NTT DATA Technology Foresight 2026 outlines six AI macrotrends, from autonomous systems to sovereign silicon and sustainable computing.
Artificial intelligence has crossed a threshold. According to NTT DATA’s Technology Foresight 2026 report, the world has entered an era of “mass intelligence” — a phase where AI is no longer a specialized tool but an ambient capability embedded across systems, industries and daily life. The analogy the report draws is deliberate: just as mass media reshaped society by making information universally accessible, AI is now doing the same with cognition.
The report identifies six macrotrends that the company believes will define how organizations build, govern and benefit from this shift — not simply by chasing efficiency, but by designing systems that are transparent, ethical and aligned with human intent.
From Task Automation to Purpose-Led Autonomy
The first trend examines the evolution of autonomy itself. Where earlier generations of software automated discrete tasks, modern AI systems can now act independently across entire business functions, physical processes and decision networks. The report describes this as a shift toward “human-orchestrated autonomy,” where humans set intent and AI carries it out at scale.
Central to this vision are AI-native architectures and agent identities — standardized mechanisms that make autonomous actions attributable, auditable and reversible. The underlying design principle is adaptive autonomy: systems that modulate their independence based on risk and context. A drone fleet, a trading algorithm and a customer-service agent may all operate under different levels of oversight, calibrated continuously through governance and feedback loops.
Machines That Read the Room
The second trend moves into less familiar territory: emotional intelligence in machines. As AI systems become embodied — through humanoid robots, digital humans and responsive interfaces — they are gaining the capacity to interpret tone, gesture and expression, adjusting how they communicate accordingly.
The report frames this as more than a usability feature. Emotionally responsive technology is becoming part of social infrastructure, deployed in healthcare, education, mobility and governance. The concept of “sensorimotor empathy” describes how machines can sense context and respond with appropriate care, building trust through interaction over time. The ethical dimension is explicit: emotional data — generated by facial recognition, voice analysis and behavioral signals — demands stringent design standards around consent, privacy and authenticity.
Trust as Infrastructure
The third trend concerns trust — specifically, the conditions under which humans can have justified confidence in AI reasoning, not just AI outputs. As systems grow more autonomous, the question shifts from whether a system produced the right answer to whether the process that generated it is sound.
The report argues that cybersecurity must evolve alongside autonomy. AI-powered security can predict threats and validate system integrity proactively; but the AI systems themselves also need protection from data poisoning, bias and manipulation. Zero-trust architectures — where every user, device and algorithm must continuously verify its behavior — extend into a new domain of cognitive transparency. Explainable AI, which allows humans to see how a system reasons and decides, becomes the mechanism through which accountability is made measurable.
Infrastructure That Learns
The fourth trend reframes what infrastructure means in an AI-intensive world. Servers, networks and data centers — once commodity assets — are now strategic ones. The report describes “informed infrastructure” as systems that sense, learn and adapt across the continuum of devices, edge environments and cloud platforms.
High-performance computing and quantum simulation allow organizations to model complex systems — urban layouts, energy grids, logistics networks — before committing resources to deployment. The placement of computation (on-device, at the edge, or in the cloud) is no longer a purely technical decision but an economic and political one, shaped by latency requirements, energy costs and regulatory constraints. Informed infrastructure, the report argues, should be designed around human wellbeing, not just operational efficiency.
The Semiconductor Sovereignty Race
The fifth trend addresses the geopolitical dimension of AI: control over the chips that make intelligence possible. Nations and corporations are racing to build end-to-end semiconductor ecosystems, from design through fabrication to supply-chain management. The report describes this as “sovereign silicon” — a recognition that dependency on foreign chip supply chains creates systemic vulnerability.
Demand from AI workloads is reshaping semiconductor design priorities, shifting emphasis from general-purpose processors to inference-optimized architectures, and from centralized data centers to edge devices capable of local analysis. Heterogeneous compute — combining ASICs, FPGAs, GPUs and photonic processors — is emerging as the approach for reducing dependency while optimizing performance. Critically, the report notes that sovereignty does not require isolation: collaborative ecosystems linking governments, universities and industry remain the engine of innovation, with ethical sourcing and energy-efficient manufacturing aligning national interests with environmental ones.
Redefining Progress Through Sufficiency
The sixth and final trend is the most conceptual — and perhaps the most urgent. The report challenges the default assumption that more computing power, more optimization and more output equates to progress. Under the concept of “sufficiency,” organizations are encouraged to value durability, adaptability and long-term adequacy over relentless growth.
AI and digital twins become tools of moderation in this framing, helping organizations identify optimal thresholds for resource use rather than pushing continuously toward maximum throughput. Scarcity — of compute, energy or materials — becomes a driver of smarter design rather than a problem to be overcome with more investment. Regulatory frameworks anchored in real-world data create accountability loops that connect local decisions to systemic outcomes.
A Common Thread
Across all six trends, the report draws a single throughline: that human intent can only scale through intelligence when it is guided by empathy, trust, sovereignty and purpose. Autonomy gives machines agency; emotional awareness makes them relatable; trust keeps them safe; infrastructure makes them scalable; sovereignty keeps them fair; and sufficiency makes them sustainable.
The Technology Foresight 2026 does not position these trends as inevitable forces to be adapted to, but as design choices — architectures that organizations can build toward or away from, depending on the values they want to embed in the systems they create.
Dr. Jakob Jung is Editor-in-Chief of Security Storage and Channel Germany. He has been working in IT journalism for more than 20 years. His career includes Computer Reseller News, Heise Resale, Informationweek, Techtarget (storage and data center) and ChannelBiz. He also freelances for numerous IT publications, including Computerwoche, Channelpartner, IT-Business, Storage-Insider and ZDnet. His main topics are channel, storage, security, data center, ERP and CRM.
Contact via Mail: jakob.jung@security-storage-und-channel-germany.de