Are you ready for AI? Seven questions most leaders cannot answer yet.
Readiness has little to do with your tech stack. It has a lot to do with seven questions, and most teams can answer three.
Before we build anything, we score seven things. Try it now, out loud:
Value clarity. Which number do you want to move: revenue, profit, or predictability?
Alignment. Do your leaders agree on it?
Workflow legibility. Can you describe how the work gets done today, step by step?
Data readiness. Is the data where the workflow needs it, and roughly clean?
Engineering capacity. Who connects the pieces?
Internal ownership. Who owns the result after the consultants leave?
Change appetite. Will people change how they work?
Low scores are not a reason to wait. They are the first items on the roadmap. Data readiness usually gets fixed inside 30 days. Ownership takes one conversation.
The dangerous score is the one nobody has taken. That is how a company ends up eight months into a pilot with no idea why it stalled.
Which of the seven would you score lowest, and who else in your company would agree?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
Your board asked for AI results. They mean something specific.
When a board asks what you are doing about AI, they are not asking for a tour of your tools. They are asking a question with a number in it.
Board members read the same headlines you do. They know AI is supposed to matter. What they cannot tell is whether it matters here, in this company, this year.
So "what are we doing about AI" means three things:
Which number will it move. Revenue, profit, or how predictable the quarter is.
By how much, by when. A target and a date, not a roadmap slide.
Who is on the hook. One name, not a committee.
Most AI updates answer none of these. They list tools, pilots, and headcount trained. The board nods. Nothing was decided, and the same question comes back next quarter, a little sharper.
Answer those three and you stop reporting activity. You start reporting a plan against a number, which is the only kind of AI update a board remembers.
What number would you put on the next board slide?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
A pilot that has run for nine months is not a pilot. It is a job nobody wants to finish, and everyone can see it.
Here is how it happens. Someone builds a proof of concept. It works, sort of. It gets shown around. Everyone agrees it is promising.
Then it stalls, because finishing it would mean:
Picking a real number it has to move.
Putting a name on the result.
Letting real users decide if it is good enough.
None of that is comfortable. So the pilot keeps running, "gathering learnings," and the budget line quietly renews.
A working workflow needs a deadline and a scoreboard. Ours: prototype in a week, live and in testing by day 30, judged against criteria we agreed before we built it. If it misses, we keep working at no cost until it meets them.
How many pilots does your team have running right now, and how many have an end date?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
Why your team is not using the AI tools you bought
People do not use tools that make their day harder. Even smart tools. Even expensive ones.
Adoption fails for boring reasons:
The tool lives somewhere else. Another tab, another login. It loses to habit every time.
Nobody showed them the first win. They tried once, got a mediocre answer, and stopped.
It was sold as replacing them. Nobody adopts the thing that ends their job.
Fix all three and usage follows. Build it into the tools they already open. Train them, hands on, every two weeks, on their own work. And say the quiet part out loud: agents multiply people. This is not a headcount play.
Adoption is not the last step. It is the product. A workflow nobody uses moved nothing, no matter how good the demo was.
What is the one AI tool your team was supposed to use this year? Did they?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
The best first workflow is rarely the exciting one. It is the one that is live in 30 days and moves a number you already report.
Every company has an AI wish list. Chatbots, forecasting, content, research. The list is not the problem. Order is.
We pick the first workflow by three tests:
It sits on a number. Revenue, profit, or predictability. If it does not, it waits.
The data is already there, or can be cleaned in 30 days.
Someone will use it tomorrow, in the tool they already open.
That usually points to something modest. Quote turnaround. Follow-up sent within a day. Renewal risk flagged 60 days out.
Modest and live beats ambitious and parked. Once one workflow moves a number, the second and third get easier to fund and easier to build. The exciting one is still on the list. It is just third.
What is on your list, and which one passes all three tests?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
In week one, you should be clicking on something. If all you have is a deck, you have agreement, not progress.
The AI industry runs on decks. Vision decks, strategy decks, roadmap decks. They are easy to make and easy to agree with. They are also easy to forget.
A working prototype is different. It is small, ugly, and real. You use it and something happens:
You react. "That is not how we do it." Good. Now we know.
Your team reacts. They tell you in five minutes what a workshop would take a day to surface.
The scope gets honest. Half the wish list turns out to be one workflow.
Reactions are cheaper than requirements. That is why we put a prototype in front of you in the first week, not a document about one.
When was the last time you clicked on the AI thing you were shown?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
Revenue, profit, predictability: why we trace everything to three numbers
Every AI initiative claims to create value. Ask which number it moves and the room gets quiet.
Strip any company down to what a board, a buyer, or an investor actually pays for, and you get three numbers:
Revenue. How much comes in.
Profit. How much of it you keep.
Predictability. How sure you are of the first two.
Everything else is a driver of one of those. Pipeline, margin, churn, cycle time, forecast accuracy: each one traces up to revenue, profit, or predictability. That is why they are the root of the value tree, and why every workflow we build has to sit on a branch of it.
If a workflow cannot be traced to one of the three, it is a project, not an investment. Interesting, maybe. Fundable, no.
Which of the three is under the most pressure in your company right now, and which of your AI efforts touches it?
If you’re an executive who wants outcomes from AI, not noise: start with the number you need to move.
Seven dimensions scored. Then software you can click through, not a slide about it.
Day 14
A roadmap tied to the numbers your board reads
What to build, skip, and sequence, and why. Every workflow mapped to revenue, profit, or predictability, with the early signal that shows it is working.
