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5 Litigation and AI Trends to Watch in 2024

Where Innovation Meets Skill: 3 Takeaways from the 2019 Bucerius Autumn Conference

Today’s global corporations need digitally savvy lawyers who are laser-focused on high-risk/high-value work, UnitedLex CEO Dan Reed said to an audience of law firm and in-house legal leaders at the 9th annual Autumn Conference of the Bucerius Center on the Legal Profession in Hamburg, Germany. Here are three takeaways from the event:

1. Enterprise Legal and the T-shaped lawyer

“The digital lawyer must build on substantive legal knowledge and skills by adding a layer of innovation built around design thinking, data analytics, technology, process and project management, and business tools,” he said. These competencies are part of being a “T-shaped lawyer” and critical to digital transformation, “the single biggest foundational element to successfully and sustainably execute on corporate strategy.”

Taking it a step further, Reed introduced the concept of Enterprise Legal, a unique model for legal services delivery that enables digital transformation and ensures that law departments create more business value.


2. Artificial intelligence as a legal delivery enabler

Artificial intelligence (AI) is fast becoming one of the most critical enablers in the legal profession. Effective AI requires general counsel and their law departments to address:

  • Tool adoption: The legal team must embrace using the tool and the related platform to drive efficiency and effectiveness.
  • Commitment to continuous improvements: Users must commit to providing necessary feedback, which is essential to the AI mindset.
  • Metrics and measurement: Legal leadership must measure tool usage and expected outcomes, including return on investment.
  • Data quality: Every data set must be complete and searchable.

In a use-case example, Reed identified AI’s potential value adds for commercial transactions:

  • Accelerates deal closure, improves deal quality, and reduces support costs via automated review.
  • Provides on-demand, ad hoc analytics across agreements. Provides data for systemic risk management and improved decision-making.
  • Prevents revenue leakage and preserves deal margins via superior obligations tracking.

3. AI dependencies for success

Successful AI deployment depends on both the AI provider and all internal teams, including service providers, Reed said. An effective AI solution must:

  • Provide at least 80%–90% accuracy: With lower accuracy, productivity gains will not be realized, because legal professionals will not trust and rely on the solution. Out-of-the-box accuracy is essential to staying on schedule and on budget.
  • Maintain an agile feedback loop: Users must quickly communicate with the development team about things the tool has missed, so the AI solution continuously learns and improves.
  • Fit within the way people work: The AI solution must work seamlessly within the existing business process workflows (tool fatigue is real!).
  • Have speed to minimum viable product: Out-of-the-box AI is a myth for use cases with any degree of complexity. The benefits need to outweigh the costs, both with respect to the investment in the solution and the human capital required to train the solution.
  • Lead to actual productivity: To state the obvious, the solution must decrease the cycle time of the process or task in question.

General counsel and the legal team must ensure that AI development is tightly intertwined with the end-user community and laser-focused on ROI, requiring significant time investment in cultivating a unified mind-set to define success.

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