A recent Disaster Recovery Journal article marking AI Appreciation Day 2026 explores how AI adoption is evolving across the enterprise. The piece brings together perspectives from technology, security, commerce, manufacturing, and data protection leaders on how organizations can move from AI enthusiasm to more disciplined, governed, and trusted use.
The article includes perspective from Jessica Hammond, Senior Director Product Management – Gen AI at Protegrity, who highlights a central issue for the next phase of AI adoption: as AI systems become more embedded in business workflows, sensitive data is moving through more prompts, logs, retrieval systems, tools, and outputs.
AI adoption is moving beyond experimentation
The Disaster Recovery Journal article notes that AI is no longer limited to tools that help people write, search, or analyze faster. AI systems are increasingly recommending actions, triggering workflows, accessing knowledge, and operating with more autonomy across the enterprise.
That shift changes the conversation. For organizations, the question is no longer only what AI can do. It is how AI should be adopted, governed, secured, and trusted as it becomes part of daily operations.
Protegrity perspective on data protection and AI risk
Jessica Hammond explains that AI Appreciation Day is an opportunity to recognize the value AI is creating, but that adoption cannot be separated from risk. As AI moves from content generation into agentic workflows, the amount of sensitive data passing through AI systems continues to grow.
Her perspective reinforces a practical point for enterprises: reliable AI starts with data that is accurate, understood, and managed throughout its lifecycle. Organizations need to know where data came from, how it is classified, who can access it, when it can be used, and how it is protected if something goes wrong.
Why governance matters as AI becomes more autonomous
The article’s broader set of expert perspectives points to a common theme: AI value depends on the discipline organizations build around it. As AI agents retrieve knowledge, interact with business applications, generate software, and support operational decisions, governance needs to become more continuous and more closely tied to how AI is actually used.
For Protegrity, that means protecting the data layer itself. As AI systems change, models evolve, and workflows become more automated, sensitive data still needs persistent controls that can support safe use without slowing responsible innovation.
What this means for enterprise leaders
The takeaway is that AI appreciation should not mean blind adoption. Organizations that succeed in the next phase of AI will be the ones that can prove their AI systems are governed, protected, and secure by design.
That requires visibility into how sensitive data moves, policies that can be enforced consistently, and protection that follows data across prompts, retrieval systems, tools, outputs, and enterprise workflows.
Note: This summary is based on the external Disaster Recovery Journal article “AI Appreciation Day 2026: Expert Opinions on the Progress and Potential of AI” and is provided for convenience. Please refer to the original publication for full context and source reporting.