Elli Peterson's TechCrunch

After advising on the implementation of AI systems across more than thirty M&A transactions in the past two years, I've observed a consistent pattern: firms that approach adoption systematically, with clear planning and realistic expectations, achieve measurably better outcomes than those that pursue ad-hoc implementations driven by vendor promises or competitive pressure. The difference between successful AI integration and expensive disappointment often comes down to methodical preparation and a comprehensive understanding of what these technologies require to deliver value in the high-stakes environment of corporate transactions. This checklist distills lessons learned from both successful implementations and costly mistakes in deploying AI in M&A practice. Each item reflects a critical decision point where thoughtful planning creates tangible advantages in deal execution, risk management, and value capture. Whether you're a law firm evaluating your first AI platfor...

Corporate law firms today find themselves at a crossroads. With increasing demands for efficient legal services and the constant pressure to minimize operating costs, many firms are turning to technology for solutions. AI Legal Analytics presents a viable path forward, addressing pain points such as document overload, compliance risks, and the need for timely legal insights. The need for effective solutions is further emphasized by the competition from alternative legal service providers who are leveraging technology to offer cost-effective services. This landscape prompts the urgent exploration of how AI Legal Analytics can streamline operations and improve client engagement. Identifying Key Pain Points in Corporate Law Law firms face several operational challenges, including: Manual processes leading to high operational costs Inability to manage large volumes of documents efficiently Risk of compliance breaches due to outdated data These pain points hinder the ability of law firms t...