be built faster than the transmission lines, substations, and transformers needed to power them can be supplied. Supply chain constraints are often to blame. In many markets, transformers now carry lead times of more than two years. More than 2,500 gigawatts of energy projects are stalled in grid queues worldwide, waiting for connections that may be years away.4 For enterprises, securing reliable compute power is becoming as much a competitive advantage as securing talent or capital.
When measuring talent demand, we see signals that some trends are maturing and selectively scaling. In connectivity, cybersecurity, energy, life sciences, and mobility, more than half of job listings were for non-R&D roles such as general and administrative, operations, and sales and marketing. While these trends are still driven by innovation, deployment is underway. Companies are now applying these technologies in use cases with commercial viability. Meanwhile, in all four AI-related trends plus application-specific semiconductors, over 75 percent of jobs posted were in the R&D category, illustrating just how early these sectors are, despite rapid growth in the past few years.
Play as a community builder and the rise of collectible ephemera
The rise of Labubu and Lulu, as well as the recent runaway commercial success of the Starbucks “bearista,” reflects a growing appetite for physical products that spark both instant delight and lasting connection. These objects are designed to surprise, to be shared and to be proudly displayed—bridging play, design and community. In 2026, the opportunity for brands will lie in treating physical goods not as commodities but as collectible moments—crafted for display, social currency and emotional resonance. By fusing playfulness, scarcity and aesthetic intent, brands can create physical hype pieces that build affinity, buzz and even secondary-market value. The same mechanics of play and exclusivity can deepen relationships—not just with consumers, but with partners, employees and clients who value being part of something rare and expressive.
The office renaissance has arrived
Although hybrid models of work still remain dominant since the pandemic, five years later we’re seeing a significant increase in formal return-to-office mandates and policies across corporate America. Coupled with the dynamics of a weakening job market, this shift means employers must double down on efforts to build the office experience as a strategic engine for boosting morale and retaining top talent. But the future workplace will move beyond superficial perks like free lunch and trendy chairs to become a true reflection of brand personality, highlighting the people and ideas shaping its success. Employees at these companies won’t just be forced to return; they’ll want to return to do their best work.
Other Emerging Technologies with Significant Impact
Quantum Computing: Quantum computing is transitioning from theoretical research to practical application. By 2026, technology leaders expect breakthroughs in cryptography, optimisation, and drug discovery. Gartner forecasts that early quantum advantage will be realised in sectors such as logistics and pharmaceuticals, where complex problem-solving is critical.
· Internet of Things (IoT) and Edge Computing: The proliferation of connected devices is accelerating, with billions of sensors and endpoints generating vast amounts of data. Edge computing is emerging as a solution to process information closer to the source, reducing latency and enhancing real-time decision-making. Forrester predicts that edge architectures will be integral to smart cities, autonomous vehicles, and industrial automation by 2026.
· Blockchain and Distributed Ledger Technologies: Blockchain is maturing from cryptocurrency applications to broader use cases such as supply chain transparency, digital identity, and contract management. IDC reports that enterprise blockchain adoption is set to grow by 30% annually, driven by demand for secure and tamper-proof transactions.
Analyst Predictions: Insights from Gartner, Forrester, IDC, and Everest
Industry analysts provide valuable foresight into the evolving technology landscape:
· Gartner: Emphasises the rise of composable business, where modular technologies enable rapid innovation and adaptability. Gartner predicts that by 2026, digital dexterity will be a critical differentiator for organisations, with AI and automation driving operational excellence.
· Forrester: Highlights the shift towards customer-centricity, supported by intelligent platforms and data-driven insights. Forrester suggests that successful enterprises will prioritise experience-led transformation, leveraging emerging technologies to deliver personalised services.
· IDC: Focuses on the growth of cloud-native applications, edge intelligence, and industry-specific digital platforms. IDC expects technology investments to be guided by sustainability, resilience, and regulatory compliance, with AI at the core of digital strategies.
FAQ’s
1. What are the biggest future trends to watch in 2026?
AI, automation, sustainable technology, digital transformation, cybersecurity, and changing consumer habits are major trends to watch.
2. Why are future trends important?
Future trends help businesses and individuals understand upcoming changes and prepare for new opportunities and challenges.
3. How is AI shaping the future in 2026?
AI is transforming areas such as business operations, content creation, customer service, healthcare, education, and technology.
4. What emerging technologies should businesses watch?
Businesses should monitor AI, robotics, advanced automation, cloud technology, cybersecurity, and other rapidly developing digital tools.
5. What are the biggest business opportunities for the future?
Opportunities are emerging around AI-powered services, digital products, sustainability, personalized experiences, and innovative technology solutions.