How to build better AI products with user research
Briefly

Artificial Intelligence (AI) has been around since the 1950s, but recent advancements in technology have enabled breakthroughs in generative AI and Large Language Models (LLMs). These advancements have transformed our relationship with technology and unveiled new possibilities.
Yet, we're witnessing a leap forward driven by advancements in computing power and the availability of extensive datasets. These factors have enabled breakthroughs in generative AI, a subset of AI focusing on creating new content and solutions, and Large Language Models (LLMs), designed to interpret and generate human language.
However, the excitement around AI has led to a fear of missing out (FOMO), causing companies to rush into integrating AI into every product feature. This can lead to a technology-centric approach that overlooks the importance of understanding user needs and solving their problems. Rushing into AI-powered solutions without proper evaluation can result in disappointing results and potential risks to user privacy, safety, and well-being.
With everyone excited about AI, a fear of missing out (FOMO) is driving companies to embed AI into every product feature. This can lead to a technology-centric approach, overshadowing a fundamental goal of product development: to create solutions that genuinely solve user problems and meet their needs.
Read at Medium
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