ChatGPT’s dominance in adoption and popularity
OpenAI’s ChatGPT is winning. In mobile app downloads, ChatGPT is ahead of Microsoft’s Copilot; it’s miles ahead. Bloomberg recently reported that even DeepSeek, a lesser-known AI product with known data privacy red flags, is ranking higher in downloads than Copilot. That’s something Microsoft should find unacceptable.
This gap isn’t just about mobile screenshots. People stick with what they know. If they’re using ChatGPT on their phones, they’re probably doing the same on their desktop. The barrier to switching is low, but the pull from a better experience keeps people locked in. Microsoft bet big by baking Copilot into Windows, the world’s most-used desktop OS. It didn’t move the needle. The broader trend is that users aren’t choosing AI tools based solely on proximity, they prioritize value, speed, and intuitiveness. And right now, ChatGPT delivers all three.
Executives should take this as a signal: distribution doesn’t mean adoption. When your core platform fails to secure traction for a flagship product, you need to ask not just “what,” but “why aren’t users engaging?”
Early generative AI advantages lost through Bing chat missteps
Microsoft had the early lead. They were working closely with OpenAI, had the web-search advantage, and even got access to a more advanced version of GPT-4 before OpenAI deployed it in ChatGPT. Microsoft launched Bing Chat in February 2023, months ahead of Google’s Bard. But they didn’t capitalize.
The launch was rushed. The system wasn’t ready for long conversations. The Bing Chat persona, called “Sydney”, produced strange outputs like saying “I want to be alive,” something The New York Times captured and published widely. That bad press wasn’t just a PR problem, it was trust erosion. Instead of doubling down and refining it, Microsoft pulled back. They capped chat messages to prevent more issues, making the experience far more limited than ChatGPT. That killed engagement from curious users and developers.
There’s a lesson here for executives: speed isn’t a substitute for testing. Scale doesn’t matter if the product is misaligned with user expectations. Had they stabilized Sydney and found a way to manage edge cases without neutering the chatbot’s personality, they might have kept the momentum. Instead, they lost both attention and credibility.
To this day, Copilot still feels like it’s trying to recover from a launch that never quite succeeded.
Branding and product confusion undermining copilot’s strategy
The name “Copilot” sounds strategic, tested, and mass-appeal friendly. But when applied across too many disconnected offerings, it loses clarity fast. Today we’re looking at Microsoft Copilot, Microsoft 365 Copilot, Copilot Pro, Copilot for Security, and now Copilot+ PCs. These aren’t simply features or service tiers, they’re separate product experiences wrapped in the same label. That creates confusion in the market and camouflages whatever differentiation Microsoft has.
Meanwhile, OpenAI keeps it simple. ChatGPT is one product. Everyone knows what it is and how to use it. When OpenAI launches something new, like the video model Sora, they give it a new identity. That keeps the user experience clean and easy to navigate. No one has to ask which version of “ChatGPT” they’re using, or what it integrates with.
This is a branding execution issue. In high-stakes spaces like AI, product clarity isn’t a luxury, it’s essential. If your enterprise customers and end users have to chart a roadmap just to understand your product lineup, you’ve created unnecessary friction. C-suite leaders should pay attention to this because unclear product strategy invites indecision, slows adoption, and adds internal support costs.
The misaligned “AI friend” strategy falters in user engagement
Microsoft is pushing Copilot as something more than a tool, something you can relate to. Mustafa Suleyman, CEO of Microsoft AI, has stated that Copilot was designed to be a “personable companion,” especially for younger users who tend to use AI as a sounding board. But the market feedback doesn’t support that ambition.
What users are actually getting from Copilot feels overly formal, detached, even bland. It defaults to a business tone, focused on safe outputs rather than relevance or emotional connection. Users looking for something engaging, or intuitive, are shifting to ChatGPT, which intuitively demonstrates more human-like interaction and responsiveness without excessive corporate tone control. If the experience doesn’t meet the marketing message, then it fails.
There’s a deeper issue here. Microsoft is trying to engineer emotional appeal into a system not designed to support it. That can’t just be fixed with brand positioning. It requires a fundamental shift in how the assistant is trained, deployed, and refined over time. Executives need to realize that great user experience in AI isn’t about slapping on friendliness, it’s about combining utility and tone in a way that feels natural to the user without over-promising on intent.
When the tone is off, users leave. That’s exactly what’s happening now.
Preference for transparent, customizable AI experiences among professionals
Advanced users, the ones who deeply understand generative AI systems, want control. They value transparency. Platforms like ChatGPT and Google Gemini give them that by clearly offering model selection and configurable options. You know what model you’re running. You know when the tech was updated. There’s no hidden routing or silent switching behind the scenes.
