Underwriting Growth with Confidence: Building an AI-Ready GTM Engine

It’s All About AI

Recently, the Alexander Group’s private equity operator community gathered to discuss the latest in go-to-market (GTM) value creation. The team talked about what is delivering results and where classic plays are falling short. Another key discussion topic centered around underwriting growth with confidence, or moving go-to-market (GTM) out of upside and into the base case, as well as how to scale GTM capabilities.

As you might expect, all roads led back to AI.

The conclusion? Start with foundations. Then, use AI to automate and inform GTM with intelligence. Alongside both of these, it’s essential to invest in talent that enables execution at speed.

Foundation Before Acceleration

AI dominated the conversation, but not in a hype-driven way. Instead, the community was candid about where AI breaks down. Data infrastructure is the gating factor. Many companies lack the foundational data needed to make AI-driven GTM plays effective. Without clean, accessible data, even the best tools produce unreliable outputs—leading to skepticism around accuracy.

Another foundation to focus on is the people and governance needed to bring AI to life. Most organizations are still in a build-and-test phase, figuring out not just which tools to use, but who owns them and how they will be managed. While the team aligned on the need and inclusion of IT, legal and compliance alongside GTM stakeholders, the actual structures differ from business to business.

Finally, the group discussed ways in which firms enable their portfolio companies. Some are building dedicated teams and centers of excellence at the firm level. Others are bringing in specialized talent and investing in upskilling existing operating partners.

Enablement methodology aside, the group coalesced on the notion that gaining portfolio company traction is most effective via a “pull” strategy. Management teams understand the importance of AI adoption, primarily because it’s one of the many high-priority pressures they face. Operating partners most effectively serve shareholders and management teams by homing in on the right use cases and enabling deployment.

Automate and Inform

The community members viewed streamlining workflows—marketing content creation, lead qualification and routing, sales administration, new customer onboarding, service ticket management and more—as a quick win and path to momentum.

They agreed that intelligence use cases (e.g., sales coaching and customer sentiment analysis) are showing promise. The group also shared how marketing functions are improving return on marketing investment (ROMI) through more precise targeting and program deployment. Ideal customer profiles (ICP) are sharpening and becoming more agile as market, competitive and customer trends shift.

Automation and intelligence use cases are not without opportunities for refinement. Outbound marketing, forecasting, pipeline, account planning and others take time to get right. To improve, these use cases must be actively monitored and given feedback.

Talent For Execution at Speed

Talent has been a critical value creation lever for a while now. The right CMO, CRO and/or CCO make a world of difference, which is why firms remain focused on evaluating leadership early in the hold. Some use operating partners while others use formal assessments between sign and close. Some are also conducting assessments across the GTM organization post-close. The community agreed that addressing talent needs early in the hold speeds up execution and impact.

In the world of AI, the emphasis on talent remains. The group suggested that management teams must become AI-fluent themselves. They must evangelize the use and adoption of new ways of working. To bring AI impact to life, they talked of the importance of investing in great Revenue Operations talent—creative, technical and engineering people eager to learn and bring new ways of working to their firms.

Conclusion

Operating partners are tasked to deliver credible and repeatable portfolio company impact. Pivoting to an AI-driven GTM model starts with foundations. As foundations are laid, use AI to automate and inform the GTM model with intelligence. And don’t forget to invest in talent that enables execution at speed.