Implementations are the edge

Implementations are the edge

The new mission critical function for AI-apps

Published

May 13, 2026

Emily Man

Partner, Enterprise AI & Fintech

Nick Daley

Senior Associate, Enterprise AI & Fintech

Jason Gelman

Operating Partner, Go-to-Market

Cassie Young

Partner, Enterprise AI

We are entering into a third era of enterprise software. Each era has seen a distinct shift of the onus of value delivery away from the customer and onto the vendor. We believe that value capture by AI-native software companies will hinge almost entirely on their ability to continuously deliver exceptional outcomes — making implementations and customer success mission critical.

We see the three eras of enterprise software as:

  1. On-prem (“Buy the House”) - large upfront investment, extremely high switching costs, ongoing monetization through professional services, in-sourcing of customization/implementation
  2. Cloud/SaaS (“Pay Rent”) - medium upfront investment, medium switching costs, ongoing monetization driven through expansion, outsourcing of implementations
  3. AI-native (“Hotel Rooms?”)- low cost of ownership, increasingly lower switching costs, ongoing monetization driven by value delivered to the business, high need for proper implementation

The On-Prem Era - “Buy the House”

In the on-prem era, enterprise software functioned much like buying a home outright: customers made a large, upfront license commitment long before any value was realized. Extremely high upfront cost of ownership and on-prem delivery meant that picking any system was a monumental decision. From there, software vendors were both able to and forced to extract ongoing value by charging through the nose to send a team onsite for every upgrade, patch, workflow change, or new integration.

As a result, professional services became a significant revenue line and a structural dependency. The knock on effect was that software had slow improvement cycles, deployments were brittle, and releasing new functionality was expensive and logistically complex. Switching costs were so high that “Customer Success” did not exist as we know it today; rather post-sale engagement centered on “Account Managers”, whose remit was increasing contract value rather than ensuring product outcomes. The guiding principle of the on-prem era was stability and control, not adaptability or continuous value realization.

The Cloud/SaaS Era - “Sign the Lease”

The transition to cloud introduced a fundamentally different software operating model. Instead of owning software outright, customers switched to recurring subscriptions akin to paying rent. Delivery in cloud environments made software improvements effectively free, with vendors shipping updates in the form of new features and functionality directly to customers. Professional services largely moved away from being a consistent, recurring revenue stream (that’s paying for the software instead) and more limited in scope to the “one time” upfront customization and onboarding work needed to adjust an “out of the box” solution to an enterprise customer.

The more one-time nature of the implementation meant that the scaled platforms largely outsourced this work — creating one of the largest services markets in enterprise IT. Global systems integrators (GSIs) emerged as a category – a $550B+ services ecosystem to support SaaS adoption. GSIs today represent nearly ~9% of all global IT spend.

In this era, the growth path for software companies in this era shifted to license / seat growth within accounts. NRR became the north star metric and therefore the optimization of expansion, renewals, and upgrades. This lowered switching costs (relative to the on-prem era) and birthed the “Customer Success” function to professionalize the processes behind account growth.

SaaS improved time-to-market and made product improvements effectively free. The lower cost of ownership meant the average number of SaaS applications per company grew from 8 in 2015 to 130 in 2022. For complex enterprises, value realization still depended on services-heavy, bespoke implementation work. This compounded with complexity as tech stacks broadened through the “unbundling” era of software. In this era, how the product was configured, integrated, and rolled out often determined actual ROI.

Entering the AI-Native Era - “Rent a Room”

In this emerging era, “software” is increasingly shifting to usage/value based models where customers effectively “pay as you go” for the value that they’re consuming.

The risk of a “bad” implementation increases exponentially because:

As a result, AI-native app companies today are each reinventing the implementation playbook from scratch. There is no “system of record” that captures customer level configurations and playbooks in a repeatable way. Implementations are increasingly a product problem (in fact – we are seeing an increase in implementation orgs structurally rolling up to the CTO). Companies are throwing bodies at the problem – and they’re expensive ones (in the form of “FDEs” too):

The last generation of customer success software (i.e. Gainsight, Catalyst) was largely a disappointment. The main challenges they faced were  1) mediocre ROI and 2) CS leaders had thin budgets and 3) existing solutions were largely reactive to what happened (oftentimes too late) vs. proactively recommending intervention and 4) data ingestion was massively painful.

This is now changing. The AI-era is blurring the line between pre and post sales as we move to a continuous delivery model. In this world, the implementation org is no longer a cost center, they are becoming a core revenue driver.

Early observations in the market suggest:

The bottom line is that the onus of ownership is shifting from the customer (in the pre-SaaS world) to now almost entirely on the vendor. Getting in the door is now easy, staying relevant towards actually delivering value is much more difficult.

So What Does this Mean?

For Enterprise AI Apps, the implementation layer is emerging as the true battleground for category leadership. What endures is a vendor’s ability to implement, align, and maintain AI systems in live environments.

So the questions for a company in this space become:

AI-native companies need to cross a new kind of chasm. The willingness to try is largely there, the willingness to stay is yet to be seen. We believe this dislocation creates a unique “why now” for a new “system of record” that is centered on the existing customer and enables continuous, ongoing implementations to emerge.

There have been a handful of new companies that have emerged to tackle this problem and automate implementations leveraging AI. There’s three main approaches:

As last mile delivery of software — in particular agentic software— becomes increasingly critical we know that the “FDE” role is only going to continue to grow in popularity. Implementations are becoming a front office problem and there’s a massive opportunity to help support this delivery problem as we shift into this new era of software consumption.