Every Single AI Use Case I Can Think Of…
AI transforms how we work, not if we work
In a world awash with AI fear-mongering, entrepreneur Sahil Bloom offers a refreshingly pragmatic take on artificial intelligence in his recent video. Rather than dwelling on abstract doomsday scenarios, Bloom methodically walks through dozens of concrete AI applications across industries, showcasing how these tools are already reshaping workflows and creating new possibilities. His message is clear: AI isn't coming to steal your job—it's here to transform how you work.
Key insights from Bloom's comprehensive AI breakdown
- AI augments rather than replaces human capability across most domains, serving as a force multiplier that enhances productivity when properly integrated into existing workflows
- Industry-specific AI applications are already delivering tangible value, from legal contract analysis to medical diagnostics to personalized education—proving AI's versatility beyond generic use cases
- The combination of domain expertise with AI literacy creates the most powerful results, suggesting professionals should focus on becoming skilled AI collaborators rather than competing against algorithms
The overlooked reality of AI adoption
The most compelling insight from Bloom's exploration isn't any single application but rather the underlying pattern it reveals: AI adoption follows a predictable augmentation path before any substitution occurs.
This matters tremendously because it contradicts the prevailing narrative about AI eliminating jobs wholesale. What we're actually witnessing is a transformation in how work gets done, with AI handling routine tasks while humans take on higher-level responsibilities. For example, when Bloom discusses how AI assists lawyers with contract review, the technology isn't replacing legal expertise—it's freeing attorneys to focus on strategy and client relationships while handling document analysis at superhuman speed.
This pattern appears repeatedly across industries. In education, AI tutors don't replace teachers but extend their reach. In healthcare, diagnostic tools don't eliminate doctors but help them make better decisions. Understanding this augmentation-first pattern gives professionals a strategic advantage in navigating the AI transition.
Beyond the obvious: AI's second-order effects
What Bloom's video doesn't fully explore are the second-order effects of widespread AI adoption. Consider healthcare: when AI handles routine diagnoses, it doesn't just make doctors more efficient—it fundamentally changes healthcare economics. Remote diagnostics become more feasible, potentially addressing provider shortages in rural areas. Insurance models
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