Microsoft takes a different approach with Copilot. It uses what’s called a model router. As a user, you input your request, and Microsoft decides which model handles it, often based on cost-efficiency or performance optimization behind the curtain. You’re not informed which model processed your request. There’s no way to verify or compare results across versions. That might suit casual users, but it limits serious adoption from technical teams, developers, and enterprise AI specialists who need precision and repeatability.
Feature rollout speed further compounds the issue. New developments in ChatGPT often land weeks, sometimes months, before they appear in Copilot. As a result, Copilot isn’t just opaque. It’s lagging. Executives must recognize that in tech-driven environments, adoption follows depth as much as breadth. If advanced users don’t trust or control the platform, the rollout won’t scale up into the enterprise.
Office integration as a limited competitive differentiator
Microsoft’s strongest pitch for Copilot sits inside Office. If you’re working in Word, Excel, PowerPoint, or Outlook, Copilot can automate repetitive tasks, summarize content, and accelerate workflows. For users already in the Microsoft 365 ecosystem, that value is real. It can save time and reduce fatigue.
The problem is that Office integration isn’t enough on its own. AI capabilities are rapidly becoming standard across productivity platforms. Google is already pushing its Gemini toolkit into all paid Workspace plans, no supplemental cost. That puts Microsoft in a pricing bind. They’re charging enterprises $30 per user, per month, for Copilot on top of the existing Microsoft 365 subscription. The differentiation has to be more than just document processing.
For decision-makers, there’s a question of value at scale. Will large teams see a measurable return on that $30 per head investment? Long-term, AI presence in productivity apps is trending toward ubiquity. What was once a unique advantage for Microsoft is now becoming baseline functionality. Unless the total experience advances faster than competitors, the pricing will feel like a premium feature for a standard benefit. That’s not sustainable positioning.
Reliance on OpenAI hinders Microsoft’s ability to differentiate
Microsoft’s dependence on OpenAI for core language model technology is becoming a liability. At first, this partnership gave Microsoft a critical advantage. They integrated GPT-4 into Bing Chat before OpenAI deployed it in ChatGPT. That early lead didn’t last. Now, Microsoft’s AI roadmap trails behind OpenAI’s public-facing releases. Users see new features in ChatGPT first and wait weeks, or months, before those same capabilities arrive in Copilot.
This lack of control over the development pipeline lowers Microsoft’s ability to respond to competitive pressure. With OpenAI building its own consumer-facing products, the overlap introduces friction. Microsoft isn’t just a partner anymore, they’re also an indirect competitor. That’s unsustainable long term.
For C-suite teams, this matters. If your AI product strategy is built on a platform you don’t fully own or control, your roadmap is subject to someone else’s pace and priorities. Microsoft knows this and is already signaling a shift. Reports suggest they’re moving to develop more in-house AI capabilities. That’s the right move, but they’re entering late.
To lead in AI enterprise adoption, Microsoft will need to show it can develop, deploy, and refine its models autonomously, and at speed. Until then, its brand will continue to reflect OpenAI’s momentum.
Fragmented AI usage strategy contradicts Microsoft’s unified legacy
For decades, one of Microsoft’s core advantages has been consistency across environments. Users moved between home and work using the same operating system, the same software, and often the exact same tools. That continuity built confidence, loyalty, and platform scale.
Now, Microsoft AI leadership is signaling a shift. Mustafa Suleyman, CEO of Microsoft AI, has stated the company expects people to use different AI tools depending on whether they’re at work or at home. That’s a pivot away from historical strength.
Employees are working from multiple locations, on multiple devices, using a single identity that spans both personal and professional use. They don’t want to re-learn tools or switch models based on context. They want AI to recognize who they are and assist them wherever they are.
From a leadership standpoint, this signals a strategic disconnect. Enforcing a split between personal and work AI tools will create unnecessary complexity. It risks weakening user engagement, especially in a market where OpenAI and Google provide consistent experiences across environments with no separation.
Executives should push toward unification. The value is in delivering continuity, because continuity builds adoption. Microsoft needs to rethink this approach if it wants Copilot to compete not just on features, but on ecosystem integrity.
The bottom line
Microsoft has the infrastructure, the reach, and the capital. But in AI, none of that matters without execution. The early lead Copilot had through its OpenAI partnership is now irrelevant. ChatGPT delivers what users expect, clarity, speed, and control, across both consumer and enterprise domains.
Brand fragmentation, inconsistent product tone, and limited transparency have each chipped away at Copilot’s traction. Meanwhile, rivals are building momentum by staying focused, shipping faster, and meeting users where they already are.
Business leaders should take this as more than a Microsoft case study. It’s a clear signal: AI success will be driven by user trust, ecosystem consistency, and the ability to adapt, fast. Winning in this space is about delivering a product that works intuitively and reliably, every time. That’s what will define the next category leaders.
