Faced with a tough M&A market, many profitable software startups are not seeking a discounted exit. Instead, they are using their capital reserves to "hold" their position while actively "accelerating" their integration of AI. This strategy aims to increase their future acquisition value by aligning with the market's new priorities.

Amplitude's CEO acquired multiple founder-led companies as a deliberate strategy to counteract the inherent slowness of a large SaaS business. This injects a startup's pace and an AI-native mindset directly into the organization to accelerate its AI transformation.

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.

Airtable, once valued at $11.7B, was acquired by Bending Spoons for an enterprise value of $1.285B. This outcome, where late-stage investors barely recoup capital and common stock holders get little, highlights the harsh reality of the SaaS market correction for even well-funded unicorns.

A powerful go-to-market strategy is for an AI company to buy a legacy business (e.g., a debt collector) with existing clients but declining revenue. This allows the startup to bypass the difficult early sales process, immediately deploy and refine its AI, and use the acquired firm's client roster as a launchpad.

For an existing SaaS company to become a credible AI player, it must do more than add features. It requires a fundamental reinvention, akin to 'open heart surgery.' This means re-architecting to be agent-first, shifting to outcomes-based pricing, and even rebranding—as seen with Intercom becoming Finn—to attract new funding.

Supabase, founded before the AI boom, found exponential growth by becoming the default database for agentic AI products. This shows a powerful strategy for pre-AI companies: instead of pivoting entirely to AI, they can 'co-attach' their existing product to a new AI-driven workflow, capturing immense value from the tailwinds.

Recent acquisitions of slow-growth public SaaS companies are not just value grabs but turnaround plays. Acquirers believe these companies' distribution can be revitalized by injecting AI-native products, creating a path back to high growth and higher multiples.

When a SaaS company successfully launches a new AI product, it creates a second, conflicting business. It must manage the legacy SaaS model (seats, predictable metrics) alongside the new AI model (outcomes, unpredictable metrics), creating tension in strategy, branding, and operations.