John Roese | Global CTO | Chief AI Officer | Dell Technologies | mail me |
In 2023, we witnessed the Big Bang of technology. That year, Artificial Intelligence (AI) ignited a new era of innovation and transformation.
In 2025, GenAI went mainstream, and agentic AI entered the scene. Most importantly, real return on investment began to emerge in major enterprises. These milestones confirm that the AI revolution continues to reshape how organisations create value.
In 2026, the AI story accelerates further. In less than three years, theory has turned into reality. The future is now arriving at light speed. As momentum builds, the AI revolution continues to compress timelines between experimentation and enterprise-scale impact.
This year, AI will reengineer the entire fabric of enterprise and industry. It will drive new ways of operating, building and innovating. The scale and pace will exceed what seemed possible just a year ago. Understanding these shifts is essential. Those who invest in resilient and adaptable foundations today will lead tomorrow, as the AI revolution continues to unfold.
A call to action – governance frameworks for a fast-moving ecosystem
As AI development accelerates, volatility increases. While governance frameworks may eventually stabilise the ecosystem, current conditions demand immediate action. Right now, governance represents the long pole in the tent. It remains a critical challenge, and progress has been too slow.
The industry has rushed to deploy valuable AI tools such as chatbots and agents. However, it has done so without sufficient governance structures. This approach is not just risky. It is unsustainable. By 2026, enterprises will no longer debate the need for robust frameworks and private environments. Stability and control will become non-negotiable.
Running models locally will become standard practice. Organisations will deploy them on premises or within controlled AI factories. This shift reflects more than a prediction. It is an urgent appeal for action. We must prioritise real governance now. Without it, uncertainty will slow the adoption of practical and valuable enterprise AI, even as the AI revolution continues.
Our specific ask to both the public and private sectors is clear. They must develop enterprise governance collaboratively with the actual enterprise ecosystem. This includes real organisations and real enterprise technology suppliers. Governing public AI chatbots or AGI does not equate to enabling enterprises to apply AI responsibly within their operations.
Governance does not slow innovation. Instead, it builds the guardrails that allow innovation to accelerate safely and sustainably.
Data management – the true backbone of AI innovation
The next major leap in AI will not come from stronger algorithms alone. It will come from how organisations manage, enrich and use data. As AI systems grow more complex, data quality and accessibility become decisive factors.
In 2026, AI data management and storage will stand as the undisputed backbone of AI innovation. AI infrastructure differs fundamentally from classic IT systems. It centres on accelerated compute, AI-aligned networking and new user interfaces. Critically, it also introduces a new knowledge layer. This layer fuels AI-driven outcomes as the AI revolution continues.
Purpose-built AI data platforms will become essential. These platforms will integrate disparate data sources. They will also protect new data artefacts and deliver the high-performance storage required to support them.
Feeding clean, organised and relevant data into AI models remains critical. However, as we enter the agentic age, data will no longer serve training alone. Instead, it will function as a dynamic asset during inference. This enables real-time, evolving knowledge and intelligence. This underlying data layer acts as the launchpad for everything that follows.
Agentic AI – the new operations continuity manager
What comes next is agentic AI. Agentic systems evolve AI from a helpful assistant into a manager of long-running, complex processes. This shift marks a fundamental change in enterprise operations.
In manufacturing and logistics, AI agents will move beyond assistance. They will help coordinate human teams. Using rich and dynamic data streams, these agents will ensure continuity across shifts. They will optimise workflows in real time and unlock new levels of efficiency.
Imagine an AI agent scaling the reach of process managers on a factory floor. It adjusts production schedules in response to supply chain disruptions. It also guides new employees through complex tasks. By positioning AI agents between team goals and workers, organisations can elevate coordination across sectors. These capabilities reflect how the AI revolution continues to redefine operational leadership.
Over time, intelligent agents will become the nervous system of modern operations. They will ensure resilience and sustained progress. Like all AI capabilities, enterprise data powers them. This data creates unique knowledge and intelligence assets that require secure storage and protection.
AI factories redefine resiliency and disaster recovery
As AI embeds itself into core business functions, continuity becomes non-negotiable. AI infrastructure will evolve accordingly. Resiliency will take priority and redefine disaster recovery in an AI-driven world.
The focus will shift away from simple system backups. Instead, organisations will ensure that AI capabilities remain operational even when primary systems fail. In the coming year, AI factories must become resilient and survivable. They must operate across hybrid, multi-cloud AI environments.
Achieving this goal will require broad innovation. Data protection and cyber resiliency firms must contribute. Core AI technology providers must also play a role. Governments and large-scale AI innovators must collaborate as well. To make enterprise AI truly resilient, the entire value chain must work together, especially as the AI revolution continues to scale.
Sovereign AI accelerates national enterprise infrastructure
As AI becomes central to national interests, sovereign AI ecosystems are rising rapidly. Nations no longer act solely as consumers of AI. They now build their own frameworks to support local innovation and digital autonomy. This shift reshapes AI infrastructure planning.
AI compute, data storage and data management now play pivotal roles. They help safeguard sensitive information and keep it local. Enterprises will increasingly adapt their operations to align with sovereign frameworks. They will scale within regional boundaries rather than across unrestricted global systems.
This transition fuels a new wave of localised innovation. It produces tangible benefits for citizens and national economies. By keeping data within borders, governments can shape public services more effectively. At the same time, enterprises can leverage indigenous infrastructure while aligning with national industrial policy. This marks a foundational shift. AI moves from a global abstraction to a powerful local reality.
Charting your course for 2026
As we look toward 2026, the next wave of AI represents more than innovation breakthroughs. It represents the construction of a resilient and intelligent backbone that supports real progress.
The difference between success and stagnation will depend on execution. Organisations must understand and build this underlying infrastructure. They must also drive core AI innovation deliberately. Those who prioritise their data backbone and invest in adaptable, high-performance systems will not merely keep pace. They will move ahead as the AI revolution continues.
The tools and insights will be available. However, leadership and decisive action will determine who captures the real rewards. The future is not simply approaching. It is accelerating toward us at light speed. The question remains: are you ready to meet it?