Archive360 In the Media

AI adoption is accelerating, but 2026 will be a defining year for how enterprises govern, secure, and scale it. From new regulatory scrutiny around AI-driven interactions to growing challenges with data sovereignty, security, and infrastructure, the stakes are rising fast. In the 18th annual VMblog.com Predictions Series, George Tziahanas of Archive360 shares five critical trends that will shape AI’s next phase.

Regulators require accountants to retain records for years, while privacy laws mandate the deletion of outdated data. Navigating this conflict is critical to avoiding costly fines and reputational damage. In this publication, our VP of Compliance, George Tziahanas, shares expert insight on how firms can balance regulatory retention with modern privacy obligations.

Finance teams are preparing for increased AI-driven fraud, rising employee fatigue, and stricter compliance demands in 2026 as automation reshapes how organisations manage risk. In the IT Brief article, Archive360’s VP of Compliance George Tziahanas highlights the growing challenge of synthetic documents and the need to treat AI-generated communications as regulated data while navigating evolving data sovereignty requirements.

Hoarding client data increases vulnerability to cyber-attacks and regulatory risks, as large unmanaged data sets become prime targets for breaches and penalties. In Financial Accountant, Archive360’s VP of Compliance George Tziahanas highlights why firms need a clear, defensible data retention and destruction policy to reduce risk and strengthen compliance.

In a recent Digital Insurance article, Archive360’s VP of Compliance, George Tziahanas, explores the insurance industry’s enthusiastic adoption of AI, which now drives everything from claims processing to marketing and market research. But with innovation comes risk: the resulting regulatory landscape is becoming increasingly complex, and carriers who aren’t ready may find themselves struggling to keep up.

In this AI Journal article, George Tziahanas, VP of Compliance at Archive360, explores one of the biggest hidden risks in enterprise AI adoption: false or misleading insights driven by ungoverned or outdated data. He highlights why “data quality debt” is a growing threat for organisations racing to deploy GenAI and outlines five key steps to strengthen transparency, authenticity, and control across AI data pipelines. Essential reading for leaders looking to make AI trustworthy, compliant, and truly valuable.