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AI PoCs are Waste of Money
- AI PoCs are under scrutiny on whether they represent a wise investment or a mere waste of resources, industry leaders offer contrasting views.
- Vin Vashishta, AI advisor and author of From Data to Profit, is a critic of PoCs in AI and questioned their purpose.
- Vin Vashishta suggests that businesses should focus on simpler initiatives that build capabilities and deliver quantifiable results, rather than sinking money into PoCs that often lack direction or measurable outcomes.
- Stefan Ojanen, an AI product leader and MLOps expert, defends PoCs as a critical step in deploying great AI models.
- Vijay Raaghavan, the head of enterprise innovation at Fractal, believes the transition from PoCs to real-world applications has presented new challenges, particularly when it comes to measuring value.
- Critics claim PoCs rarely deliver scalable value, while proponents emphasise their role in validating innovative AI solutions.
- Industry leaders advocate simpler initiatives, leveraging vendor demos, trialling AI tools, and conducting educational sessions like seminars to introduce AI capabilities to businesses.
- IT giants realised that it was easier to build AI products using their technologies, as it was easier to transition from PoCs to products quickly.
- Without clear objectives and alignment with business goals, PoCs will fail.
- According to some, PoCs test the AI solutions within the business’s specific environment, uncovering edge cases and architectural challenges and reducing the risk of failures during full-scale implementation.
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