Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Stephen Manley, Druva, CTO
Agentic AI has begun to reshape how organizations use data to optimize operations, but it is also expanding the attack surface and enabling a new generation of cyber threats. Organizations will succeed based on how effectively they balance the costs and benefits of agentic AI.
In the coming year, organizations will face some strong currents as they navigate an AI-driven future:
The Workforce AI Revolution Begins, and No Role Will Be Left Untouched
In 2026, every role that touches data will evolve. Privacy, protection, and security teams will find that the old mindset of “privacy and security through obscurity” is unsustainable. AI agents will find, analyze, and expose every bit of accessible data because unlike human users, AI agents easily pull data from SaaS platforms, cloud services, and internal data stores, stitching together information that was previously siloed. Organizational silos won’t provide data boundaries, so teams must install explicit central governance, protection, and oversight.
Agentic AI fundamentally reshapes how data is accessed and used by collapsing the traditional boundaries that once separated systems, teams, and applications. Data that was technically accessible but rarely touched becomes routinely queried, correlated, and acted upon. As a result, assumptions about “safe” obscurity, limited exposure, or implicit separation no longer hold. Business Intelligence teams will need to evolve, as well. Agentic AI enables more people to analyze data, so their role will shift to curating data and monitoring the inputs and outputs of the AI systems. They will need to embed oversight, transparency, and ethical data handling into every layer of the process. Those that rise to the challenge will set the new standard for digital trust. Those that don’t will lose the faith of their customers.
2026: AI Fluency Becomes Survival
The next digital divide won’t separate technical from non-technical employees. Instead, it will divide the AI-fluent from the AI-hesitant. As AI agents and copilots enter the workforce, the employees who blend curiosity with AI literacy will augment their expertise with AI tooling.
This does not mean that employees should blindly trust AI agents. The employees who thrive will know how to guide, question, and validate AI outputs, turning machine intelligence into an extension of their judgment.
Those who resist will fall behind as peers move faster and smarter, so organizations that encourage AI fluency will strengthen their workforce; those that don’t will risk losing it.
AI Breaches Move From Human Mistakes to Machine Mayhem
AI security failures will go mainstream in 2026. While AI-driven social engineering has made phishing significantly more successful, the new target is the AI systems themselves. The next wave of high-profile breaches will stem from within: data leakage, prompt injection, compromised small language models, and data pipelines that were not built with proper governance or protection in mind.
Attacks on AI will devastate organizations because the AI systems are incorrectly configured, poorly understood, and inadequately monitored. The danger, however, is to the data – not to the models. CISOs and IT leaders who reframe AI risk as a data problem, not a model problem, will be better equipped to mitigate vulnerabilities stemming from how data is accessed and shared by AI. Organizations will curb AI-driven crises by making on data security, visibility, and governance a top priority for the coming year.
As agentic AI becomes embedded in core business processes, the inevitability of misconfigurations, misuse, and unforeseen failures shifts the measure of success from prevention to resilience. No organization will anticipate every way AI agents interact with data, systems, or each other. The differentiator will be how quickly enterprises detect anomalous behavior, understand the scope of impact, and recover with confidence and transparency. Leaders will be judged not by the absence of incidents, but by their ability to explain what happened, contain the damage, restore trusted operations, and maintain stakeholder trust. In an AI-driven enterprise, resilience is no longer a fallback plan. It is the primary strategy for sustaining innovation at scale.
The year ahead will challenge enterprises to rethink their strategies, embrace AI fluency, and fortify their data governance frameworks. Those who adapt will not only survive but thrive, setting new benchmarks for innovation, security, and workforce empowerment. As AI continues to evolve, the organizations that lead with foresight and resilience will define the future of enterprise success.
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ABOUT THE AUTHOR
Stephen delivers solutions to help customers extract the full potential of their data. In leading development of data management capabilities for startups and serving as CTO of the Data Protection Group at Dell EMC, Stephen found his passion in partnering with customers to solve data protection challenges for today’s enterprise and evolve modern data storage. He also spent time at NetApp as a senior technical director of data protection. Stephen is excited to connect with new customers and technology to transform how people protect, preserve, and use their data. Stephen works tirelessly to bring the latest innovative technologies to our customers, so they can always protect, manage, and increasingly obtain more value from their data.
