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...

Implementing automation in M&A advisory requires more than adopting new software—it demands a fundamental rethinking of how we approach deal flow, due diligence, valuation analysis, and integration planning. After guiding multiple advisory teams through this transformation, I've distilled the critical elements into a comprehensive checklist that addresses both technical implementation and the cultural shifts required for success. This structured approach ensures that automation enhances rather than disrupts your existing capabilities, ultimately delivering faster deal execution, deeper insights, and more predictable synergy realization. The framework presented here draws from implementations across bulge bracket firms and boutique advisories, encompassing transactions ranging from $50 million bolt-ons to multi-billion dollar transformational mergers. Each checklist item includes rationale based on what separates successful Intelligent Automation in M&A implementations from...

Three years ago, our fund made a decision that fundamentally altered how we approach deal sourcing, due diligence, and portfolio management. We committed to integrating artificial intelligence across our investment operations—not as a novelty, but as a core capability. What followed was a journey filled with unexpected wins, humbling setbacks, and invaluable lessons that reshaped our understanding of how AI Integration in Private Equity actually works in practice, beyond the conference presentations and vendor promises. The promise of AI Integration in Private Equity was compelling from the start: faster deal screening, deeper analytical insights, and the ability to monitor portfolio companies with unprecedented granularity. Yet the reality of implementation taught us that technology alone solves nothing. The real transformation came from understanding where AI genuinely adds value versus where it creates expensive distractions. Our experience offers a candid look at what actually wor...