How to Choose the Right AI Tool in 2026: A Use-Case Guide
The AI tools market has become impossible to navigate. Every week brings a new model, a new benchmark, and another social media debate about the “best AI tool.” The issue is that the question itself is wrong. There is no best AI tool. There is the right tool for your specific use case.
We use these tools daily with our clients. Here is our framework, organized by concrete need.
Writing and text analysis
The need: drafting emails, summarizing documents, analyzing text data, rewriting, translating, brainstorming.
This is the most common use case, and the one where the choice matters least — all major models perform well. But differences do exist.
Claude (Anthropic) excels at long-form text and nuanced analysis. If you need to summarize an 80-page report or produce a well-structured document with a precise tone, this is our first pick. The context window is generous and the model follows style instructions rigorously.
ChatGPT (OpenAI) remains the default Swiss army knife. Its plugin ecosystem, built-in web search, and multimodality (image, voice) make it the most versatile tool for everyday, non-specialized use. If you only want one subscription, this is the one.
Mistral Le Chat deserves a mention: it is the French sovereign model. For businesses with compliance requirements or those that prefer to keep their data in Europe, Mistral is a credible option. Performance is solid, even if the ecosystem is less mature.
Gemini (Google) stands out through its native integration with Google Workspace. If your company lives in Gmail, Drive, and Sheets, Gemini transforms those tools from within. Version 2.0 has significantly closed the gap.
Our recommendation: Claude for demanding writing and analysis, ChatGPT for daily tasks, Mistral if data sovereignty matters.
Code and development
The need: writing code, debugging, refactoring, building applications, automating technical tasks.
This is the area where AI tools have progressed the most in the past year, and where your choice of tool creates a real productivity difference.
Claude Code (Anthropic) is our primary tool. It works directly in the terminal, understands entire projects (not just individual files), and handles multi-file modifications simultaneously. For structured development on existing codebases, nothing matches it today.
Cursor popularized the AI-augmented IDE. The experience is smooth: you code normally, and the AI intervenes contextually. This is the best choice if you want to stay in a familiar graphical environment and primarily work file by file.
GitHub Copilot remains relevant for real-time autocompletion. It is less powerful than the previous two for complex tasks, but its integration into VS Code is frictionless. Useful as a complement, less so as a primary tool.
Windsurf (formerly Codeium) is improving rapidly and offers a solid alternative to Cursor with a similar approach.
Our recommendation: Claude Code for developers comfortable with the terminal and complex projects. Cursor for those who prefer a visual IDE. The two complement each other well.
Visual and video creation
The need: generating images, creating videos, producing marketing visuals, animating presentations.
The most spectacular domain, but also the one where you need to be most careful about quality and licensing.
HeyGen has become essential for corporate video. You can create realistic avatars, translate videos while maintaining lip sync, and produce video content at a fraction of traditional costs. For training or presentation videos, the time savings are substantial.
Midjourney remains the reference for aesthetic quality in generated images. Outputs are consistent, styles are controllable, and the community produces impressive results. The Discord interface can be off-putting, but the quality is there.
DALL-E 3 (via ChatGPT) is more accessible and better integrated into a conversational workflow. Quality falls below Midjourney for artistic renders, but is more than sufficient for functional visuals: blog illustrations, mockups, concepts.
Runway is opening the path to generative video. Results are still experimental for final professional content, but short clip generation and AI-powered video editing tools are already usable.
Our recommendation: HeyGen for corporate and training video, Midjourney for high-end visuals, DALL-E for quick everyday needs.
Automation and workflows
The need: connecting tools together, automating repetitive tasks, building data pipelines, orchestrating processes.
This is where AI moves from novelty to measurable productivity tool. Automating a 30-minute daily workflow saves 120 hours per year.
Make (formerly Integromat) is our primary automation platform. The visual interface is powerful, integrations are extensive, and error handling is robust. We use it to connect CRM, email, invoicing, and internal tools for our clients.
n8n is the open-source alternative. Self-hostable, with no execution limits, and increasingly mature. If you have data sovereignty constraints or a high volume of automations, this is the right choice.
Zapier AI adds AI capabilities to Zapier (rewriting, extraction, classification). Simpler than Make for basic automations, but less flexible for complex scenarios.
Claude with Cowork allows you to orchestrate complex tasks directly within an assistant: generating documents, batch-processing files, chaining analyses. Less suited to recurring automations, but powerful for one-off complex tasks.
Our recommendation: Make for recurring cross-tool automations. n8n if sovereignty or volume is a concern. Claude for complex one-off tasks.
Research and monitoring
The need: finding reliable information, summarizing the state of the art, monitoring a topic, deep-diving into a complex subject.
Traditional search engines are showing their limits compared to AI-augmented research tools.
Perplexity has become our go-to for factual research. Answers are sourced, synthesis is clear, and the ability to cross-reference multiple sources in real time is invaluable. It is the most natural replacement for Google when it comes to informational search.
NotebookLM (Google) is an underrated tool. You import your documents (PDFs, articles, notes) and the model becomes an expert on your corpus. For preparing a sector analysis from 20 reports, nothing beats it. The automatically generated podcast feature from your sources is surprisingly useful.
Gemini Deep Research represents the “autonomous research” approach. You ask a complex question, and the model spends several minutes exploring the web, consulting dozens of sources, and producing a structured report. Results are uneven, but when it works, it replaces hours of manual research.
Our recommendation: Perplexity for daily research, NotebookLM for analyzing existing document collections, Gemini Deep Research for deep explorations.
How we choose for our clients
When we work with a company, we do not recommend “the best AI tool.” We start with three questions:
- What concrete problem are you trying to solve? One tool per use case, not one tool for everything.
- What are your constraints? Budget, data sovereignty, in-house technical skills, existing tool stack.
- What is your AI maturity level? A team just starting out does not need self-hosted n8n — ChatGPT and Make are enough to get going.
Our approach: start small, measure impact, then expand. A single working automated workflow is worth more than ten paid tools sitting unused.
You have a concrete need and don’t know where to start? That is exactly why we exist.