Screenshots leaked on January 31 show Google quietly trialing a powerful Gemini upgrade. The beta control, titled “Import AI chats,” promises seamless conversation portability from ChatGPT and Claude. Early coverage suggests Google aims to erase switching friction that still cages many enterprise teams. Consequently, the move spotlights Interoperability as the next competitive front in generative AI. However, privacy implications and technical unknowns linger behind the polished leaks. This report examines the feature’s mechanics, strategic motives, and enterprise considerations. Throughout, we measure potential benefits against emerging risks. Additionally, we highlight how User Migration pressures influence the timeline for public release. Meanwhile, technical leaders must prepare policies for imported data that could feed Google’s training pipelines. Our analysis relies on TestingCatalog screenshots, secondary verification by Android outlets, and Google’s published privacy hub. Therefore, readers gain a concise yet rigorous briefing suitable for immediate strategic planning. Let us unpack what the beta actually delivers and why Interoperability will define 2026 platform choices.

Gemini Import Feature Overview

TestingCatalog discovered the Import AI chats toggle buried inside a pre-release Gemini build. Moreover, screenshots display the option under the familiar plus icon where users attach files. A pop-up instructs users to export conversations from another assistant, then upload the resulting archive. Consequently, Gemini would ingest the ZIP and store threads within Gemini Apps Activity. Import status appears labeled beta, suggesting limited reliability during current testing. No Google announcement accompanies the leak, and most journalists cannot replicate the button. Nevertheless, Android Authority confirmed matching resource strings inside decompiled APKs. These clues indicate serious engineering investment rather than a transient experiment. Interoperability emerges as the clear product narrative backing that investment. Early adopters expect quicker User Migration once the control reaches stable channels. In summary, Google now tests a practical path from competitor chat archives into Gemini. The groundwork signals imminent production rollout once stability improves. Next, we examine why Interoperability shapes user choice and market share.

Interoperability Driving User Choice

Platform stickiness stems from conversation history accumulated across months of iterative work. Therefore, deleting or manually copying that history deters experimentation with rival assistants. Google’s import tool targets this barrier directly. Consequently, Interoperability neutralises lock-in and invites professionals to compare responses across ecosystems. Android Authority framed the move as a “switching accelerator” likely to influence enterprise procurement cycles. Meanwhile, User Migration already shows traction through unofficial scrapers like Magai and RecurseChat. Those services parse ChatGPT exports into standardized formats for other clients. Google appears willing to formalize the same pipeline within Gemini itself. Moreover, cross-platform data portability could pressure competitors to offer reciprocal export paths. That dynamic mirrors messaging-app history where data portability eventually became regulated. Reduced lock-in elevates user agency while rewarding platforms that innovate quickly. Interoperability therefore emerges as a decisive enterprise procurement metric. Understanding technical limitations clarifies whether the beta can meet that expectation.

Technical Workflow And Unknowns

At first glance, the workflow seems simple. However, several technical gaps could hinder seamless execution. OpenAI exports a ZIP containing conversations.json plus media folders. Anthropic uses a similar layout yet different metadata keys. Gemini must parse both variants, preserve timestamps, and maintain message order. Moreover, attachments require secure hosting after import because links inside JSON expire. Branching threads, a frequent ChatGPT pattern, complicate linear mapping into Gemini’s interface.

After decompiling strings, testers highlighted these unresolved variables:

• Accepted file extensions beyond ZIP and JSON remain unspecified.
• Import success rate during beta builds remains unverified.
• Whether multimedia stays linked or embedded is unclear.
• Reciprocal Gemini export capability is still absent.

Consequently, administrators should pilot imports on non-production data before wide rollout. Robust logging will help quantify Interoperability quality across diverse archive structures. Technical ambiguity could stall enterprise adoption until Google releases detailed specifications. Clear guidance will prove vital for smooth User Migration at scale. The next section explores privacy stakes attached to those specifications.

