Migration Checklist: Moving Users from Chrome to a Local-AI, Privacy-First Browser

Start here: why your dev and IT teams are tired of managing Chrome

Switching browsers at enterprise scale feels like changing the OS on a million desks. Users complain about lost bookmarks, critical extensions, and subtle UX differences. Security teams worry about data exfiltration and long-tail telemetry. Developers worry about web-app compatibility and subtle rendering changes. Meanwhile, a new class of privacy-first browsers that run local AI models on-device — and thus reduce cloud exposure and latency — emerged in late 2025 and early 2026, forcing organizations to decide: keep Chrome for inertia, or invest in a modern Chrome alternative that better aligns with privacy and on-device intelligence?

Quick read: the executive summary (inverted pyramid)

• Top priority: Inventory Chrome extensions, critical integrations, and enterprise policies.
• Security first: Validate local-AI data flows, disable network egress for models unless approved, and integrate browser DLP.
• Compatibility testing: Use automated Playwright/Selenium suites; run a 2-week pilot with power users.
• UX trade-offs: Expect slower feature parity for niche Chrome-only extensions and sync differences; plan mitigations.
• Deployment: Phased rollout by org unit with rollback paths and co-existence for a transition window.

Why this matters in 2026: trends shaping browser migration

The landscape changed in late 2025 and into 2026. Vendors focused on local-first AI introduced desktop and mobile experiences that run compact LLMs on-device, reducing cloud dependency and improving privacy. Examples include mobile local-AI browsers gaining traction and Anthropic's Cowork preview (Jan 2026) expanding AI desktop capabilities with local file system access for agents. Enterprises now weigh the benefit of local AI — faster internal search, redacted telemetry, offline capabilities — against integration and governance costs.

Regulatory pressure also increased: more jurisdictions require demonstrable data residency and minimal external data sharing, which makes a privacy browser that keeps AI inference local an attractive alternative. But a migration without a plan increases helpdesk load, causes productivity loss, and introduces security gaps. This playbook focuses on the practical steps to migrate with low friction.

Enterprise migration playbook: step-by-step checklist

1) Discovery & inventory

Start by building a complete inventory. You can pply automated telemetric scans and lightweight user surveys.

• Collect a per-user list of installed extensions, bookmarks, saved passwords, and profiles.
• Tag applications by criticality: mission-critical, business-critical, optional, personal.
• Identify dependencies: SSO, IDP integrations, corporate proxies, VPNs, and enterprise SAML/OAuth apps.
• Map OS platforms: Windows, macOS, Linux, iOS, Android — mobile local-AI browsers are maturing fast in 2026.

Actionable deliverable

Create a CSV named extension_inventory.csv with columns: user, extension_id, extension_name, version, criticality, notes. That file becomes your canonical mapping input for testing.

2) Extension compatibility mapping

Extensions are the single biggest source of migration friction. Your aim is to build an extension compatibility matrix and then an approved alternatives list.

• Classify extensions by capability: content-blocker, password manager, dev-tool, SSO, accessibility, custom enterprise extension.
• Flag Chromium-only native-apis (eg webRequest with blocking behavior) vs standard WebExtensions APIs.
• Check manifest versions: many alternative browsers implement Manifest V3 and may restrict background service workers or blocking APIs.

For enterprise-owned extensions, plan code changes to conform with the target browser's API set. For third-party extensions, identify vendor alternatives or request vendor support for the target browser.

3) Automated compatibility testing

Manual testing won't scale. Use headless and real-browser automation focused on both functional and visual regressions.

