How we use AI at "AI for Finance"
Balancing AI & Human Effort
AI is a powerful tool, but content is only valuable when it is well-researched, relevant, and thoughtfully structured. At AI for Finance, we use AI extensively—but we also put significant human effort into everything we publish. Every word on this site is reviewed, refined, and fact-checked by us before it goes live. Transparency matters, and we want our readers to understand exactly how AI fits into our process.
The Concept: AI as a Thought Partner
AI played a key role in shaping this site’s vision, but not in the way you might think. The idea for AI for Finance came from our deep experience in finance and technology, but we used AI—specifically ChatGPT—as a thought partner to refine it.
We iterated with AI through discussions on:
- Who this site is for – Defining our ideal audience and the specific problems they face.
- What we should cover – Selecting content areas that balance expertise with market demand.
- How to structure our insights – Finding the best format to make AI-driven finance topics engaging and practical.
The Site Development: AI-Powered Efficiency
We have the technical skills to develop a site from scratch, but that’s not where we wanted to invest our time. Instead, we used AI to quickly scan the market, compare platforms, and experiment with options before selecting the platform we now use. AI also helped us refine the site's design, by generating ideas for font choices, layouts, and wording. And lastly, AI excels at generating and editing code, which we used when starting and continuously to implement functionality not available natively in the platform we use.
The Research Process: BigQuery & GenAI
One of our core principles is quality research—and AI helps us achieve that at scale. We use a combination of Google BigQuery and Generative AI (Gemini & ChatGPT APIs) to gather, filter, and structure our research database. Here’s how it works:
- Data Aggregation: We pull relevant financial news, research papers, and reports into a structured dataset using BigQuery.
- AI-Powered Filtering: Our scripts send this data to GenAI models, which summarize and prioritize key insights.
- Human Review: We go through the AI-curated findings to identify the most relevant and valuable insights for our readers.
The Content Creation Process: AI & Human Collaboration
Once we identify a strong topic, content development is a human-AI iterative process:
- AI helps us structure ideas and suggest frameworks for articles.
- We refine, expand, and fact-check every piece, ensuring clarity, accuracy, and relevance.
- No article is ever purely AI-generated—every final piece is human-crafted and quality-assured.
Why This Matters
AI is transforming finance, but its real power comes from how humans use it. We believe that by combining AI’s ability to process vast amounts of information with human expertise, we can create better, more insightful finance content.
By being transparent about how we use AI, we set the right expectations for our readers—and hopefully, demonstrate how AI can be integrated thoughtfully into finance workflows.
AI for Finance is both an experiment and a mission: to explore, distill, and share what truly matters in this rapidly evolving space. And we’re excited to have you on this journey with us.