Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Octavian Tanase, Chief Product Officer for Hitachi Vantara
If 2025 was the year that enterprises learned how to experiment with AI, then 2026 will be the year they learn how to depend on it. The era of pilot projects and isolated generative AI tools is giving way to something far more transformative: AI systems that can act, decide, and operate with increasing autonomy ultimately reshaping not only how businesses function, but the underlying infrastructure nations use to secure their futures. The most powerful thread connecting the coming year’s biggest trends is simple but sweeping: AI is evolving from a capability into a foundational layer of economic and national competitiveness. Everything else, from data strategy, and cloud architecture to hardware design and workforce models, now orbits around that shift.
At the center of this transformation is the rise of agentic AI, the defining enterprise technology trend of 2026. Unlike earlier generative models that simply produced content, agentic AI systems can carry out tasks, make decisions, and operate autonomously within business workflows. Companies will build them into supply chains, customer service operations, compliance processes and financial analysis routines. These agents won’t just answer questions-they’ll take action: triggering workflows, adjusting parameters in real time, and handling decisions previously owned by people.
But with autonomy comes complexity. Enterprises will need deep governance systems, trust frameworks, and high-quality data pipelines to ensure these agents behave predictably and responsibly. This is where the second major trend of 2026 emerges: data becomes the primary source of competitive differentiation.
As compute, models, and even advanced algorithms continue to commoditize, the differentiator becomes proprietary, high-quality, well-governed data. Every enterprise will be forced to confront a common reality: the sophistication of their AI will depend less on the power of their models and more on the precision, cleanliness and trustworthiness of the data feeding them. Companies with mature data estates will leap ahead. Those that haven’t will struggle to adapt as agentic systems require faster decision cycles, real-time correlation and more granular contextual signals.
The third unifying thread builds on this shift: governments around the world now view AI infrastructure as a strategic asset, on par with energy or defense. The growth of sovereign clouds is not a niche movement but rather a geopolitical response to the AI era. Nations want the ability to own and protect the data that fuels their economies and secures their populations. They want assurances about where sensitive information is stored, how models are trained, and whether AI systems can be trusted to respect regulatory boundaries.
In 2026, expect sovereign cloud ecosystems to accelerate dramatically. Countries will invest in regulation-ready, energy-efficient data centers designed specifically for AI workloads. These facilities will become the sanctuaries for citizen data, financial data and defense-adjacent data, built to support regulatory compliance and national oversight. As AI agents proliferate, the need for national oversight and infrastructural control becomes impossible to ignore.
That dovetails directly with the fourth trend: AI is pushing the physical limits of today’s data-center architectures, forcing a modernization cycle unlike any seen before. AI and agentic workloads demand staggering compute density, specialized accelerators, and storage architectures designed for low latency and high throughput. Power and cooling constraints, once an operational consideration, are now a limiting factor for AI innovation.
As a result, organizations will aggressively shift toward high-density, energy-efficient systems, especially flash-based architectures that outperform traditional disk systems while dramatically reducing power consumption. This modernization isn’t just about performance. It is driven by he need to free power capacity for AI workloads. If companies cannot free up power capacity, they cannot expand AI capabilities. If they cannot expand AI capabilities, they will fall behind competitively. Sustainability requirements and emerging regulations will also accelerate this shift, making energy efficiency not merely an operational upgrade, but a compliance imperative.
Across these important trends, a single narrative emerges: AI is no longer a tool layered onto business operations. It is the backbone upon which operations, infrastructure, regulation and national strategy will depend. Agentic AI drives the need for better data Better data drives the need for secure, sovereign, compliant environments. Those environments require modernized, energy-efficient infrastructure purpose-built for intelligent automation. This ecosystem reinforces itself.
And woven throughout is a final, human truth. Even as systems become more autonomous, people remain essential. 2026 will see a surge in workforce reskilling, not to make employees coders, but to make them orchestrators who can harness these autonomous systems to transform their industries. The next breakthroughs won’t come solely from data scientists but from domain experts empowered by AI that can act alongside them.
In 2026, AI becomes the new infrastructure and the organizations that understand this shift early will define the competitive landscape for years to come.
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As Chief Product Officer, Octavian Tanase drives the vision, strategy, development, and execution of Hitachi Vantara�s product portfolio. He ensures the creation and delivery of innovative products, services, and solutions that provide robust cybersecurity protection, meet business requirements, drive adoption and engagement, and transform customer experiences.
Octavian joined Hitachi Vantara in 2024. He brings more than 25 years of experience in engineering roles, including core storage technology, hardware platform development, software and systems development, application integration and data protection. Prior to joining Hitachi Vantara, he was the senior vice president of hybrid cloud engineering at NetApp, where he led the integration of NetApp�s software portfolio in the AWS, Azure and Google Cloud Platform clouds. Prior to NetApp, he held engineering and product development positions at Oracle, Sun Microsystems and several Silicon Valley startups.
Octavian is a University of California, Berkeley graduate and resides in the San Francisco Bay Area.
