In 2023, we witnessed the Big Bang of technology – a year in which artificial intelligence ushered in a new era of innovation and transformation. In 2025, generative AI went mainstream, and agent-based AI took the stage. Most importantly, real returns on investment began to emerge for large companies such as Dell Technologies.
In 2026, the story of artificial intelligence is accelerating. AI will redesign the entire structure of businesses and industries. It will drive new ways of doing things, building and innovating at a scale and pace previously unimaginable.
Understanding these changes is essential, as those who invest today in a robust, flexible technology base and benefit from a network of partner ecosystems will be ready to manage the rapid changes to come.
Time to act: principles governing a dynamic ecosystem
With the acceleration of artificial intelligence comes a degree of volatility. While we anticipate that the governance framework will eventually stabilise the ecosystem, today’s reality is a call to action.
Governance is currently causing the most delays and it’s even a critical problem that is not making progress. The industry has rushed to bring valuable artificial intelligence tools such as chatbots and agents into production, but we have done so without sufficient governance.
This is not only risky, but unsustainable. By next year, robust frameworks and private environments are needed to ensure stability and control. Running models locally, on their own servers or in controlled AI factories, will become the norm to provide a stable foundation and insulate organisations from external disruption.
But this is more than a forecast. It is an urgent appeal. We need to focus more on governance. Without this, we will end up with uncertainty that will slow down the implementation of practical and valuable artificial intelligence for businesses.
Our concrete demand to the public and private sector is to create rules for the governance of the enterprise market in collaboration with the real players in this market – enterprises and business technology providers.
We cannot assume that managing public AI or AGI chatbots is the same as helping businesses shape the actual application of artificial intelligence in their companies and processes.
Governance is not about slowing down innovation. It is about building a protective framework that allows us all to accelerate in a safe and sustainable way.
2. Data management: the real foundation of innovation in artificial intelligence
The next big leap in artificial intelligence will not just come from more powerful algorithms. It will come from the way we manage, enrich and use our data. As artificial intelligence systems become more complex, the quality and availability of the data they use is paramount.
In 2026, AI-based data management and storage will become the undisputed foundation of all AI innovations.
AI infrastructure is different from classic IT systems. It focuses on accelerated computing, advanced networking adapted to AI, new user interfaces and, most importantly, a new layer of knowledge from data that drives its results.
Purpose-built AI data platforms, designed to integrate disparate data sources, protect new artefacts and provide the efficient storage needed to support them, will become essential. Partner ecosystems can help unlock the potential of these purpose-built platforms, with partners using their expertise to integrate and optimise data management solutions for enterprise AI.
The ability to effectively feed clean, structured and relevant data into artificial intelligence models is crucial. However, as we enter the era of agent-based AI, this data will no longer be used solely to train large models. Instead, they will be a dynamic resource during inference, enabling the generation of evolving knowledge and intelligence in real-time. This foundational layer of data is the starting point for everything that comes next.
3 Agent AI: the new business continuity manager
What is coming is agent-based artificial intelligence. An evolution that transforms artificial intelligence from a helpful assistant to an integral manager of long-term, complex processes.
In areas such as manufacturing and logistics, artificial intelligence agents will not just assist workers, they will assist in coordinating their activities. Using rich, dynamic data streams, they will ensure continuity between shifts, optimise real-time workflows and create new levels of operational efficiency.
Imagine an artificial intelligence agent scaling the capabilities of process managers on the shop floor, adjusting production schedules based on supply chain disruptions or guiding a new employee through a complex task. By positioning AI agents as intermediaries between a team’s goals and its employees, we are elevating team coordination across all sectors to unprecedented levels.
These intelligent agents will become the nervous system of modern operations, ensuring resilience and progress. Like any other AI capability, they rely on enterprise data to create a unique store of knowledge and intelligence that must be properly stored and protected.
4. Artificial intelligence factories redefine resilience and disaster recovery
The more AI integrates with a company’s core functions, the more business continuity becomes unquestionable.
Artificial intelligence infrastructure will evolve to prioritise operational resilience, redefining the meaning of disaster recovery in an AI-driven world. The focus is not just on backing up systems, but on ensuring AI functionality, even if the underlying systems go offline. This includes protecting vectorised data and other unique artefacts, so that system intelligence can survive any disruption.
Achieving this requires innovation across the AI value chain, from data protection and cyber security companies to key AI technology providers. Collaborative ecosystems include governments, partners and large-scale AI innovators. They must work together to build resilient factories that bring together the tools and expertise needed to ensure continuity and secure critical functions in hybrid cloud environments.
5. Sovereign artificial intelligence accelerates development of national enterprise infrastructure
Artificial intelligence is central to national interests, which is why we are seeing the rapid development of sovereign artificial intelligence ecosystems. Countries are no longer just consumers of AI technology, they are actively building their own frameworks to drive local innovation and maintain digital autonomy.
This is changing the way artificial intelligence infrastructure is planned, with computing, data storage and management playing a key role in protecting and locating sensitive information.
Businesses will increasingly adapt to this framework, scaling their operations within regional boundaries. By storing data locally, governments can shape public services such as healthcare, and businesses can use national infrastructure while aligning business objectives with national industrial policy.
This creates innovations with a direct impact on citizens and economies, and represents a fundamental shift that moves artificial intelligence from a global concept to a concrete, local reality.
Setting the course for 2026
In 2026, the artificial intelligence revolution is not slowing down, but accelerating. What started with the Big Bang has reached the speed of light, and leading organisations are evolving and adapting to change just as fast.
To succeed, you don’t need to chase every breakthrough. It’s better to build an infrastructure that can keep up with these changes: resilient AI factories, sovereign frameworks, agent systems that manage complex operations and collaborative ecosystems that turn innovation into real business impact. The tools and information are available. It is the readiness to act that already sets leaders apart from the rest.
Leadership and concrete action will determine who reaps the real rewards. The future is rushing by at the speed of light. The question is: are we ready?
By John Roese, global director of technology and artificial intelligence at Dell Technologies