• Use Playwright with multiple engines (Chromium, WebKit) to detect rendering and feature regressions.
• Run targeted extension smoke tests: loading extension, exercising core actions, verifying content scripts and UI injection.
• Automate policy tests for enterprise settings (bookmarks import/export, managed preferences, SSO flows).

npm install -D @playwright/test

# sample test pseudocode using single-quote strings
const { test, expect } = require('@playwright/test')

test('login and extension smoke', async ({ browser }) => {
  const context = await browser.newContext()
  const page = await context.newPage()
  await page.goto('https://intranet.corp')
  // exercise SSO
  await page.click('#login')
  // validate extension UI
  await page.click('#extension-button')
  expect(await page.textContent('#status')).toBe('ok')
})

4) Security controls and governance

Local AI changes the threat model. In 2026, on-device LLMs reduce cloud exposure but introduce new risks: local model poisoning, unauthorized local file access by AI agents, and model telemetry leakage. Your security controls must cover these areas.

• Model data flow governance: ensure local models do not exfiltrate sensitive context. If the browser supports a model store or plugin, require policy to disallow networked model downloads unless vetted.
• Data Loss Prevention (DLP): integrate browser DLP to block sensitive copy/paste, uploads, and screenshotting when local-AI agents are active.
• Endpoint controls: use MDM/endpoint management to enforce app integrity, disk encryption, and tamper detection for local model artifacts.
• Authentication: enforce SSO, MFA, device-bound attestations, and per-application session policies. Use enterprise CDPs or zero-trust policies for context-aware access.
• Network policies: restrict outbound connections from the browser's helper processes and block unknown telemetry hosts at the firewall unless explicitly approved.

Configuration example: managed policies

Many privacy-first Chromium-based browsers accept enterprise policy bundles similar to Chromium. Prepare a baseline policy that disables auto-updates for non-approved extensions, blocks external extension stores, and enforces safe browsing settings. Exchange with your vendor for the correct policy keys.

5) UX trade-offs and mitigation

No migration will be 100% feature-parity. You must acknowledge trade-offs and proactively mitigate them.

• Sync differences: Password and bookmark sync may use vendor-specific encrypted stores. Plan export/import tooling and educate users about what changes.
• Extension gaps: Some Chrome-only extensions may not exist. Provide alternative workflows or host internal utilities as web apps that work across browsers.
• Developer tools: DevTools forks or missing features could impact front-end teams. Run developer-focused pilots and gather feedback early.
• Performance: Local AI can improve perceived latency for AI features but can increase CPU usage. Offer device capability baselines and options to opt out of heavy local inference on laptops.

Practical rule: migrate power users and engineers last — they reveal edge cases early and will help harden the rollout.

6) Pilot, phased rollout, and coexistence

Deploy in waves. A recommended sequence:

1. Pilot with 1-2% of users: include helpdesk staff and a cross-functional engineering team.
2. Targeted rollouts by org unit where privacy or regulated data is a priority (legal, R&D, HR).
3. Broader rollouts with a 3-month overlap window where Chrome remains available as a fallback.
4. Final cutover with enforced default browser policy when extension compatibility and security baselines are met.

During coexistence, configure telemetry to tag which browser is used for sensitive apps so you can detect any policy violations or usage anomalies.

7) User training, documentation, and support

User adoption is a people problem as much as a technical one. Invest in concise, role-based training.

• Prepare a one-page cheat sheet: how to import bookmarks, enable enterprise passwords, install approved extensions.
• Run 30-minute virtual workshops for teams, focused on changes that matter to them.
• Create a searchable FAQ and a video walkthrough for common tasks.
• Staff helpdesk with migration-specific runbooks and escalation paths for extension or SSO issues.

8) Monitoring, KPIs, and rollback

Define success metrics up-front.

• Adoption rate by org unit and role.
• Helpdesk ticket volume and mean time to resolution for browser-related tickets.
• Security events originating from the new browser vs baseline.
• Performance metrics: page load times for critical apps, CPU usage when local AI runs.

Always keep a tested rollback plan that restores Chrome as default and re-applies enterprise policies. Rollback should not mean data loss — design migration tooling to preserve bookmarks and credentials.