Day 30, 60, 90
A new workflow live every 30 days
Workflow 1 live by day 30. Improve the last, deliver the next. Three live by day 90.
Throughout
Training every two weeks, and a standing commitment
Your team learns to run what we ship. Miss the standard we agreed? We keep working at no cost until it is met.
*From completion of discovery and access to your data and systems. Full 90-day plan →
Your readiness scored on seven dimensions, free. Then a working prototype of the first workflow for you to react to.
Plus one quick-win tool: an interview scoring tool, an economic buyer map, or a dynamic competitive battle card.
Within 14 days
A roadmap tied to the numbers your board reads
What to build, skip, and sequence, and why. Every workflow mapped to revenue, profit, or predictability, with the early signal that shows it is working.
Every workflow sits on a branch of the value tree, with the reasoning behind its place in the sequence. Written to hold up with a board or an investor.
Day 30
Workflow 1 live and in testing
Real data, real users, and a standard we agreed before building. Training is already underway so it gets adopted, not just built.
Days 30 to 60
Iterate workflow 1, deliver workflow 2
We fix what is awkward in workflow 1, in what goes in and what comes out, while workflow 2 ships.
Days 60 to 90
Iterate workflow 2, deliver workflow 3
Same rhythm. One workflow further down your roadmap.
Throughout
Training every two weeks, and a standing commitment
Your team learns to run and extend what we ship. If a workflow misses the standard we agreed before building it, we keep working at no cost until it meets it.
*Measured from completion of discovery and access to your data and systems.
Questions we get
Asked and answered
What does it cost?
The readiness score is free. The roadmap, the workflows, and the training are priced per engagement after the score, so the scope matches what the number can justify. You will have a price before the prototype, and nothing after that is a surprise.
How much of our team's time does this take?
Discovery is a few working sessions with the people who own the workflow and the data. After that, one owner on your side for each workflow and the training hour every two weeks. We do the build; your team reacts and adopts.
What happens if a workflow does not work?
Before we build it, we agree in writing what "working" means: the number it moves and the standard it has to meet. If it misses, we keep working at no cost until it meets the standard. That commitment is in the agreement.
Do we need new software or a migration?
No. We build inside the tools you already run: your CRM, your inbox, your spreadsheets, your systems of record. The workflow shows up where the work already happens.
Who owns what we build?
You do. The workflows, the prompts, the documentation, the results. The training exists so your team can run and extend them without us.
How do you handle our data and security?
Inside your permissions and your policies. Access is scoped to the workflow, every action is logged, and model choice follows your rules, not our convenience. We sign your NDA before discovery starts.
Why three numbers, and what if ours is different?
Revenue, profit, and predictability are what a board, a buyer, or an investor pays for; everything else is a driver of one of them. Your number will trace to one of the three. If it does not, that is worth knowing before anyone builds.
What is the first conversation like?
Thirty minutes. We ask which number is under pressure, what your team has tried, and where it stalled. You leave with a view on which workflow we would build first, and what it would move. No deck.
Scope your first workflow
An AI department for less than the cost of one senior AI hire.
Two operators, one stance: agents multiply people, and every workflow traces to a number.
What we are here to do
Our mission
Working agents, adopted by real teams, traced to real numbers. Agentic outcomes, delivered by operators fluent in how the work actually gets done.
Agents multiply people. Never headcount replacement as the pitch. That stance is why our work gets adopted.
You own it all at the end. The agents, the workflows, the results.
What we stand on
Our values
Goodness
We do the right thing, no matter what. Integrity before profits, always.
What this means for you
A partner who is focused on doing what is right for you, not for our bottom line. We’ll give you advice you can trust and you’ll get the truth, even if it’s hard to give.
Greatness
We do everything as best as possible. No cutting corners or phoning it in.
What this means for you
We create everything at our best. Every interaction, every deliverable, no exceptions. What we build is focused on making you and your team far better.
Agency
We build ownership, create options, and take burdens off your plate.
What this means for you
We create space and freedom to work on higher impact efforts for you and your organization. Everything we build, you own and understand.
The founders
The operators
Brian Murphy
Co-Founder · Architecture & Build
Brian was a leader in go-to-market for twenty years at Oracle Data Cloud, Simon, Yobi, and Verve. He built and shipped AI products at Yobi and Verve, inside companies where getting the sales floor to use them was the hard part. At AGENXI he owns delivery: the value tree, the agent architecture, and the code that ships.
Joseph Zito
Co-Founder · Strategy & Client Leadership
Joe was an operating executive for twenty years: Group VP at Oracle Data Cloud, CRO at Custora, founder of Rev(X) and (X)Form. Through Rev(X) he has partnered with more than 100 B2B companies, from Series A startups to S&P Global. At AGENXI he owns client engagement, the offer, and pricing.
Organizations served through our Founders’ Rev(X) and (X)Form consultancies
AGENXI is new. The experience behind it is not.& many more
Principles
How we operate
AGX · A
Operator-fluent
We have run these functions and partnered with more than 100 B2B companies. We build for how the work actually gets done, so what we ship works in real hands on first contact.
AGX · B
Production first
Working prototypes over decks. If it does not run inside your workflow, it does not count.
AGX · C
Measured claims
No numbers we cannot defend. Every workflow is tied to revenue, profit, or predictability before build, with a standard for done that we agree in writing.
AGX · D
Agents multiply people
Judgment stays human and the pitch is never headcount. That stance is why what we ship gets used.
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