AI in the workplace continues to evolve. Early capabilities enabled by generative AI focused primarily on saving employees time by summarizing meeting notes, documents, and messages, improving search and access to knowledge, and enabling basic content creation.
These capabilities are now a key element for nearly all collaboration vendors, either building generative AI into their products or enabling add-ons at additional cost. Generative AI has certainly helped, but it hasn’t fundamentally changed the nature of our work. Most of the time, it’s just a time saver.
As we move towards 2026, we are entering a more disruptive phase: the transition from generative AI to agent AI.
Generative AI is now transitioning to agentic AI. Metrigy defines agent AI as “It is an advanced AI framework that uses large-scale language models to make decisions and actions autonomously, or in other words, without human involvement. ” In reality, agent-based AI-powered assistants can assist humans on the fly or automate interactions and processes.
The main difference between the AI we’ve been using and agent AI is autonomy. GenAI is reactive (waiting for prompts to create content), while Agentic AI is proactive. It doesn’t just suggest a response. Understand your goals, break them down into steps, and execute them across different applications based on the guardrails and features your users provide.
In collaborative spaces, agent AI can monitor activity and suggest a course of action, or even act on its own based on what it knows and the permissions provided. For example, an agent can see a chat message requesting a project update and respond without human intervention. Agents can prioritize work based on what they know and learn, allowing employees to focus on the activities that are most important to the organization. You can also initiate workflows such as customer and employee onboarding based on your ability to interact with a wide range of applications.
of metrology AI for business success: 2025-26 A global survey of more than 1,100 organizations found that interest in agent AI is high, with more than 52% already familiar with the technology and nearly 36% saying they believe agent AI brings more value than generative AI. Most participants (72.9%) said their organizations plan to use agent AI to complement, rather than replace, human employees.
Agentic AI is ready to create digital twins for individual knowledge workers. A collaborative digital twin is a model trained on specific communication styles, project history, and decision-making patterns. These digital twins can reside within a specific platform, such as a CRM or ERP, or they can be integrated into broader applications via APIs, or access apps and data via Model Context Protocol (MCP) servers.
The functionality of a digital twin is limited only by the access to data and apps and the capabilities granted to the digital twin. In the future, digital twins will be able to handle multi-step processes such as identifying project delays, rescheduling necessary stakeholders, and updating the project team via chat channels, all without human intervention.
Apexanalytics, a supply chain risk management platform vendor I recently spoke to, is working on implementing this functionality within its internal platform. Digital twins learn not only from their human counterparts, but also from the knowledge available throughout the organization. The ability to respond to queries can persist long after the original employee leaves the company.
Examples of digital twin capabilities include:
-
Attend meetings for you: Digital twins do more than just record meetings. It represents your “point of view” based on past data and only flags when a decision requires uniquely human intuition.
-
Manage inquiries: Digital twins respond to everyday questions such as “What is the status of X?” Get and ping real-time data from project folders, messages, and connected project management, CRM, operations, and ERP apps.
-
Project orchestration: Digital twins autonomously guide team members toward deliverables, keeping projects on track while you focus on high-level strategy.
Agentic AI is changing the way we interact with work. We’ve been debating for years whether our work “hub” is our inbox, a team chat app, or a role-specific app like ERP or CRM. In the not-too-distant future, the answer could be an AI-enabled browser.
New entrants like Dia, Kosmik, and Perplexity Comet are reimagining the browser as an operating system for agents, alongside established players like Microsoft Edge Copilot and browser plugins like Anthropic’s Claude for Chrome.
These browsers do more than just display web pages. They interact with them. In-browser agents can read different messaging and email apps, check calendars, and write responses, bridging the gap between siled SaaS applications that previously never communicated with each other. Instead of checking in with multiple activity streams, employees can start their day with a report from a bot in their browser. From there, you can invoke customized dashboards and have the AI agent perform actions on your behalf. AI browsers could also provide an interface for vibecoding, allowing employees to create their own bots and apps to optimize their work.
Of course, this change brings significant challenges. As I pointed out in a previous post, Security and data governance remains the “elephant in the room”. When agents perform actions on behalf of users, the potential for automated mistakes and data leaks increases exponentially.
Organizations need to move beyond “AI policies” to “agent governance” frameworks that define exactly what AI twins can and cannot do. Recent developments in Metrigy Workplace collaboration and contact center security and compliance: 2026 A global survey of more than 300 companies found that 65.2% already have a security and compliance strategy in place for AI agents. Another 20.9% will be acquired by the end of this year.
Agent AI will fundamentally change the way people work and interact. IT and business leaders must proactively identify ways to leverage agent AI to improve productivity and reduce friction. They must also do so in a way that protects against security risks and meets compliance requirements.
—
About metrics: Metrigy is an innovative research and advisory firm focused on rapidly changing areas such as workplace collaboration, digital workplaces, digital transformation, customer experience, and employee experience, as well as several related technologies. Metrigy provides technology providers and enterprise organizations with strategic guidance and informative content backed by key research metrics and analytics.
