Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Madhu Shashanka, Cofounder and Chief Scientist of Concentric AI
In 2026, I expect renewed emphasis on data security fundamentals, ongoing investments in computing power, and continuous efforts to protect privacy and secure sensitive data as GenAI becomes more integrated into enterprise workflows.
AI-related risks such as adversarial attacks, model manipulation and bias, model injections, and more have garnered widespread attention for good reason. But in 2026, companies will need to prioritize fundamentals such as data security, data governance, and data hygiene, including thorough inventorying of sensitive data assets, effective classification systems, and appropriate access controls.
While we’ll see meaningful advancements in the infrastructure and platforms needed for broad adoption of agentic AI, I anticipate a trough of disillusionment in 2026 as the technology inevitably falls short of today’s sky-high expectations for productivity and ROI. Achieving automation at scale requires predictability and reliability, but chaining together non-deterministic intelligent agents can compound errors in unpredictable ways. The industry must overcome major challenges in 2026, including context sharing, memory management, and high-level orchestration.
The massive investments that AI companies are making in compute capacity is a trend I expect to continue. There is broad alignment on the fact that more computing is needed as AI adoption accelerates. However, this assumption doesn’t account for potential algorithmic breakthroughs that could dramatically improve computational efficiency, and there is a real possibility that new theoretical and algorithmic advancements could “burst” the compute-capacity bubble in 2026.
Additionally, as enterprises embed GenAI across their workflows, they’ll continue to face challenges securing it. In 2026, data privacy will elevate to a board-level priority, and the convergence of AI guardrails and PQC readiness will redefine trust as the new benchmark for digital maturity.
2026 will be a pivotal year for transformation. CIOs must prioritize building a strong foundation of high-quality data, unified master data, governed metadata, and consistent data standards across the business. This applies not only to structured data in systems but also to unstructured data such as contracts, documents, reports, messages, and files, where most enterprise knowledge actually resides. Establishing this data foundation is essential for future initiatives such as modernization, analytics, compliance, customer experience, and long-term value creation.
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