Copilot vs Internet Explorer: Is Microsoft's AI Assistant Falling Short?

Microsoft’s Copilot is in that awkward, headline-friendly place where an ambitious product becomes shorthand for a corporate misstep — and the comparison to Internet Explorer keeps showing up for a reason. The narrative taking hold in tech communities and some press coverage is blunt: Copilot promised to be the invisible productivity muscle behind Windows and Office, but instead it often feels like an intrusive, under‑cooked layer that doesn’t reliably do the work users expect. That critique is not just a Reddit chorus; it’s echoed in mainstream reporting and, remarkably, in internal Microsoft discussions. Microsoft CEO Nadella tells managers Copilot's Gmail and Outlook integrations ‘don't really work’ and steps in to fix them))

Background: what Microsoft promised — and what Copilot actually is​

Microsoft pitched Copilot as the next evolution of productivity: an AI assistant baked into Windows, Office apps, and cloud services that would understand your documents, calendar, and inbox, and do real work on your behalf. The product family name covers several related offerings:

• Windows / Consumer Copilot — the assistant integrated into Windows 11 (system tray, Alt+Space, and the “native” app wrapper users see).
• Microsoft 365 Copilot — the tenant-aware, enterprise-grade assistant embedded in Word, Excel, Outlook, Teams and other Microsoft 365 apps (grounded in Microsoft Graph).
• GitHub Copilot — the developer tool for code completion, refactoring and developer workflows.
• **Copilot+ on— features that leverage local NPUs in Copilot+ hardware for low‑latency or offline-capable AI tasks.

Under the marketing veneer, Copilot is not a single LLM of Microsoft’s own invention. It has been architected as a multi‑model, multi‑surface system that routes requests to whichever model Microsoft deems best for a task — historically leaning heavily on OpenAI’s GPT models and increasingly incorporating Anthropic’s Claude family and other options depending on the product and tier. Microsoft’s product teams and public docs show Copilot using Azure OpenAI endpoints (GPT variants) for many Copilot surfaces, while GitHub and enterprise offerings expose selectable or evolving model stacks.
That technical flexibility should be a strength — in principle. In practice it creates complexity for users, admins, and even Microsoft’s own internal teams.

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Why some journalists and users call Copilot “the new Internet Explorer”​

The parallel that keeps repeating​

There’s a shorthand in tech culture for a dominant vendor shipping a product that is widely available but underwhelming in practice: “the new Internet Explorer.” The gist is simple — a widely bundled, default feature that everyone has access to but that few people choose voluntarily because alternatives are objectively better.
Several threads of evidence have pushed Copilot into that comparison:

• Product critics and users report that Copilot is less competent and less flexible than alternatives such as ChatGPT, Google Gemini, or Anthropic Claude for many everyday tasks. Community reports and multiple reviews show users preferring non‑Microsoft models or services when they need consistent results.
• Internal signals suggest this is not merely a perception problem: according to reporting that reviewed an internal Microsoft email, CEO Satya Nadella criticized Copilot’s integrations with Gmail and Outlook as “for the most part don’t really work” and “not smart,” and has personally taken a hands‑on role to fix underperforming elements. That’s an unusually candid admission from the top of the company.
• Engineers and product teams at Microsoft themselves are experimenting with or preferring Anthropic’s Claude variants for internal work, especially around coding (Claude Code), which undercuts confidence in Copilot’s default stack. Independent reporting and follow‑ups indicate Microsoft’s teams are pragmatic and will pick the best model for the job, even if it’s not their flagship product.

Combine the user dissatisfaction, public critique, and internal admissions and you get a product that’s widely available but lacking the competitive polish to win enthusiastic, sustained adoption — the hallmarks of the “Internet Explorer” fate.

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Where Copilot actually does shine​

It’s important to separate marketing noise from genuine capability. Copilot does have meaningful strengths, particularly in contexts where Microsoft’s ecosystem control delivers unique value.

Deep Office and tenant grounding​

• Microsoft 365 Copilot can be tenant‑aware: when enabled and licensed for enterprise customers it uses Microsoft Graph grounding to access calendars, files, and organizational context to produce summaries, draft documents, and action items with workplace context that a generic chatbot lacks. That tight tenant integration is a real differentiator for knowledge work where user permissions and context matter.

