In the rapidly evolving landscape of artificial intelligence (AI), the role of in-house counsel is undergoing a significant transformation. Gone are the days when legal advisors could solely focus on the legality of end products. Today, understanding the intricate workings of AI technologies is crucial, akin to a pilot needing to know the mechanics of an aircraft, not just its capability to fly.

AI technologies are not isolated developments; they are the culmination of numerous technical decisions, each carrying potential legal implications. For in-house counsel, this means that a deep understanding of AI processes is indispensable. It is the bedrock on which sound, practical legal advice is built, ensuring that guidance is not only theoretical but also applicable in real-world scenarios.

The traditional model where engineers create and lawyers approve is becoming obsolete. AI systems are dynamic; they learn, adapt, and make decisions that continually blur the lines between design and application. This evolution means that legal reviews can't wait until a product’s development concludes, as many risks need addressing at much earlier stages.

In-house product counsel today need to be bilingual in AI and legal language. This dual fluency allows them to engage effectively in product discussions, not just as risk assessors but as proactive contributors to design and strategy. Understanding the nuances of training datasets, model architectures, and performance tests is crucial. These elements provide insights into potential legal exposures far more accurately than any product launch presentation.

The collaboration—or the lack thereof—between legal and technical teams can lead to significant oversights. For instance, an AI hiring tool might develop a bias toward a particular gender, or an art generator might unlawfully train on copyrighted images. These are not unavoidable errors but are often the result of missed opportunities to integrate legal insight into the early stages of product development.

By having a grasp of AI's technical underpinnings, in-house counsel can identify potential issues when they are still manageable, rather than when they have escalated into costly, public legal challenges. Staying exclusively in the legal lane can lead to a failure to see how AI design might embed biases or breach privacy laws. Conversely, focusing only on technical aspects might underestimate how compliance failures could lead to broader regulatory or reputational damage.

For in-house counsel, developing AI fluency begins with curiosity. Engaging with engineering teams, participating in technical reviews, and understanding how decisions are made at the code level are all vital. Keeping abreast of AI regulations across different jurisdictions is equally important, ensuring that legal advice is timely and relevant.

Ultimately, when in-house counsel are adept in both AI and law, they transition from being mere gatekeepers to becoming integral partners in innovation. They contribute to designing products that are not only legally compliant but also more transparent and resilient to market and regulatory pressures. In an AI-driven era, the ability to translate between code and case law is not just an additional skill—it is essential to leadership and a mark of teams that don’t just launch products, but launch products that endure.