GREG JONES | BUILT WITH AI
— WHERE AI PAYS
Know Where to Invest in AI —
and Where Not To
Before you spend another dollar on AI tools, subscriptions, or projects — learn which opportunities are worth pursuing, where AI actually belongs, and what to do first.
For founders and leadership teams of $5M–$50M service firms.
The question isn't where you can use AI. It's where AI is worth the investment.
A return isn't only revenue. It can mean more capacity, better margins, faster delivery, less rework, or less dependence on your key people.
25+ Years
U.S. intelligence & cybersecurity · high-consequence systems
Founders & C-Suite
Advising leadership teams on complex strategy, operations, and technology decisions
Founded Mandiant Labs
Built and co-led the research, innovation, and malware-analysis division.
01 — The Problem
Your Firm Is Full of AI Activity. Where's the Return?
Your team already uses ChatGPT. Someone built a custom GPT. There are automations running. You're paying for AI subscriptions. Someone has a folder full of prompts.
But ask the harder question:
Is any of it changing the economics of your business?
Is it adding capacity without adding headcount? Is it cutting hours of expensive work? Is it scaling the expertise of your best people?
More Capacity
without adding headcount
Better Margins
less time, rework, and cost in delivery
Less Key-Person Risk
work keeps moving when critical people are unavailable
AI is everywhere in your firm.
That doesn't mean the investment is paying off.
02 — The Filter
Stop Asking "What Can AI Do?"
Start Asking "Where Is AI Worth the Investment?"
It doesn't matter what AI can do if it isn't pointed at the right part of your business.
The masterclass gives you a six-part filter for deciding which opportunities are worth pursuing, whether AI belongs in the solution, and what must be true before you invest.
The AI Investment Filter
Six questions to separate interesting ideas from investments worth pursuing — and decide where AI belongs.
Value
Does it move something that matters?
Leverage
Does one solution create value across the firm — and keep creating it?
Mechanism
What's the best way to solve it — AI alone, human + AI, or no AI?
Control
What happens if AI is wrong — and what stays human?
Foundation
What must be in place first — and what can we build once to enable more?
Ownership
Who owns the outcome — and how will you measure the return?
The path is simple:
04 — Proof
From complexity to clarity
11 Business Units.
One Clear AI Investment Strategy.
70+ people. Multiple business lines. One prioritized path from assessment to implementation.
Greg completed an organization-wide AI diagnostic — separating where AI could create value, where automation was the better answer, where human judgment had to stay, and which shared capabilities could create leverage.
What the assessment delivered:
Clear investment priorities — where AI was worth the investment, and where it wasn't
The right solution for the work — AI, human + AI, traditional automation, or no AI at all
Shared capabilities with leverage — one investment supporting multiple business lines, including a development capability designed to speed future delivery
A sequenced path to implementation — what needed to happen first, what came next, and how results would be measured
Leadership approved the direction, and the highest-priority initiatives are moving into implementation. The work has since led other organizations to request similar assessments.
The masterclass shows you how to apply the same decision logic in your firm.
03 — What You'll Learn
In 45 Minutes, You'll Learn:
Why the best first investment may be a shared capability that unlocks several more — not an AI use case at all
Why the easiest workflow to automate is often not the one worth doing first
When hiring, training, process redesign — or doing nothing — is a better investment than AI
What AI should handle, what your people must own, and where human review is still required
The numbers to capture before an AI project starts — so you'll know whether it produced a return
How to pick one high-value investment instead of launching scattered AI experiments
05 — Execution
AI Isn't the Outcome. Operating Leverage Is.
More capacity without matching headcount growth. Better margins. Less dependence on a few critical people. That's operating leverage. If it doesn't change the work or move the numbers, it doesn't count.
Start with one. Prove the return. Scale what compounds.
06 — Experience
Greg Jones — Diagnose before you deploy.
When the Stakes Are High, Judgment Matters More Than Tools.
25+ Years
U.S. intelligence and cybersecurity — high-consequence systems, sensitive information, and decisions where being wrong carried real cost.
Founded Mandiant Labs
Built and co-led the research, innovation, and malware-analysis division.
Advisor + Operator + Builder
From enterprise strategy to operating reality to technical execution — connecting the decision to what must actually work underneath it.
For your firm: clear decisions before you commit time, money, and people.
Where to invest. What to build. What to automate. Where human judgment must stay. Every decision grounded in business value, risk, confidentiality, and measurable return.
Where Should You Invest in AI First?
Watch the free 45-minute Where AI Pays masterclass and leave knowing where AI is worth the investment in your firm, where it isn't — and what to do first.
P.S. — You don't need more AI. You need the right first investment — and proof of return.
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