Future of Technology: Key Tech Trends Shaping What Comes Next

The future of technology is being shaped by one force above all: artificial intelligence. It is changing software, chips, energy use, robots and security at the same time. But the biggest story of 2026 is not AI alone. McKinsey says the technology story of 2026 has moved off the screen and into the physical world: power grids, chips, robots, cars and networks.

That shift brings real limits. AI needs enormous amounts of electricity, most companies are still struggling to turn AI use into profit, and some hyped technologies, such as humanoid robots and 6G, are further away than the headlines suggest.

This guide covers the key tech trends for the next few years, what is already real, what is still early, and how to prepare. It draws on Gartner, McKinsey, the International Energy Agency (IEA) and Ericsson, and it separates reported facts from forecasts.

Key tech trends at a glance

The table shows where each major trend stands in 2026 and the next milestone analysts point to.

Trend	Where it stands in 2026	Next milestone
Agentic AI	Nearly 9 in 10 organizations use AI; 40% of large and 22% of smaller ones are scaling AI agents	Gartner: by 2030, 80% of organizations move to smaller, AI-augmented software teams
AI chips and infrastructure	AI infrastructure spending doubled in one year; inference is overtaking training	Gartner: over 40% of leading enterprises on hybrid computing by 2028
Data centre power	Data centre electricity demand rose 17% in 2025, against 3% for all electricity	IEA: data centre demand doubles and AI demand triples by 2030
Quantum computing	Record of 96 logical qubits reported in January 2026	Fault-tolerant machines still years away; IBM targets 200 logical qubits by 2029
6G	Specifications are being drafted	First commercial 6G systems expected in 2030 (Ericsson)
Electric vehicles	Over 20 million sold in 2025, about a quarter of new cars	IEA forecasts 23 million in 2026, close to 30% of sales
Robotics	Humanoid robots mostly in pilots	Gartner: fewer than 20 companies run humanoids in live production by 2028
Security	More than 75% of vulnerabilities were zero-days	Gartner: half of security spending goes to preemptive tools by 2030

Sources for each row are named in the sections below.

AI moves from chatbots to agents

AI is no longer experimental, but turning it into profit is still hard. McKinsey’s State of AI survey (1,719 respondents in 97 countries, May to June 2026) found that nearly nine in ten organizations use AI in at least one business function. About 44% are scaling AI across the enterprise, up from 38% a year earlier. Only 37% say AI has added anything to their earnings (EBIT), essentially unchanged from 2025.

The next step is agentic AI: systems that plan and carry out several steps of a task on their own, instead of only answering questions. 40% of respondents at large organizations and 22% at smaller ones report scaling AI agents. Three related trends show where this is heading, according to Gartner’s 2026 list:

• Multiagent systems: groups of AI agents that work together toward shared goals and automate complex processes.
• AI-native development platforms: generative AI tools that let small teams build software. Gartner predicts that by 2030, 80% of organizations will shift from large engineering teams to smaller AI-augmented ones.
• Domain-specific language models: AI trained for one industry. Gartner expects over half of enterprise generative AI models to be domain-specific by 2028.

McKinsey’s Technology Trends Outlook 2026 adds two new trends: agentic software development and AI for scientific discovery and engineering. Both are on pace to more than double their 2025 investment, along with AI infrastructure, space technologies and robotics.

What to expect: AI tools will keep spreading into everyday software, but the gap between using AI and gaining value from it is the main thing to watch.

Computing hardware: custom AI chips and quantum

AI is changing the chips underneath it. McKinsey reports that spending on AI infrastructure doubled in one year, and that running trained models (inference) is overtaking training as the main AI workload. That is driving demand for application-specific chips built for one job.

Gartner describes the same shift as AI supercomputing platforms, which combine CPUs, GPUs, AI chips and other processors. It predicts that over 40% of leading enterprises will use hybrid computing architectures by 2028, up from 8% today (Gartner, via CRN Asia).

