For years, updating legacy systems like bank mainframes running COBOL was prohibitively expensive. Modern AI agents are now so proficient at code migration that these projects are finally feasible. One engineer migrated the entire Bun codebase to a new language in just 11 days, a task that previously would have taken a team a year.

The PayPal bid exemplifies a new M&A trend: modern, AI-first companies are buying mature, founderless digital businesses. They see untapped potential in optimizing operations, networks, and products with AI, creating a playbook for reviving what they see as "flaccid" digital assets.

Roll-up strategies for old SaaS companies rely on slow customer churn. However, AI is drastically reducing migration friction. A platform migration that once took a year can now be done in a day, causing these legacy assets to decay much faster than acquirers have modeled.

For PE firms buying founder-owned software companies, AI is a game-changer. It dramatically accelerates paying down the technical debt and modernizing the tech stack—often the biggest hurdles to growth post-acquisition. This allows firms to unlock value faster and more efficiently than ever before.

A new startup strategy involves acquiring traditional businesses and dramatically increasing their margins by integrating AI. This approach requires a unique blend of M&A, operational change management, and AI expertise, differing from typical venture-backed company creation.

AI makes running software in "maintenance mode" much easier and cheaper. Acquirers like Bending Spoons no longer need to retain expensive engineering teams for their institutional memory of a codebase. An AI can now learn the code instantly, reconstituting that historical knowledge and dramatically reducing the overhead of maintaining legacy products.

Migrating from legacy enterprise systems was once a multi-year ordeal, creating powerful vendor lock-in. AI now automates the process by analyzing environments, converting code, and validating results. This has reduced migration timelines to as little as 30 days, dramatically lowering switching costs for large companies.

For private equity firms acquiring software companies, assessing a target's AI-readiness is becoming paramount. The massive cost to re-architect a legacy platform for the AI era will become a primary valuation factor, making tech diligence the new first screen.

Enterprises are finding immediate, high return on investment by using AI to port legacy codebases (like COBOL) to modern languages. This mundane task offers a 2x speed-up over traditional methods, unlocking significant infrastructure savings and even driving new developer hiring.