The technology shifts every business leader should be watching

Equity investment across 14 top technology trends totaled about $761 billion in 2025, according to McKinsey’s Technology Trends Outlook 2026. At the same time, the field is more interconnected than ever. How can leaders identify what matters most? Which trends are likely to attract the most investment and create value?

During a McKinsey Live event, McKinsey experts Michael Chui and Roger Roberts discussed where momentum is building, the growing convergence between trends, and the impact of these shifts on businesses, workers, and society.

The changing face of technology

The 14 technology trends fall into three broad categories: the AI revolution, compute and connectivity frontiers, and cutting-edge engineering. The boundaries are blurring, and the most important innovations are increasingly happening between categories rather than within a single one.

The big news for 2026? AI has more autonomy. Agents are completing end-to-end tasks. Physical AI is bringing perception, reasoning, and action into robotics, mobility, and wearables. To succeed, business leaders need to determine which trends will affect their sources of competitive advantage and distinguish where they need to lead and where they should build partnerships.

Rising investment

Some of these trends are attracting capital at a remarkable pace. This year, five trends are expected to receive more than twice the investment they received in 2025 (for more about the fifth trend, on the future of robotics, see our recent McKinsey Live event “Physical AI: The hidden value pools leaders are missing”):

1. AI infrastructure and model architectures

AI infrastructure and model architectures is the most searched technology trend in 2025, reflecting broad enterprise urgency to understand and deploy foundational AI capabilities. Equity investment was $145 billion in 2025, the second highest of any trend, and has since surged to nearly $384 billion through mid-2026, the largest of any trend. If investment continues at the current pace, full-year 2026 investment would reach roughly $769 billion.

2. Agentic software development

Nearly every industry writes software now, fundamentally changing how software engineers operate. Even so, only about 25 percent of companies using these tools have significantly improved their pace or output. In addition, companies need to protect against both intentional and inadvertent risks when it comes to adopting agents into their engineering teams and code.

3. Future of space technologies

Space is becoming an infrastructure layer for the terrestrial economy. Increasingly, the value proposition focuses on what happens on Earth: assuring connectivity, geospatial intelligence, sensing, navigation, and decision support. As lower launch costs and more capable satellites expand the array of use cases, space technology is attracting substantial interest and investment.

4. AI for scientific discovery and engineering

AI can now propose thousands of drug candidates in a short amount of time and help evaluate them. What happens when the speed of discovery starts to outrun the systems we rely on to validate and scale? In many cases, AI cannot accelerate biological testing or regulatory review, but this remains an exciting opportunity for the technology to create innovation and significant impact for companies and society.

Considerations for leaders

With tech trends converging, how do leaders decide where to lean in and where to partner?

• Identify where to lead and where to ride the wave. Take advantage of external innovation, talent, and capital for some activities, while making well-measured bets on the capabilities that can materially change differentiation, customer value, or critical operations.
• Match the pace of adoption to evidence. A frontier demonstration may justify learning, but scaling should depend on reliable performance, economics, risk, ecosystem readiness, and the organization’s ability to absorb the change.
• Recognize that technology is often not the hard part. Change leadership applied across the tech stack and across governance, procurement, and talent can often determine whether a promising technology becomes a scaled business capability.
• Redesign operating models. As agents work alongside people and take on more end-to-end work, companies will need to redesign operating models, including skills, decision rights, governance, and accountability.
• Know where to allocate resources. Invest in no-regret foundations such as data, cybersecurity, compute, talent, and adaptable architecture, while making a smaller number of differentiated bets.