Enterprise security to be reshaped by AI, cloud & automation

Senior technology leaders are forecasting significant changes to enterprise security and IT operations as new file formats, hybrid cloud strategies, AI governance, and high-availability requirements reshape risk management in 2026.

File security gaps

George Prichici, Vice President of Products at OPSWAT, said traditional enterprise security teams are struggling to keep pace with the evolution of productivity files. While Office documents and PDFs remain a focus, he noted that attackers are increasingly turning to scripts and packages that evade inspection tools.

"Security teams remain focused on productivity files such as Office documents and PDFs, in which embedded hyperlinks and encrypted content continue to pose real risks. But this focus can leave blind spots elsewhere. Today's "files" increasingly include Python scripts and malicious npm packages - many of which slip past traditional content inspection tools. Attackers are aware of this gap and are actively exploiting it."

AI and attack surfaces

Prichici highlighted concern over artificial intelligence deployments within enterprises. He said the use of large language models (LLMs) in the workplace is outpacing the development of control frameworks, leading to increased risk.

"The enterprise rush to deploy LLMs is outpacing governance. Chatbots and AI copilots now handle sensitive data with little oversight. The result? A widening attack surface that includes data leakage, brand impersonation, and adversarial probing - a mix of insider risks and external threat actor delivery that will require stronger policy and technical controls."

Trust and third parties

According to Prichici, CISOs are reevaluating how much trust to place in third-party integrations and partners.

"Third-party vendors and 'trusted' integrations remain soft targets. CISOs are realizing that focusing budgets solely on endpoints, identity, or edge security creates imbalance: a fortified front door, but an open side entrance. The path forward is not zero trust for everything, but smarter, consistent processes that elevate defenses across all channels, including partners, APIs, and supply chains."

He emphasised the need for organisations to redefine threats and enforce new approaches to data governance and security. "Security leaders must redefine what constitutes a threat, scrutinize every data exchange, and enforce AI governance before innovation turns into exposure," said Prichici.

Cloud and hybrid approaches

Cassius Rhue, Vice President of Customer Experience at SIOS Technology, said enterprise cloud strategies will shift further towards hybrid and multicloud solutions. Rhue said these approaches are now a proven way to balance performance, costs and resilience while avoiding vendor lock-in.

"Hybrid and Multicloud solutions have become a more proven option to help organizations balance performance, cost, and resilience while avoiding vendor lock-in. More enterprises will continue to consider and adopt hybrid and multicloud architectures in 2026. As a result, HA solutions that can seamlessly operate across diverse infrastructures will become indispensable to modern IT strategies," said Rhue.

Resilient cybersecurity

Rhue said high availability (HA) technologies will become integral to enterprise security postures, not only guaranteeing uptime but also enabling rapid, low-risk maintenance and patching.

"The rising wave of cybersecurity threats is transforming how enterprises view HA clustering. In 2026, HA will not only be about achieving 99.99% uptime-it will also serve as a vital tool for maintaining security resilience. More organizations will use HA clusters to enable rapid, low-risk patching and updates, ensuring systems remain both highly available and protected against emerging threats," said Rhue.

Data management simplicity

Rhue anticipates pressure to simplify HA management for a broader range of IT teams. He expects demand to grow for platforms that automate complex tasks and minimise the need for specialist skills.

"As IT administrators and generalists are given increasing responsibility for managing complex high availability (HA) application environments, the demand for intuitive, automated HA solutions will surge. In 2026, IT teams will favor platforms that do not require specialized HA skills, minimize manual configuration and simplify cluster management. Vendors that prioritize ease of use, automation, and guided workflows will stand out as the market evolves toward accessibility for non-specialist admins," said Rhue.

DevOps and AI impact

He predicts DevOps functions will increasingly incorporate HA clustering into early-stage application design, reducing deployment risks. "Clustering tools with robust APIs, automation hooks, and real-time observability will allow rapid updates without interrupting production services. DevOps engineers will use clusters to test patches against active workloads, reducing the risk and degree of change. HA becomes a built-in feature of the delivery process-not an afterthought," said Rhue.

On the AI front, Rhue said continuous availability and observability of distributed systems will become the standard for trusted machine learning workloads.

"AI and ML workloads will run more frequently on distributed clusters and GPU-intensive systems, where downtime creates costly disruptions. In 2026, IT admins will demand high availability solutions that simplify complex AI stacks and expose full visibility into data, storage, and node health. Continuous availability becomes a prerequisite for AI reliability and trust," said Rhue.

Automation and disaster recovery

Rhue expects rising needs for automated disaster recovery aligned with more complex IT environments. "By 2026, high availability and disaster recovery IT admins will expect clustering tools to support disaster recovery locations with automate failover, verify replication integrity, and give full visibility into the entire application stack-including networking, storage, and cloud resources. Frequent cyber incidents will force DR teams to apply patches and recover systems rapidly, with clusters minimizing downtime during failover. Disaster recovery becomes proactive, not reactive," said Rhue.