AI and Agents Can Supercharge Your Business Model

Why It Matters

The approach demonstrates a replicable path for traditional service businesses to capture AI‑generated efficiencies and new revenue streams, accelerating digital transformation across the private‑equity ecosystem.

Key Takeaways

• Carta uses Anthropic's Claude to prototype AI agents for its platform
• Playbook focuses on converting dated services into AI‑driven products
• Start with small, finite problems before scaling AI solutions
• Human‑in‑the‑loop is essential for trust and differentiation
• Strict data health checks prevent agent‑driven mishaps

Pulse Analysis

Carta’s latest AI‑powered playbook marks a turning point for firms that began as pure service providers. By leveraging a $600 million revenue base, the company illustrates how a legacy business can re‑engineer its core offering into a productized, AI‑enhanced solution. The strategy hinges on identifying narrow, high‑impact use cases and building agents with Anthropic’s Claude, allowing rapid prototyping without overhauling existing infrastructure. This method not only accelerates time‑to‑value but also creates a scalable model that can be replicated across the private‑capital sector and beyond.

Industry leaders at the AI Agent Conference stressed that successful AI adoption starts with hands‑on experimentation. Vrushali Paunikar urged teams to “pick a very finite problem,” a sentiment echoed by Pearson’s CTO, who noted that C‑suite familiarity with AI tools drives broader organizational confidence. Apply Digital’s CEO highlighted the necessity of reimagining workflows rather than merely adding automation layers, while Groupon’s VP warned against the temptation to chase every emerging tool. Together, these insights form a pragmatic roadmap: experiment, iterate, and embed human oversight to safeguard trust and compliance.

The broader implication for the market is clear: legacy service firms can unlock new growth trajectories by converting their expertise into AI‑infused products. However, the journey is fraught with risks—data breaches, unintended agent behavior, and regulatory scrutiny demand robust governance. Carta’s insistence on data health checks and human‑in‑the‑loop controls sets a benchmark for responsible AI deployment. As more firms adopt this blueprint, we can expect a wave of AI‑enabled platforms that blend human judgment with machine efficiency, reshaping competitive dynamics in finance, education, and beyond.