Commercial AI.
Revenue Architecture.
Results, Not Roadmaps.
The gap between an AI platform and AI revenue is a commercial architecture problem. The Reily Group builds that architecture — for enterprises, platforms, and agencies that need results, not reports.
Most organizations already have the capability. What they're missing is the commercial infrastructure around it — the pricing model that holds under negotiation, the GTM motion that generates qualified pipeline, the co-sell architecture that scales, and the operating cadence that converts pilots into signed contracts. That infrastructure is the work.
When to call
Common signals the commercial architecture work needs to happen now:
- AI platform launched — pipeline hasn't followed
- Co-sell or partner motion is generating activity, not yield
- AI pricing is intuition, not a defensible commercial model
- GTM is disconnected from revenue accountability
- Pilots proliferating; enterprise contracts aren't closing
- Board wants an AI strategy that survives contact with a client
What we build
In the first engagement:
- Commercial architecture diagnosis + competitive position
- GTM motion design + pricing model framework
- Partner co-sell architecture + deal structure templates
- Operating cadence + revenue-accountable KPIs
- Decision-ready commercial brief + scorecard
What we do
Two practices. One operating discipline. Sized to the problem.
Commercial AI Strategy & Commercialization
For organizations building or deploying AI platforms at scale — where the gap between capability and commercial return requires purpose-built architecture.
Commercial AI GTM Architecture
Building the commercial foundation for AI platforms: go-to-market strategy, sales motion design, ICP definition by vertical, pricing model development, and the operating cadence that converts platform capability into signed contracts. Revenue accountability from day one, not capability showcasing.
- GTM motion design + ICP segmentation
- Pricing model development by deal type
- Sales enablement + process architecture
- Revenue accountability framework + pipeline KPIs
Agentic AI Platform Commercialization
From platform capability to enterprise revenue: vertical use case mapping, client-specific pricing architecture, enterprise proof-of-concept design, and the structured pathway from pilot to multi-year contract. Built for agentic platforms operating at Fortune 100 scale and complexity.
- Use case mapping by vertical + business function
- Pilot-to-contract pathway design
- Pricing architecture by client type + deal size
- Enterprise deal structure + governance model
Partner & Co-sell Strategy
Structuring high-yield alliances — ISV co-sell, agency partnerships, channel motions — that expand market coverage without proportional cost. Designed around actual deal architecture: who initiates, who owns, how it prices, and how it closes. Not a slide deck. A motion that works in the field.
- Co-sell motion design + field enablement
- ISV + platform alliance architecture
- Partner economics + deal split structure
- Joint pipeline governance + cadence
AI Operating Model & Governance
The internal discipline to deploy, measure, and scale AI initiatives across the enterprise: evaluation frameworks, governance structures, KPI accountability, rollout sequencing, and the operating cadence that sustains commercial progress beyond the initial engagement.
- Governance + risk evaluation frameworks
- KPI accountability systems + scorecards
- Rollout sequencing + change management
- Operating cadence design + decision rights
Practical AI for Businesses That Want to Win
Most businesses know AI matters. Very few know where to start. The ones that figure it out first build a real competitive advantage — and it compounds. This practice is built to get you there fast, without the vendor hype or the wasted pilots.
AI Opportunity Assessment
A focused audit of your business that identifies exactly where AI can save time, reduce cost, and drive growth — ranked by impact and how fast you can act on it. No vendor pitches. No generic frameworks. A prioritized roadmap built for your specific operations.
- Operations + workflow audit
- AI opportunity mapping by function
- Prioritized roadmap: impact vs. effort
- Tool + vendor recommendations
2–3 weeks
AI Implementation Sprint
From roadmap to running. We configure the right AI tools for your specific workflows, build the automations that connect AI to your actual business processes, and train your team so adoption actually happens. Not installed — running. With your people using it and your operations measurably improved.
- Tool selection + configuration
- Workflow automation + integration
- Team training + adoption support
- Measurement: time saved, output improved
4–8 weeks
Ongoing AI Advisory
First-mover advantage in AI compounds quickly. Monthly advisory keeps your tools current, expands to new use cases as the technology evolves, and ensures your business keeps pulling ahead as competitors start catching on. Access to a senior operator who tracks what's actually working across industries — not what's being marketed.
