2025 was the year of announcements. 2026 is the year of disillusionment and real results. Microsoft Copilot, Google Gemini in Workspace and Salesforce Einstein GPT have arrived in production environments. The question is no longer "Can AI write emails?" but "How much productivity do we actually gain and at what cost?"
Microsoft Copilot: The De Facto Standard
Microsoft has executed the most aggressive rollout. Copilot for Microsoft 365 is available to an estimated 180 million users in 2026. The strength: integration into Word, Excel, PowerPoint, Outlook and Teams at a level no competitor can match.
What really works:
- Meeting summaries in Teams: Reliable, saves 15-20 minutes per meeting. The killer use case for many companies.
- Email drafts in Outlook: Good for standard communication, less so for complex matters.
- Excel analyses: Creating pivot tables via voice input works surprisingly well. Formula suggestions reduce the error rate.
What is not yet convincing:
- PowerPoint creation: The generated presentations are a starting point, but not a finished product. Too generic, too little design understanding.
- Copilot in Word: With long documents, the model loses context. Legal or technical texts require considerable rework.
Cost: 30 USD per user per month. For 500 employees, that is 180,000 USD per year. The ROI question arises clearly.
Google Gemini in Workspace: The Quiet Challenger
Google has caught up with Gemini 2.0 in Workspace. The integration into Gmail, Docs, Sheets and Meet is solid. Particularly strong: the search capabilities. Gemini can search across all Google Workspace data and provide contextual answers including Drive, chat histories and calendar.
The advantage over Microsoft: Google's models are often better at multilingual tasks. For internationally operating companies, a relevant factor.
The disadvantage: the ecosystem is smaller. Those relying on Active Directory, SharePoint and Exchange face a hard integration break with Google.
Salesforce Einstein GPT: AI in Sales
Salesforce focuses on sales and does so consistently. Einstein GPT generates customer summaries, suggests next steps, writes email drafts based on CRM data and automatically prioritizes leads.
The integration with Slack (now a Salesforce subsidiary) enables AI-powered sales communication directly in team chat. A sales representative can ask: "What is the status with customer X?" and receives a summary from CRM, email history and the last meeting.
Strength: Deep CRM integration. Weakness: Expensive and limited to the Salesforce ecosystem.
The Integration Question: Why the Model Is Secondary
The most interesting insight of 2026: The AI model itself is not the differentiator. GPT-4o, Gemini 2.0 and Claude 3.5 deliver comparable results for most business use cases. What makes the difference is the integration:
- How well does the AI access existing company data?
- Are permissions correctly enforced?
- How seamless is the embedding into existing workflows?
- Who operates and maintains the system long-term?
This is exactly where the opportunity lies for specialized IT service providers. While Microsoft, Google and Salesforce deliver the platforms, partners are needed to adapt these platforms to the specific corporate reality.
Practical Example: How Nemonicon GmbH Approaches the Copilot Rollout Differently
An interesting counter-model is shown by Nemonicon GmbH. Instead of simply rolling out Copilot licenses and hoping for the best, the Swiss service provider approaches the rollout in three phases:
- Data Quality Assessment: Before Copilot is activated, Nemonicon analyzes the SharePoint structure, permissions and data hygiene. Because Copilot is only as good as the data it accesses. If sensitive documents are visible to everyone, Copilot becomes a data protection risk.
- Targeted Activation: Instead of rolling out 500 licenses at once, Nemonicon starts with 20-30 power users, measures actual usage and productivity gains, and then scales deliberately.
- Supplementation through Custom RAG: For data that Copilot cannot reach (file servers, legacy systems, PDFs), Nemonicon builds supplementary AI knowledge assistants. The result: an AI strategy that goes beyond the Microsoft ecosystem, but is seamlessly integrated.
The approach is more involved than a blanket license rollout. But it works because it respects the reality in companies: data is messy, permissions have grown organically, and employees need guidance, not just licenses.
Conclusion: AI Assistants Are Here to Stay
The Copilot revolution is real but it is no sure thing. The technology works. The question is whether companies have the discipline to introduce it properly: clean up data, check permissions, roll out step by step, measure, optimize.
Those who do it alone risk expensive licenses without added value. Those who have a partner guiding the process invest in sustainable productivity. The big players deliver the platform. The specialists deliver the success.