As AI continues to transform the market, companies rush to capitalize on the trend, often without considering if their products (or end users) need AI. This haste has led to a surge in failure rates, with estimates suggesting that more than 80% of AI-driven projects fall short of expectations — almost twice the failure rate for information technology projects that do not involve AI.
Why it matters: Failed products cost companies more than wasted time and resources. They can erode customer trust, weaken the brand, and ultimately lead to lost revenue —consumers are less likely to engage with companies that don’t meet user expectations.
Improved outcomes: To improve the application of AI in products, companies need to invest in psychology-backed user research prior to design and development. The right research can help companies answer two crucial questions — “what problem is your product looking to solve?” and “Is AI necessary to do so?”
What you’ll learn in the white paper:
- The root cause of ineffective AI products.
- How cross-functional research can improve AI product outcomes.
- How research psychologists help create products that resonate with real user needs.
- How psychology-backed research can help craft more ethical AI products.
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