'All That Glitters' — AI Fool's Gold Vs. The Quantiva Approach
By Quantiva Team
The Risks of AI Hype
Not all AI implementations deliver value. CNET began experimenting with AI-generated articles for its personal finance section in early 2023. The initiative backfired when the content contained significant errors, including compound interest calculation mistakes and plagiarism concerns. This example demonstrates how AI can undermine credibility, deliver negligible value, and cause reputational harm without proper oversight.
AI/ML Is a Tool — Not a Goal
Rather than chasing trends, Quantiva's approach prioritizes solving genuine business problems through:
- Problem identification before technology selection
- Feasibility assessment to determine if AI is truly necessary
- Business alignment ensuring solutions drive measurable outcomes
- Data strategy establishing high-quality foundational datasets
- Iterative development with real-world validation
- Change management supporting organizational adoption
Success Through Strategic Implementation
Two notable implementations demonstrate the approach in action:
An FDA-cleared medical device for radiation oncology — where the regulatory and accuracy requirements left no room for "good enough" AI.
A real estate fund that reduced asset processing from four days to two hours — where AI was the right tool for a clearly defined, data-intensive problem.
The Bottom Line
Thoughtfully designed, strategically aligned, and carefully executed AI solutions deliver genuine business value. The difference between AI fool's gold and real impact comes down to discipline, domain expertise, and a relentless focus on outcomes over hype.