Let's Do This | AI Transformation Index

Overview

Let's Do This operates a transaction-based event registration and discovery marketplace for endurance and adventure sports, earning fees per booking while also selling AI-powered analytics (NOVA) to event organizers to drive registrations and optimize event growth.

Executive Summary

Let's Do This is a niche marketplace intermediary in endurance sports registration — a position with structural vulnerability to AI-driven disintermediation, as both participants and organizers could increasingly bypass the platform layer as AI agents improve. The company is already pursuing AI transformation through NOVA and customer support automation, which reduces unrealized opportunity but also signals that this is a self-sufficient team rather than a PE candidate needing external AI catalysis. The strategic question for EQT is whether the proprietary cross-organizer data asset is defensible enough to sustain a durable analytics-led moat, or whether the platform risks being commoditized by larger general-purpose ticketing and AI-native discovery players entering the niche.

Durability Rationale

Let's Do This operates as a marketplace intermediary in a structurally exposed position — it sits between event organizers and participants with low regulatory barriers to entry, meaningful disintermediation risk from AI agents and direct-to-organizer tools, and a core outcome (digital event registration) that is readily substitutable. The network effect provides a degree of stickiness, but it is not reinforced by the kind of switching costs, regulatory moats, or physical infrastructure that would make the business resilient to well-capitalized AI-native competition. The primary durability risk is that the marketplace layer gets squeezed from both sides as organizers build direct registration capability and participants use AI agents to find and book events without a marketplace intermediary.

Opportunity Rationale

The unrealized AI opportunity for Let's Do This is real but bounded — the company is already actively building AI into its product (NOVA, customer support agents), meaning the step-change is being captured in real time rather than sitting as latent potential. The business is entirely cognitive and software-driven, making virtually all core workflows AI-applicable, but the magnitude of improvement is constrained by the relative simplicity of the underlying transaction. The most meaningful opportunity is using its cross-network proprietary data to build organizer intelligence that general-purpose AI cannot replicate — but this requires continued data accumulation and product investment to sustain the moat.

Key Risks