Three AI Implementation Priorities from Legal Innovators California

Last month's Legal Innovators California conference highlighted three areas where legal professionals see meaningful change. While AI adoption varies widely across firms and in-house teams, these patterns have emerged consistently.

1. Rethinking junior lawyer development

AI can now handle much of the document review and basic research that traditionally served as a training ground for new lawyers. This creates both opportunities and challenges for talent development.

The shift is noticeable: first-year associates are working on matters that would have been beyond their reach just a few years ago, while the incremental skill-building that came from routine work is disappearing.

For in-house teams: Consider how to develop judgment and strategic thinking when junior lawyers can skip past many foundational tasks.

For firms: Training programs built around document review and basic research need updating. The focus shifts to developing skills that complement AI capabilities—client counseling, negotiation, and business judgment.

2. Making thoughtful technology decisions

The "build versus buy" question comes up frequently. Based on what we're seeing, custom AI development makes sense in specific situations:

• When security requirements are absolute e.g., highly sensitive client data that can’t leave or touch any external systems
• When integration with existing bespoke systems is critical and off-the-shelf solutions don't work
• When you have high-volume, repetitive work with clear patterns

For most other situations, proven solutions deliver better results with less risk in initial development and ongoing maintenance. AI is moving so quickly that what’s cutting edge today could be out of date in a month.

For in-house teams: Start by mapping your current workflow inefficiencies. Often, the most significant gains come from better integrating existing tools rather than adding new ones.

For firms: Custom AI development is resource-intensive. Consider whether the investment will create genuine competitive differentiation that clients will value.

3. Collaborating on AI knowledge

An interesting development is that successful legal professionals share AI strategies with clients rather than keep them proprietary. This approach recognizes that clients are already experimenting with AI tools, often without the benefit of legal expertise.

Sharing knowledge helps prevent compliance issues and positions lawyers as strategic partners rather than just service providers.

For in-house teams: Ask your outside counsel about their AI workflows. Many are willing to share insights that can improve your internal processes.

For firms: Consider offering AI guidance as part of your service. Clients appreciate practical knowledge about tools they're already considering.

What's next

These changes are happening gradually but are consistent across different practice areas and firm sizes. The question isn't whether AI will change legal work—it's how to adapt thoughtfully.

Worth considering: Are your current approaches to training, technology, and client relationships aligned with these shifts? Minor adjustments now may be easier than significant changes later.

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