Dispelling Myths About Generative AI

An eDiscovery Today article by Doug Austin debunks common misconceptions surrounding generative AI (GenAI) and offers insights into its implementation. Austin cites “Five Myths About Generative AI That Leaders Should Know” by Scott A. Snyder and Sophia Velastegui, whose insights can be translated into the legal industry.

Myth #1: Gen AI tools are available for free or minimal cost. The authors acknowledge that Gen AI tools are universally inexpensive but emphasize that costs can vary significantly depending on the organization and implementation. They stress the need to consider factors such as user base and tool integration. Austin agrees that labeling this as a myth may not apply universally.

Myth #2: AI always improves human performance. Contrary to popular belief, GenAI doesn’t guarantee enhanced human performance. Instead, success hinges on training employees in soft skills like critical thinking and bias detection. Austin underlines the importance of a holistic approach involving people, processes, and technology.

Myth #3: Building the GenAI model is the hardest part of implementation. While customizing pre-trained AI models can be challenging, transforming workflows and ensuring employee readiness are equally crucial. Austin acknowledges that the difficulty level can vary depending on existing workflows but cautions against overlooking the human aspect.

Myth #4: Wait and see how GenAI plays out. The authors caution against a wait-and-see approach, citing examples of companies that failed to embrace new technologies and suffered consequences. They emphasize the need for continuous adaptation to keep pace with competitors and AI advancements. Austin notes, “If you’re standing still, you’re falling behind.”

Myth #5: Investing in GenAI will automatically give you a competitive advantage. The authors caution that simply deploying AI technology is insufficient for gaining a sustainable competitive advantage. They stress the need for ongoing innovation and differentiation in Gen AI strategies to outperform competitors. According to Austin, failure to invest in AI could result in a competitive disadvantage.