Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Nuha Hashem, Co-Founder & CTO, Cozmo AI
For twenty years enterprise work has centered on improving the layers that run software. Teams moved from physical servers to virtual machines. They moved again to containers and later to cloud systems. Each step improved efficiency, but none created systems that could finish work on their own. In 2026 a new pattern begins. Companies will move from managing workloads to overseeing AI workforces that complete governed tasks across distributed systems.
Progress will not be measured by how much compute a company can scale. It will be measured by how much real work an AI system can complete without slowing down ongoing operations. The cloud gave companies elastic capacity. AI workforces will give them steady execution. Many leaders will track success by how much work these systems complete with accuracy and with records that hold up during review.
Early AI copilots showed potential. They helped with writing and analysis but rarely held up inside enterprise limits. They struggled with policy rules and continuity. Many teams learned that producing text is not the same as carrying work from the first step to the last. In 2026 companies will begin to use systems that take on tasks while following the same review paths that guide their existing operations.
This change introduces a new layer in the stack. AI employees need a stable identity, a memory of past steps and a clear record of how each decision formed. They need a way to confirm who they can speak with, and which actions they can take. Most enterprises do not yet have this type of control plane. What they need is not a larger model but a straightforward way to guide each action and observe how it unfolds.
For IT leaders this shows up in daily practice.
- Teams will treat AI employees like workers with roles and permissions. These workers handle tasks inside the limits the business sets.
- Operations will need a clear view of what the system did and which facts it used. Logs must be simple enough for review teams to follow.
- Leaders will focus on work that is finished and stands up to inspection, not on raw output.
We are already seeing early signs in banking and insurance. These groups work with firm rules and maintain detailed records. AI employees help with routine calls and produce records that match the standards of other production systems. These early uses show what is possible when companies can see how work moves across each step.
Enterprise systems have always moved through new layers of abstraction. Teams build a new layer then use it to handle more work with fewer delays. Over time each layer becomes part of normal operations. In 2026 companies will begin using AI employees as part of their core stack. They will rely on these systems to carry work from start to finish. The companies that learn how to guide and review these employees will set the pace for what comes next.
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ABOUT THE AUTHOR
Nuha Hashem is the CTO and co-founder of YC-funded Cozmo AI building voice-native AI workforces for regulated enterprises.
