Research and writing on the commercial operating model for the agentic AI era

Your AI is ready.
Your business model isn't.

Seat pricing plus an AI tier isn't a strategy. It's a value creation risk sitting in your numbers. This is the framework, the evidence, and the nine layers that have to change.

"Every enterprise is racing to deploy AI. Almost none have asked what happens to their commercial model when it works."

From Dead Model Walking

The commercial operating model, not the technology, decides who wins agentic AI.

Flagship Report · First Edition

The State of Agentic Commercial Readiness

34 vendors audited for real agent access, mapped to the nine layers. 53% ship an MCP server: the two layers that decide price and pay have zero.

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The Framework

The Agentic Commercial Model

A structured commercial operating model for the agentic AI era: nine layers a software business must rebuild when its customers, its users, and its competitors are deploying AI agents at scale. Move one layer and leave the rest untouched, and the model leaks at the seams you didn't touch.

01

Organisation Design

Whether the commercial structure embodies the new operating model, rather than describing how work used to be done.

02

Go to Market

Reaching and winning the buyer who actually decides now: including a buyer's own agents shortlisting vendors.

03

Pricing & Packaging

Rebuilding the value metric so price scales with value delivered, not seats consumed.

04

Sales Strategy & Enablement

Equipping teams to sell outcomes rather than features, and answer why pay for this if the AI does the work.

05

Compensation

Rewarding the behaviour the AI strategy actually needs, so the comp plan pulls with strategy instead of against it.

06

Metering & Entitlement

Measuring what the customer consumes and values: the precondition for usage or outcome based pricing.

07

Adoption & Customer Success

CS structured and measured to drive and prove value realisation, not just manage renewals.

08

Revenue Architecture

Recognition, forecasting, billing and unit economics rebuilt for variable, consumption and outcome revenue.

09

Commercial Systems

The CRM, CPQ, billing and analytics stack capable of running the new model, not blocking it.

Read the Full Framework → Origin, definition, and the complete nine layer breakdown.

Built By an Operator

Twenty years inside the commercial engine, not beside it

Fessal Rahman

Fessal Rahman is the originator of the Agentic Commercial Model and author of Dead Model Walking and Dead Gods Walking. His career spans McKinsey, Bain, Cloudinary, The Access Group, Emarsys (SAP), Exasol, and enterprise technology companies including Lenovo and Teradata.

McKinsey & Company Bain & Company Cloudinary The Access Group Virgin Media O2
Full Bio →
I

Dead Model Walking

Why agentic AI breaks the business of software, and the model that wins.

II

Dead Gods Walking

How agentic AI builds around business leaders who won't adapt.

Books, Ebooks & Writing →

Twenty years of operating record

$50m to $105m

Usage-priced developer platform

Doubled in 2.5 years. NRR up 15%, win rates up 10%, unit economics up 25%. Consumption model rebuilt, growth pricing built into every contract.

121% NRR

Marketing automation SaaS

NRR from the low 100s to 121%. New business ACV up 25% through a new sales methodology and packaging.

90% converted

Enterprise data platform

90% of the installed base moved from perpetual to subscription inside four years, with new comp design and territory management. Growth returned.

20 companies

PE-backed software group

Commercial function across 20 businesses, around £1bn combined. NRR up 4%, GRR up 2%, forecast accuracy improved.

As heard on Building Great Tech: How to Price Your SaaS in the Age of AI →

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Playbooks, ebooks and both books are in Resources.

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