Practical artifacts: templates and snippets you can use

Extension mapping CSV template

user,extension_id,extension_name,criticality,target_status,alternative_extension_id,notes
alice,abcd1234,Password Magic,high,required,keep,'Enterprise password manager; vendor supports target browser'
bob,wxyz9876,DevTab,medium,optional,replace,devtab-lite,'Feature differences in background API'

Playwright-based extension smoke harness (pseudocode)

// run against target browser executable path
const { chromium } = require('playwright')
;(async () => {
  const browser = await chromium.launch({ headless: false, executablePath: '/path/to/privacy-browser' })
  const context = await browser.newContext()
  // load extension (if the browser supports loading unpacked extensions)
  await context.addInitScript({ path: '/path/to/extension/bootstrap.js' })
  const page = await context.newPage()
  await page.goto('https://critical.app.corp')
  // perform smoke assertions
  // ...
  await browser.close()
})()

Case study: 10k-user migration in 6 months (high level)

Synopsis: a 10k-user enterprise in finance replaced Chrome with a privacy-first Chromium fork that offered an optional on-device LLM for internal search. The migration prioritized security and compliance:

• Months 0-1: inventory and pilot with 100 users (helpdesk & legal). Created extension compatibility matrix and decided to vendor uplift two enterprise extensions.
• Months 2-3: hardened DLP, integrated IdP, tested SSO flows across hidden SAML partners, and limited local model downloads via endpoint policies.
• Months 4-5: phased rollout by business unit. Maintained Chrome for dev teams and power users. Trained 500 champions to field first-line support.
• Month 6: full policy enforcement and migration completed with 10% reduction in cloud-hosted AI requests (due to local inference) and a measurable drop in third-party telemetry.

Licensing, compliance, and procurement notes

Local models and privacy browsers introduce procurement nuances. Contracts must address:

• Model licensing: are model weights redistributable? What security controls does the vendor provide for model integrity?
• Support SLAs for enterprise features, extension compatibility, and security incidents.
• Data processing agreements and attestations around telemetry and telemetry opt-out mechanisms.
• Export compliance for certain model technologies — validate with legal if your organization operates in regulated verticals.

Final recommendations and frank trade-offs

Migration to a privacy browser that supports local AI can reduce cloud exposure, improve response times for knowledge work, and help meet regulatory goals. But it is not a plug-and-play replacement for Chrome in every case. Expect:

• Initial productivity dips for users reliant on niche extensions.
• Additional engineering work to adapt enterprise extensions and to implement DLP and zero-trust integration.
• Long-term gains in telemetry minimization, offline resilience, and lower recurring cloud costs for AI inference.

Practical advice: treat migration as a multi-quarter program. Prioritize security, automate compatibility testing, and keep users informed. Ship a strong pilot, iterate quickly, and maintain a co-existence window that preserves Chrome for power users until parity is acceptable.

Actionable deployment checklist (copy and use)

• Inventory extensions and apps (create extension_inventory.csv).
• Run automated Playwright/Selenium compatibility tests for top 200 web apps.
• Map extensions to alternatives and plan enterprise extension updates.
• Define and deploy baseline managed policies: disable external stores, enforce SSO, lock model downloads.
• Pilot 1-2% users for 2-4 weeks including helpdesk staff.
• Phased rollout with targeted training and champions for each BU.
• Monitor KPIs and be ready to rollback per unit if needed.

Closing: make the decision that aligns with your risk profile

If your organization values reduced external AI telemetry, wants on-device assistants for faster internal workflows, and faces regulatory pressure on data residency, migrating to a privacy-first browser with local AI is a strategic move in 2026. If you prioritize complete extension parity with minimal change, maintain Chrome for specific user cohorts while evaluating alternatives in parallel.

Next step: download the extension inventory CSV template, run the Playwright smoke harness against a sample group, and open a migration project in your PM system with a 90-day pilot target.

Need help operationalizing this playbook? Contact our team for a migration readiness review, compatibility audit, and pilot plan tailored to your environment.

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