From Agentic AI to Quantum: How Enterprises Will Change in 2026

After a year dominated by pilots and proofs of concept, enterprises are entering a more consequential phase of digital transformation. In 2026, the defining question will no longer be whether advanced technologies work but whether organisations are structured to run them at scale.

According to Sandhya Arun, Chief Technology Officer, Wipro Limited, the global IT industry crossed a threshold in 2025, with artificial intelligence moving from experimentation into meaningful adoption. Generative AI and automation became part of everyday operations, while early agent-led models began influencing enterprise decision-making, always with human oversight at the core.

Looking ahead, Arun sees a sharper shift: AI systems embedded directly into critical workflows, operating continuously across the enterprise. This evolution, she notes, does not diminish human roles. Instead, it elevates them from execution to orchestration, where judgement, governance, and strategic intent become central.

Below are seven technology trends Arun believes will shape how enterprises operate in 2026.

Agentic AI Will Actuate The Autonomous Enterprise

Enterprises are moving from isolated agentic AI experiments to pragmatic, enterprise-wide strategies focused on measurable business outcomes. By 2026, networks of collaborating AI agents will manage complex workflows across IT, HR, finance, marketing, sales, legal, procurement, operations, supply chains, customer engagement, and commerce. As AI gains autonomy, the human role evolves toward strategic direction, governance, and human-centric steering.

Embodied AI Will Unlock The Physical Economy

AI will increasingly be embedded in robots, vehicles, machines, and intelligent devices, evolving from standalone units into connected ecosystems integrated through an “AI mesh”. With enhanced spatial awareness and autonomy, embodied AI will drive adoption across healthcare, manufacturing, energy, utilities, mobility, and logistics, improving safety, efficiency, and human experience in complex or hazardous environments.

Digital Twin And AI Will Transform Operations

The combination of Digital Twins (DTs) and AI will enable intelligent virtual models that continuously simulate, predict, and optimise physical assets and processes through real-world simulations. These AI-enabled DTs will support preventive maintenance, real-time monitoring, product design, testing, and resource optimisation, helping organisations become more agile, resilient, and data-driven.

Domain-Native AI Will Drive Deep Vertical Mastery

We will see a growing shift towards specialised, “industry- or domain-native” models rather than broad, general-purpose ones. These models will be trained on industry-specific datasets and built with contextual intelligence such as ontology, risk controls, safety and regulatory requirements—embedded into the solution from the start. Smaller, focused models will deliver deeper expertise and better accuracy in specific areas, while also being more cost-effective and less resource intensive.

Programmable Money Will Become The New Economic Engine

Distributed ledger technologies are moving from pilots to real-world use, enabling transparent and immutable record-keeping without central control. With growing regulatory clarity and the rise of CBDCs, decentralised finance will become more enterprise-ready, supporting use cases such as tokenised bonds, autonomous lending, and always-on settlement. Stablecoins and asset tokenisation will further accelerate faster, more efficient finance across cross-border payments, supply chains, and digital asset management.

Quantum Technology Will Mark The Birth Of A New Era

Breakthroughs in quantum computing are opening up new possibilities for solving problems that are too complex for traditional systems. Early use cases are emerging across pharma and life sciences, financial services, and materials science, with technology-forward enterprises already experimenting with quantum computing as a Service. At the same time, quantum advances pose risks to existing encryption standards, accelerating the shift towards quantum-safe algorithms and Post Quantum Cryptography (PQC).

Workforce Readiness Will Be A C-Suite Survival Metric

Workforce readiness is critical to unlocking value from frontier technologies. High-potential talent will be defined by continuous learning, practical application of new skills, sound judgement, and initiative. Organisations that foster a culture of learning, collaboration, and effective human–machine collaboration will gain a clear advantage, with change management becoming a core leadership responsibility as advanced technologies scale.

These trends point to a future where humans and machines operate as integrated systems, reshaping business models, value creation, and the nature of work itself. Enterprises that invest in people, embed governance into innovation, and reimagine their operating DNA will be best positioned to thrive in an AI-first world.

From the enterprise vantage point, 2026 is shaping up as a year of accountability. The technologies are largely proven, the use cases are visible, and the investment cycles are already in motion. What remains uneven is execution—how well organisations align talent, governance, operating models, and culture to support systems that increasingly think, act, and learn at scale.

The throughline across these trends is not speed, but structure. Enterprises that treat AI, automation, and emerging technologies as layered capabilities, rather than standalone tools will be better equipped to absorb disruption without losing control. Those that fail to recalibrate decision-making, risk frameworks, and workforce readiness may find that technological ambition outpaces operational reality.

As enterprises move deeper into an AI-first era, the competitive divide will widen not between those who adopt advanced technologies and those who do not, but between those who redesign their organisations around them and those who attempt to bolt them onto legacy ways of working. The next phase of digital transformation will be less about innovation headlines and more about who can run these systems responsibly and at scale every day.