How Neurosymbolic AI Transformed My Favorite SWOT Analysis Tool: A Game-Changer for Strategic Insights
Author(s): Mukundan Sankar
Originally published on Towards AI.
From surface-level summaries to actionable intelligence — discover how this AI upgrade breathed new life into my top-performing blog on SWOT analysis
This member-only story is on us. Upgrade to access all of Medium.
SWOT analysis has always been one of my go-to tools for business insights, and it’s a topic close to my heart. In fact, my original post about automating SWOT analysis using GPT-3.5 was my top-performing blog — proving just how valuable people find this kind of strategic analysis. (Link to the original blog here).
But recently, I discovered a way to take SWOT analysis even further, thanks to a powerful approach called neurosymbolic AI. When I revisited SWOT analysis using this new method, the results blew me away. Neurosymbolic AI isn’t just a fancier AI; it’s a unique blend that combines pattern recognition (neural networks) with rule-based logic (symbolic AI) to deliver richer, more actionable insights. And it made me realize how much more sophisticated my original AI-driven SWOT analysis could be.
In this post, I’ll compare my initial GPT-3.5-based SWOT approach with the neurosymbolic AI-driven version. We’ll dive into how each one works and explore the real-world benefits of this upgrade.
When I first wrote about using AI for SWOT analysis,
Discover how I leveraged AI to automate SWOT analysis… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