- Monthly strategy + implementation review
- New use case identification + rollout
- Tool evaluation + vendor management
- Competitive AI landscape monitoring
Monthly retainer
When growing businesses call
You know AI is important but don't know where to start — and you're tired of generic advice
You've tried ChatGPT but it hasn't connected to your actual business workflows
Your competitors are talking about AI and you want to move before they figure it out
You want to do more with the team you have — not hire more people to do manual work
You need someone to cut through the vendor hype and tell you what's actually worth doing
You're growing fast and AI is the leverage that lets you scale without proportional headcount
How we work
A simple operating model designed to ship commercial outcomes: diagnose, align, execute, measure — without strategy theater.
2–3 weeks
Map where AI investment is and isn't generating commercial return. Baseline the GTM position, partner motion, and pricing model. Produce a decision-ready view of what to change and why. Clarity in weeks, not quarters.
1–2 weeks
Develop the funded commercial architecture — GTM motion, pricing model, partner structure, or operating governance — with clear owners, sequenced priorities, and an execution cadence designed to ship.
6–16+ weeks
Embedded operating leadership to drive the roadmap, manage partner and client alignment, navigate internal friction, and sustain commercial momentum. Not oversight from a distance. Active operating presence until outcomes show up in the numbers.
Continuous
Revenue-accountable scorecards, learning loops, and course-corrections anchored to pipeline, conversion, contract value, and partner yield — so progress survives beyond the engagement because it is measured, not assumed.
Proof
Evidence matters. Outcomes from prior operating roles and active engagements — framed carefully where required.
Commercial outcomes
- $550M+ incremental revenue delivered in a prior operating leadership role via experimentation, conversion architecture, and platform optimization at scale.
- 20%+ conversion lift and ~80% engagement lift from an AI-assisted B2B marketplace initiative — anonymized. Use cases tied to KPIs, not demonstrations.
- Active commercial AI platform work: embedded pricing architecture, GTM motion, and partner co-sell strategy for a major enterprise agentic AI platform. Clients include Fortune 100 organizations across financial services, consumer, and marketing verticals.
- Global operating cadence across 51 countries in prior executive roles, including founding and scaling a 6,000-person global commerce organization.
What "AI-native" means here
- Use cases tied to KPIs — not capability demonstrations
- Pricing that reflects value delivered, not hours billed
- Partner motions designed around deal architecture, not slide decks
- Governance: risk, evaluation, rollout sequencing, client trust
- Measurement: offline evaluation + online experimentation
- No AI theater. No pilot parking lots. No strategy that stops at the deck.
Want a sample commercial architecture brief?
We can share a redacted example after an intro call.
About
Led by Jon Reily — operator, not advisor. Senior bench when needed.
The Reily Group is an executive-led enterprise AI commercialization partner. We work with enterprises, platforms, and agencies when the gap between AI capability and AI revenue needs to close — fast.
Led by Jon Reily (founder of Dentsu Commerce, ex-Amazon), The Reily Group brings 25 years of global executive operating experience. Jon is currently embedded in commercial AI platform work at the operating level — building pricing architecture, GTM infrastructure, and partner co-sell strategy for a major agentic AI platform with Fortune 100 clients globally. He is not a consultant who advises on AI from a distance. He builds it from inside.
Jon also serves in select governance and community leadership roles.
Focus areas
Small by design. Senior by default.
Contact
Whether you're a platform with a commercial AI gap, an enterprise with a partner strategy that isn't generating yield, or a growing business that needs to figure out AI before your competitors do — share a few details and Jon will respond personally.
Start a conversation
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Email: jon@reilygroup.com
Engagements (typical)
Platforms · Agencies · Enterprises
Commercial AI GTM Sprint (2–3 weeks) — commercial baseline, GTM architecture, pricing model framework, and revenue-accountable scorecard.
Agentic AI Commercialization Leadership (8–16 weeks) — embedded operating leadership across pricing architecture, sales motion development, and partner alignment.
Partner & Co-sell Architecture (4–6 weeks) — deal architecture for co-sell, ISV, and alliance motions designed to close, not just generate pipeline activity.
Interim AI Operating Executive — fractional leadership to stabilize AI execution and drive the commercial cadence.
Growing Businesses · $5M–$100M
AI Opportunity Assessment (2–3 weeks) — operations audit, AI opportunity map, prioritized roadmap, tool recommendations.
AI Implementation Sprint (4–8 weeks) — tool configuration, workflow automation, team training, measurable outcomes.
Ongoing AI Advisory (Monthly) — keep current, expand use cases, maintain competitive advantage as the tools evolve.