Technology Foresight 2026: What happens when intelligence is everywhere?

For years, we talked about digital transformation as if it were a destination: Automate this, optimize that, move faster.

But something has changed. We’ve entered the era of mass intelligence, embedded all around us and accessible to billions of people through systems, infrastructure and interfaces. Where the advent of mass media democratized access to information with socioeconomic impact, the world now democratizes access to intelligence itself, shifting not just what we know but also how decisions are made, value is created and power is distributed.

As more machines begin to learn, adapt and act independently, the important question becomes how we choose to use this intelligence.

That’s the starting point for NTT DATA Technology Foresight 2026: a deep exploration of how organizations can sustain operations in a world where technology systems are autonomous, emotional, interconnected and increasingly powerful.

Our report maps six macrotrends that together form the architecture of what comes next — and what leaders need to design for today.

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From automation to autonomy: 6 technology macrotrends

1. Human-orchestrated autonomy: When machines act but humans are in control

Imagine a logistics network that reroutes delivery vehicles automatically in real time during a crisis, a customer-service system that resolves issues without escalation, or a trading algorithm that slows itself down when risk spikes.

This is autonomy, but not without limits. The shift underway is from task-based automation to purpose-led intelligence. Humans define intent while intelligent systems execute it at scale, with oversight always built in.

Advanced organizations are designing adaptive autonomy, building systems that know when to act independently and when to ask for guidance. Every action remains attributable, auditable and reversible, because autonomy cannot replace human judgment.

2. Embodied agency and emotions: When technology learns how we feel

We’re used to machines that respond to commands. What’s emerging now are systems that respond to both commands and people.

Emotionally aware technologies can sense our tone, interpret our gestures and understand our context. They constantly adjust how they communicate with us and build trust through presence, not just performance.

Think of a digital health assistant that detects anxiety in a patient’s voice, or a learning system that adapts when a student seems frustrated. In these scenarios, emotion becomes part of the interface.

Of course, this raises new responsibilities. Emotional data demands consent, transparency and ethical design. But done right, emotionally intelligent systems can humanize digital transformation.

3. Intelligence we trust: Why transparency matters more than accuracy

As AI systems become more autonomous and emotional, trust becomes the real foundation of progress.

Trust now goes beyond security to include confidence in how decisions are made. Organizations are moving beyond deterministic outputs toward explainable intelligence with systems whose reasoning can be audited and challenged. At the same time, cybersecurity evolves into adaptive defense, learning from threats and responding proactively.

AI itself must be protected from bias, manipulation and data poisoning. Zero trust architectures, continuous verification and cognitive transparency are helping organizations to redefine governance.

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4. Informed infrastructure: When systems start thinking ahead

Infrastructure used to be invisible — just “the plumbing.”

Not anymore.

The latest infrastructure learns and adapts across devices, edge environments and cloud platforms. With applications ranging from energy grids to urban planning, high-performance computing and simulation allow outcomes to be modelled before decisions are made.

Instead of reacting to problems, these systems anticipate them.

Infrastructure choices are no longer just technical, either. Where data is processed — on a device, at the edge or in the cloud — becomes an economic, regulatory and even political decision.

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5. Sovereign silicon ecosystems: Why chips have become strategic assets

Every intelligent system runs on silicon, and control over silicon increasingly means control over intelligence itself.

As AI demand accelerates around the world, computing shifts from general-purpose processing to specialized, inference-heavy workloads — often at the edge. This has led to a global race to build sovereign semiconductor ecosystems.

Nations and industries are investing across the entire stack: design, fabrication, photonics and supply chains. Heterogeneous computing architectures — GPUs, application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) and more — reduce dependency and improve resilience.

But sovereignty doesn’t mean isolation. The most successful ecosystems combine national capability with global collaboration to align ethical sourcing with energy efficiency and long-term innovation.

6. From illusory efficiency to sufficiency: Why “more” is no longer the goal

The final macrotrend brings the conversation back to purpose. For years, efficiency meant fast scaling and constant growth. But in a world of near-limitless computing power, that definition starts to break down. The question is now: What is enough?

Instead of optimizing endlessly, organizations are focusing on resilience, durability and long-term value. AI and digital twins model optimal thresholds for resource use, not maximum extraction.

Constraints become catalysts for innovation, and governance becomes grounded in real-world data. Beyond output, progress is also measured by trust, stability and wellbeing.

Design intelligence with intent

Across all six macrotrends, one message is clear: Intelligence scales human intent — but only when guided by empathy, trust, sovereignty and purpose.

The NTT DATA Technology Foresight 2026 report is your invitation to make deliberate and responsible choices about how this intelligence shows up in our systems, our societies and our everyday lives.

Because in an era where technology can do almost anything, the real differentiator is knowing what it should do — and why.

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