GitHub Copilot for developers​

• GitHub Copilot remains one of the more mature, developer‑centric AI experiences. For code completion, refactoring, and in‑IDE assistance, Copilot’s toolio Visual Studio/VS Code provide tangible speedups for many teams. Even here, Microsoft’s multi‑model approach means users can pick models suited to code tasks.

Multi‑modal input: Vision, voice, and files​

• Copilot Vision (desktop vision)e of the product’s best bits — the ability to analyze screenshots or images in context on the desktop is a capability many competing chatbots don’t match out of the box. When used carefully (and with privacy awareness), vision assists shorten workflows that previously required screenshots, piecewise explanation, or manual copying.

Enterprise control and handoffs​

• For organizations willing to invest in Microsoft 365 Copilot and tenant configuration, the platform offers admin controls, audit trails, and tenant grounding that can make Copilot safer (and more useful) in regulated environments than some consumer chatbots. Those enterprise controls are a substantial benefit when they’re configured correctly.

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The practical and technical problems dragging adoption down​

Even with notable strengths, a string of recurring problems has undermined Copilot’s promise. These are not hypothetical concerns; they’re reflected in user reports, product documentation caveats, and internal corporate conversations.

1. Reliability and accuracy — hallucination remains a hard problem​

Copilot — like all large language model assistants — can and does hallucinate. That risk makes it unreliable for tasks that require high accuracy (financial statements, legal language, or compliance work). Microsoft itself has warned users not to rely on some Copilot features for tasks requiring reproducibility and strict accuracy checks. Users and admins must treat Copilot outputs as drafts to be verified, not authoritative answers.

2. Integration gaps and flaky connectors​

Some of the most damaging complaints center on connectors and integration workflows — the very features meant to make Copilot useful. If Copilot cannot reliably read a OneDrive, an Outlook mailbox, or a linked Gmail account, the assistant that promised to be a “digital worker” fails at the job. Nadella’s blunt internal critique about Gmail and Outlook integrations reflects the reality that these connectors are fragile or inconsistent in many deployments.

3. Fragmentation and licensing complexity​

Microsoft runs multiple Copilots with different capabilities and licensing models (consumer Copilot app, Microsoft 365 Copilot, GitHub Copilot, Copilot+ hardware features). That fragmentation has real costs:

• Users don’t know which “Copilot” will run for a given task.
• Licensing tiers determine access to models and feature limits, introducing confusion and occasional surprises in enterprise pilots.
• Admins face complex removal, blocking, or policy paths if they want to restrict Copilot surfaces on enterprise devices.

4. Resource and user‑experience issues​

Many users complain the “native” Copilot is still a web wrapper (WebView2/Electron‑like behavior), consuming surprising memory and feeling less responsive than a true native app. That undermines the “native experience” messaging and makes Co‑on rather than a seamless assistant.

5. Privacy surprise and consent fatigue​

Features like desktop vision and file handoffs create real privacy decisions. When Copilot prompts to read or upload files, uhrough dialogs without understanding what’s shared. For organizations handling sensitive data, that’s a liability unless strict policies, user training, and tenant controls are in place. Microsoft proand settings, but they must be proactively configured and audited.

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What users and administrators should do now — practical guidance​

If your organization is considering Cor user testing it at home, here are clear, actionable steps to get value while managing risk.

• Run pilots on scoped, non‑sensitive data. Start with a small set of users and test typical workflows. Treat Copilot outputs as drafts and measure time saved vs. verification cost.
• Audit connector permissions and usage monthly. Treat consent dialogs as data‑flow decisions. If Copilot is given access to Gmail/Outlook or third‑party connectors, log and review what’s being requested.
• Turn off model training flags if you don’t want tenant data included. Microsoft exposes toggles to exclude conversations from being used for model training; use them when privacy is paramount.
• Prepare governance if you need an AI‑free baseline. Uninstalling the Copilot app may not remove all hooks; plan imaging baselines and policy configurations for full control.
• Expect to mix and match tools. Don’t assume Copilot must be the only assistant. In many teams the most pragmatic approach is a hybrid workflow: Copilot for tenant‑grounded tasks, external models for exploratory research or generative work where Copilot underperforms.