Quantum computing is the long-range bet. Recent progress is measured in error-corrected (logical) qubits rather than raw qubit counts:

• QuEra reported 96 logical qubits from 448 atoms in a January 2026 Nature paper, the largest verified logical-qubit count on Quantum Zeitgeist’s tracker.
• The Quantum Insider reports that Quantinuum ran computations with 94 error-protected logical qubits in March 2026, and that IBM’s Starling system, targeted for 2029, aims for 200 logical qubits.

These are still research-stage results. No quantum computer today can break current encryption (InterviewBit). For a closer look, see our guide to whether quantum computers exist and what they can do.

What to expect: more specialized chips in data centers within the next few years, and useful but narrow quantum machines later in the decade at the earliest.

Connectivity: 6G is coming, but not soon

6G is the next generation of mobile networks, and the standards work has started. Ericsson reports that in June 2026 the standards body 3GPP set Release 21, the period when the 6G specifications are written, to run from March 2027 through late 2028. Ericsson expects the first commercial 6G systems in 2030.

So for most people, 6G is a 2030s upgrade. In the meantime, the focus is on getting more from today’s 5G networks.

Investment tells a similar story. In McKinsey’s 2026 outlook, every trend except advanced connectivity is on track for higher funding than in 2025. Networks are not where the money is flowing right now.

What to expect: no need to wait for 6G before buying a phone or planning a network upgrade. The first 6G phones are unlikely before the end of this decade.

Energy and transport: power is the bottleneck

AI runs on electricity, and the grid is now a limit on tech growth. According to the IEA, data centre electricity demand rose 17% in 2025, while overall global electricity demand grew 3%. The IEA projects data centre consumption to double by 2030, with AI-specific demand tripling.

McKinsey adds three details on the strain:

• US data centers running AI workloads are projected to use as much electricity by 2030 as California does today.
• In many markets, transformers have lead times of more than two years.
• More than 2,500 gigawatts of energy projects are stalled in grid queues worldwide.

Energy technologies drew nearly $200 billion in investment in 2025, among the highest totals of any technology domain, the same report says.

Electric vehicles are the other big physical trend. The IEA’s Global EV Outlook 2026, as reported by pv magazine, gives these figures:

• 2025: global electric car sales grew 20% to over 20 million, about a quarter of new cars sold.
• 2026 forecast: 23 million sales, close to 30% of the market.
• Early 2026: sales fell 8% in the first quarter after policy changes in China and the United States, while Europe rose nearly 30%.
• Southeast Asia: sales more than doubled in 2025 to a share of nearly 20%, and the IEA projects it could reach 60% by 2035.

What to expect: electricity supply, not chips alone, will decide how fast AI grows. EVs keep gaining share, with the fastest growth outside the big three markets.

Robotics and AI for science

Physical AI means AI built into real-world machines such as robots, drones and industrial equipment. It is one of Gartner’s top 10 trends for 2026, and robotics is one of the five trends on pace to more than double its 2025 investment, according to McKinsey.

Humanoid robots are the most hyped part, and the least ready. Gartner expects fewer than 100 companies to move humanoids beyond early testing by 2028, and fewer than 20 to use them in live production, mostly in tightly controlled settings. It cites weak performance on mixed items and exceptions, limited battery life, high cost and hard integration. Gartner favors polyfunctional robots instead: purpose-built, often wheeled, and more reliable for warehouse work.

AI for scientific discovery and engineering is the other fast riser. McKinsey added it as a new trend in 2026 and expects its investment to more than double.

What to expect: robots that do one task well will spread first. General-purpose humanoids are a later story.

Security and trust

As AI spreads, protecting it becomes its own industry. McKinsey notes that more than three-quarters of cybersecurity vulnerabilities are classified as zero-day, meaning an exploit already existed when they were disclosed. That is why defenders are moving from reacting to predicting.