Privacy Policies And Risks

Importing third-party conversations moves sensitive information under Google’s privacy framework. Google’s Gemini Apps Privacy Hub states that saved chats may train future models. Furthermore, human reviewers can sample stored content for quality evaluations. Users can disable Keep Activity, yet temporary chats still persist for 72 hours. Imported archives join the same retention schedule unless separate toggles appear. In contrast, OpenAI currently processes export requests offline and never resubmits them into training data. Therefore, enterprises must evaluate whether Interoperability outweighs exposure of proprietary prompts. Legal teams should map obligations under GDPR data-portability and confidentiality clauses. Moreover, consent banners could require adjustments to reflect multi-platform data flow. Privacy controls exist yet demand proactive configuration for each imported dataset. Neglecting them risks reputational damage and regulatory penalties. Competitive forces further complicate these privacy calculations.

Competitive Landscape And Standards

Generative AI providers now race to capture enterprise mindshare. Microsoft recently integrated Copilot across Office, yet lacks inbound chat import capabilities. Consequently, Google’s planned feature could undercut that advantage. TestingCatalog’s leak also energized third-party toolmakers who already facilitate User Migration between assistants. Standards bodies have not yet proposed a universal conversations schema. However, informal consensus around conversations.json hints at a de facto standard. Interoperability leadership could allow Google to drive formal standardization discussions. Meanwhile, regulators may view data portability favorably, echoing European telecom precedents. Market share will likely shift toward platforms embracing open archives and quick imports. Therefore, keeping pace requires both feature velocity and transparent standards engagement. Enterprises must translate these trends into concrete implementation roadmaps.

Implementation Guidance For Enterprises

CIOs should craft phased pilot programs before enabling wide chat imports. Firstly, select a non-production workspace containing representative but non-sensitive archives. Subsequently, monitor import fidelity using automated diff tools against original JSON. Meanwhile, instruct users to disable Keep Activity until privacy impact assessments finish. Next, update internal acceptable-use policies to reflect cross-platform data ingestion. Legal counsel should review Google’s privacy hub plus upstream assistant terms for export reuse constraints. Additionally, professionals can enhance governance expertise with the AI Ethics for Business™ certification. That coursework covers data stewardship, bias mitigation, and audit frameworks. Consequently, teams align technical rollouts with ethical best practices. Structured pilots, robust audits, and ongoing training minimize operational surprises. These steps position enterprises for smooth User Migration when the feature launches. Finally, we explore future milestones and unanswered questions.

Future Outlook And Questions

Gemini’s import capability remains locked inside internal builds without a public timeline. Google may surface the beta during I/O 2026, aligning with broader Gemini releases. Nevertheless, critical unknowns persist about accepted file formats and attachment handling. Equally pressing is whether exports from Gemini will gain parity, satisfying regulators demanding bilateral portability. Furthermore, clarity on per-import consent prompts could assuage enterprise compliance teams. Subsequently, market adoption will hinge on documented success rates for large archives. Android outlets plan further APK teardowns, while TestingCatalog promises hands-on videos once access expands. Consequently, technology leaders should monitor update channels and allocate experimentation budgets. Near-term releases will likely focus on stability and documentation. Continuous vigilance ensures organisations are ready when the import button finally lights up.

Conclusion

Google’s planned import tool signals a pivotal chapter for conversational AI platforms. The feature promises smoother User Migration while intensifying competitive pressure across the market. However, privacy governance and technical readiness will ultimately determine rollout success. Forward-thinking enterprises should pilot workflows, refine policies, and train staff before public availability. Moreover, continuing education such as the AI Ethics for Business™ certification empowers leaders to navigate emerging data dilemmas. Stay informed through verified leaks, official changelogs, and rigorous internal testing. Act today to ensure your organisation takes full advantage the moment Gemini opens the gates. Consequently, early preparation converts uncertainty into competitive benefit. Download, test, and learn before your rivals do.