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Microsoft’s dilemma (and the strategic choices it faces)​

Microsoft has two paths that are not mutually exclusive but will require priority and focus.

• Double down on the ecosystem advantage. Make Copilot’s integration into Microsoft 365 and Windows flawlessly reliable, and make the admin, privacy, and tenant grounding experience best‑in‑class. That requires solving connector reliability, clarifying licensing, and heavily investing in enterprise UX and trust signals. This path emphasizes differentiated value for businesses that live in Microsoft’s stack.
• Compete on model quality and openness. Where model quality matters (creative writing, open‑ended research, coding), Microsoft can’t win if users perceive other models as better. The practical response — which Microsoft seems to be pursuing internally — is model pluralism: pick the best model for the job. That means continuing to integrate Anthropic Claude models, OpenAI variants, and internal models as appropriate, and giving users or administrators explicit control over model selection. Reports show Microsoft experimenting with, and sometimes preferring, Anthropic’s models internally. That flexibility may reduce the company’s brand cohesion but will likely improve outcomes.

Either way, execution matters. The story of Internet Explorer was not that it was technically impossible to make better — it was that better alternatives emerged and users migrated away because default wasn’t good enough. Microsoft’s Copilot will avoid that fate only ifincreases reliability, and provides unique, verifiable value that competitors can’t match.

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A realistic assessment: strengths, risks, and when Copilot makes sense​

Strengths (where to consider Copilot)​

• Tenant‑grounded work: Summarizing org docs, drafting internal reports, extracting items from large corpora where Microsoft Graph grounding is a genuine advantage.
• Developer workflows: GitHub Copilot continues to deliver real productivity gains for many developers.
• Multi‑modal desktop tasks: Vision and local assistance (on Copilot+ PCs) make certain tasks faster and more natural.

Risks (where to avoid or use extreme caution)​

• High‑stakes, accuracy‑critical tasks: Financial reports, legal contracts, compliantputs must be human‑verified.
• Sensitive PII or regulated data: Don’t expose regulated content to any cloud model without contractual, legal, and technical controls in place.
• Boxes that need a single‑click native experience: If you require a lightweight, low‑memory, always‑on companion that isn’t a web wrapper, Copilot’s current consumer app may disappoint.

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What to watch next (metrics and signals that matter)​

• Connector reliability metrics — are Gmail/Outlook and Drive connectors fixed and robust? Internal pressure from leadership shows Microsoft is prioritizing this; watch for improved SLA‑like statements and fewer user complaints.
• Model transparency and selection — does Microsoft expose model picker options for organizations and users? Broader model choice and clearer documentation will be a win.
• Privacy controls and admin tooling — visible, easy‑to‑use controls for connector consent, model training opt‑outs, and tenant grounding will determine enterprise uptake.
• Internal bias toward competitors — if Microsoft’s own engineering teams continue to favor Anthropic models for mission‑critical work, that’s a signal the Copilot product team must address the performance gap or embrace multi‑model plumbing.

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Conclusion​

Microsoft’s Copilot is simultaneously one of the most ambitious and one of the most polarizing AI products in the consumer and enterprise software landscape. Its promise — a helpful, context‑aware assistant embedded wherever you work — is real and valuable in well‑scoped scenarios. Its problems — accuracy, flaky connectors, confusing packaging, and the gap between “native” marketing and web‑based reality — are also real, and they’ve put the product in a precarious position where users and even Microsoft insiders compare it to past missteps.
The good news for Microsoft is that the core levers that can change this outcome are straightforward: improve reliability of connectors; clarify licensing and model behavior; add transparent admin and privacy controls; and lean into the distinctive strengths of tenant grounding and developer tool integration. If Microsoft executes on those fronts and keeps the product honest about its limits, Copilot can be a meaningful assistant rather than a default oddity.
If it does not, Copilot risks becoming a widely distributed, widely ignored feature — the very Internet Explorer fate many critics warn about. The company’s internal urgency and model openness — even if it means using rivals’ models — are encouraging signs. But for everyday users and IT teams, the practical advice remains cautious: pilot deliberately, verify outputs, and configure governance before letting Copilot near sensitive workflows.

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Source: PCWorld Microsoft Copilot is the new Internet Explorer