In a move that could reshape how teams collaborate on AI-driven tasks, Google has introduced the ability to share custom “Gems” within its Gemini app, a feature now rolling out to Google Workspace users. These Gems, essentially tailored versions of the Gemini AI chatbot, allow individuals to create specialized assistants for specific workflows—think a marketing strategist that generates campaign ideas or a code reviewer that flags bugs. The sharing capability, announced this week, enables users to distribute these custom AI tools with colleagues, potentially streamlining productivity across organizations.

The rollout comes at a time when enterprises are increasingly integrating generative AI into daily operations, and Google’s timing appears strategic. By embedding sharing directly into the Gemini app, which is accessible via web and mobile, the company is addressing a key pain point: the siloed nature of personalized AI setups. Users can now generate a shareable link or integrate Gems into shared Google Drive folders, making it as seamless as collaborating on a Doc or Sheet.

Unlocking Collaborative AI: How Gem Sharing Enhances Team Dynamics in the Enterprise

For industry insiders, the implications extend beyond mere convenience. Administrators in Google Workspace can configure sharing permissions, determining whether Gems can be shared internally, externally, or not at all, according to details outlined in the Google Workspace Updates blog. This granular control is crucial for sectors like finance and healthcare, where data sensitivity is paramount. Early adopters report that shared Gems reduce redundancy; for instance, a sales team could deploy a single Gem trained on negotiation tactics, rather than each member building their own.

Moreover, the feature builds on Gemini’s existing integrations with Workspace apps such as Gmail and Drive, allowing shared Gems to pull contextual data from these sources. This interconnectedness could accelerate decision-making processes, as noted in a recent analysis by 9to5Google, which highlighted how sharing mimics file collaboration in Drive, complete with version history and access logs.

From Beta to Mainstream: Tracing the Evolution of Gems in Google’s AI Ecosystem

The journey to this sharing functionality has been iterative. Gems were first introduced in mid-2024 as customizable AI personas, with Workspace integration following in July 2025, per updates from the Google Workspace Updates blog. Initially limited to individual use, the expansion to sharing aligns with Google’s broader push for enterprise-grade AI, including data protections compliant with regulations like HIPAA and FERPA.

Critics, however, point to potential challenges. Sharing custom AI could inadvertently propagate biases if the original Gem’s training data is flawed, a concern echoed in discussions on platforms like TechCrunch. In a piece from TechCrunch, experts warn that without robust auditing tools, shared Gems might amplify errors across teams. Google counters this by emphasizing that shared instances retain the core model’s safeguards, including content filters and enterprise data isolation.

Strategic Advantages: Positioning Google Against Rivals in the AI Productivity Space

Looking ahead, this feature positions Google advantageously against competitors like Microsoft’s Copilot, which also offers shared AI agents but with different integration depths. Insiders suggest that Gemini’s emphasis on seamless Workspace embedding could give it an edge in adoption rates, especially among small to medium enterprises seeking cost-effective AI solutions. A blog post on Google’s official Keyword blog touts examples like a project manager sharing a Gem for task prioritization, which could shave hours off weekly planning.

Yet, the true test will be in scalability. As organizations experiment with shared Gems, metrics on usage and efficiency will reveal whether this fosters innovation or introduces new complexities. For now, Google’s update signals a maturing AI ecosystem where customization meets collaboration, potentially transforming how knowledge workers interact with technology. With the current date marking the feature’s fresh availability, early feedback from users, as reported in The Verge, indicates enthusiasm for its Drive-like simplicity, hinting at broader implications for AI-driven workflows in the coming months.