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Are AI PoCs Worth the Investment or Just Burning Cash?
- Many companies are moving artificial intelligence (AI) Proof of Concepts (PoCs) to production, but industry leaders have contrasting views on whether they are worth the investment.
- AI advisor Vin Vashishta questions the purpose of AI PoCs stating that they do not deliver revenue and cannot be scaled in production.
- Vashishta suggests businesses focus on simpler initiatives that build capabilities and deliver quantifiable results; he advocates for alternative approaches such as leveraging vendor demos and trialling AI tools.
- AI product leader Stefan Ojanen defends PoCs as a critical step in deploying great AI models, arguing that the first iteration is a way to discover advantages.
- Vijay Raaghavan, the head of enterprise innovation at Fractal, sees the transition to real-world applications as presenting new challenges, particularly when it comes to measuring value.
- PoCs test AI solutions within a business's specific environment, uncovering edge cases, and architectural challenges, thereby offering insights that conventional solutions from others might not provide.
- Fabian Leon Ortega, the CTO at SunDevs, views PoCs as stepping stones to innovation that have a real-world application.
- PoCs can be cost-effective when executed strategically and provide valuable insights, but success hinges on clear objectives and alignment with business goals.
- Without clear objectives and alignment with business goals, PoCs have the tendency to become a 'money pit.'
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