Gartner’s list has four security-related trends, each with a forecast:

• Preemptive cybersecurity: AI-powered tools that stop attacks before they happen. By 2030, half of all security spending will go to them.
• AI security platforms: protection against threats such as prompt injection, data leakage and rogue agents. By 2028, more than 50% of enterprises will use them.
• Confidential computing: hardware that protects data while it is in use. By 2029, over 75% of operations in untrusted infrastructure will be secured this way.
• Digital provenance: proof that code and content are authentic, using tools such as watermarking. Gartner warns that organizations that skip it could face sanction risks worth billions by 2029.

A fifth issue is encryption. NIST finalized its first post-quantum standards (ML-KEM, ML-DSA and SLH-DSA) in August 2024, and organizations have begun migrating to them, according to InterviewBit. The aim is to stop “harvest now, decrypt later” attacks, where stolen encrypted data is unlocked years later by a quantum computer. No quantum computer can do that today.

What to expect: more AI-driven defense, more rules about proving where content comes from, and a slow, steady move to quantum-safe encryption.

How to prepare for what comes next

You do not need to chase every trend. These steps work for most people and small businesses:

1. Learn one AI tool well. Use it on a real task each week. McKinsey’s data shows that using AI is common but getting value from it is not, so focus on a workflow, not on trying everything.
2. Build skills that work alongside AI. Judgment, domain knowledge and checking AI output matter more as tools handle routine steps.
3. Check claims before you believe them. Ask for the source, the date and the baseline. Many “breakthroughs” are pilots or company-reported results.
4. Keep security basics current. Update software, use strong unique passwords and two-step sign-in, and be careful with AI-generated messages and media.
5. Plan for power and cost. If you run a business, expect AI and cloud costs to be tied to electricity and chip supply.
6. Wait on the long bets. You do not need to plan around 6G phones, humanoid robots or quantum computers yet. Revisit them when products reach your market.

FAQ

What is the future of technology? A mix of AI that acts on its own, custom chips, quantum computing, cleaner energy and electric vehicles, smarter robots and stronger security. AI sits at the center of most of them.

What are the biggest technology trends right now? Gartner’s 2026 list includes multiagent systems, AI-native development platforms, physical AI, preemptive cybersecurity and digital provenance. McKinsey tracks 14 trends, led by agentic AI.

Will AI take over jobs? The evidence so far is mixed and it depends on the role. Gartner predicts that by 2030, 80% of organizations will move from large engineering teams to smaller AI-augmented ones, which means the work changes shape.

When will 6G arrive? Ericsson expects the first commercial 6G systems in 2030, after specifications are written between March 2027 and late 2028.

Will most cars be electric? Not yet. The IEA expects electric cars to reach close to 30% of global sales in 2026, and a quarter of sales in 2025.

Are quantum computers useful yet? Only in research and pilots. Fault-tolerant machines are still years away.

Are humanoid robots about to take over factories? Unlikely soon. Gartner expects fewer than 20 companies to run them in live production by 2028.

Sources

• CRN Asia: Gartner unveils top strategic technology trends for 2026
• McKinsey: Technology Trends Outlook 2026, key takeaways
• McKinsey: The State of AI (2026 survey)
• Ericsson: 6G standardization timeline, key milestones and RAN decisions (June 2026)
• pv magazine Australia: Nearly 30% of cars sold in 2026 to be electric (IEA Global EV Outlook 2026)
• IEA: Data centre electricity use surged in 2025 (Key Questions on Energy and AI, April 2026)
• Supply Chain 24/7: Gartner on humanoid robots by 2028
• Quantum Zeitgeist: Top Quantum Hardware Companies 2026 by Modality
• The Quantum Insider: Types of Quantum Computers (Aug 2026)
• InterviewBit: Quantum Computing Applications in 2026

Checked 8 November 2026. Forecasts are analysts’ predictions, not certainties, and figures change with each new report.