Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Michael Gray, CTO of Thrive
As organizations prepare for the year ahead, many are reassessing how artificial intelligence, security, and trust will influence their strategies and operations. AI continues to evolve at a rapid pace, creating opportunities for innovation while also introducing new forms of risk. Questions around model integrity, authenticity, and long-term market stability are beginning to shape how businesses plan for growth and prepare for disruption. As these pressures intensify, companies are recognizing that the systems they deploy must be both technically sound and resilient to emerging threats that challenge traditional safeguards.
The following predictions explore how 2026 may unfold across AI security, digital trust, and the shifting dynamics of the AI market. They highlight the increasing need for organizations to strengthen verification, safeguard model reliability, and take a more disciplined approach to AI adoption as the landscape becomes more complex.
The AI Breach Reckoning
2026 will bring cybersecurity’s AI moment of truth. The first major public breach of an AI model will expose how fragile model pipelines and data integrity really are. Attackers will learn to ransom or corrupt models used in high-stakes industries like insurance and finance, forcing companies to treat AI as critical infrastructure rather than an experimental tool.
The fallout will drive investment in model governance and �AI firewalls’ that verify system output for accuracy and trustworthiness, proof that advanced defenses mean little without getting the basics right. In the aftermath, regulators and security leaders will face growing pressure to define standards for AI integrity before public trust erodes further.
The Trust Crisis
As deepfakes and generative AI continue to advance, the line between real and artificial will blur beyond recognition. Voice, video, and written communication will all be weaponized, making authenticity nearly impossible to verify. Phishing emails will mimic CEOs perfectly, and fake video calls will fool even trained professionals.
This erosion of trust will force enterprises to build new verification layers into daily operations, changing how organizations confirm identity, share information, and make decisions in the digital world. The next frontier of cybersecurity won’t just defend systems; it will defend perception itself.
The AI Bubble Bursts
The artificial intelligence sector is heading for a sharp correction: less of a bubble burst and more of a tidying-up. Companies will need to take a step back to understand where they are in their AI deployment and master what they have before they scale.
The surge of infrastructure startups racing to build foundation models will give way to mass consolidation as major players absorb or outlast them. By contrast, domain-focused AI, tools built for specific industries like healthcare, legal, and cybersecurity, will thrive by delivering tangible, measurable, real-world results. The winners of this next phase won’t be those with the largest models, but those that prove the clearest value. Consolidation will usher in a more disciplined market, where substance and specificity finally outweigh hype.
Looking ahead to 2026, organizations will face rising pressure to ensure the integrity, security, and authenticity of the AI systems they rely on. The year will demand a deeper focus on protecting models, validating information, and approaching AI investments with clarity and discipline. As threats escalate and the market recalibrates, success will depend on a strong foundation of trust and a commitment to deploying technology in ways that are both secure and strategic.
The coming year will also challenge businesses to adapt to new realities in cybersecurity, verification, and AI market consolidation. Companies that prioritize resilience, strengthen their safeguards, and make thoughtful decisions about where and how they scale their AI capabilities will be better positioned to navigate uncertainty. Organizations that invest early in robust governance practices and adopt a proactive stance toward AI risk will gain a significant advantage as expectations for accountability continue to rise. As 2026 unfolds, trustworthiness and disciplined innovation will become essential components of sustainable growth.
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ABOUT THE AUTHOR
Michael Gray has been a strong technology leader at Thrive over the past decade, contributing in the consulting, network engineering, managed services and product development groups while continually being promoted up the ladder. Michael’s technology career began at Dove Consulting and later Praecis, a biotechnology startup that was acquired by a top-five pharmaceutical firm in 2007. Serving in his current role, he is now responsible for Thrive’s R&D, technology road-mapping vision, while also heading the security and application development practices. He is a member of several partner advisory councils and participates in many local and national technology events. Michael has a degree in Business Administration from Northeastern University and he also maintains multiple technical certifications including Fortinet, Sonicwall, Microsoft, ITIL, Kaseya and maintains his Certified Information Systems Security Professional (CISSP).
