OUTCOME #1
One way of working, company-wide
The same task gets done the same way whether it runs through sales, ops, or finance. Quality stops depending on which person picked it up.
Services
AI enablement that lands on the work your team already does
You bought the licenses. Half the team never opened them and the other half is improvising.
Phos AI Labs makes your whole company fluent, role by role, in four to six weeks.
AI enablement is the work of getting an entire company to use AI well: the role-specific training, the playbooks, the policy, and the habits that turn purchased licenses into daily practice. Phos AI Labs builds the training around each role's actual work, ties it to live workflows, and measures adoption afterward.
The gap was never access. Your people already have the tools. Nobody has shown them where AI fits the job they were actually hired to do.
Claude (Anthropic) Partner · Select OpenAI Partner · CCA-F certified team
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40+ AI Systems
shipped to production in the last 6 months
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4 to 6 weeks
to working fluency, department by department
Trusted across 450+ builds
Why does AI training almost never change how a team works?
Because it teaches a tool to a room instead of a job to a person. Everyone leaves impressed, goes back to a full week, and the software sits exactly where it was on Monday.
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Licenses nobody opens
You rolled out seats company-wide. Usage concentrated in four people and flatlined everywhere else, and there is no report that tells you which four.
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Five different standards
With no written policy, some people avoid AI on anything that matters. Others paste client data into a free-tier tool without thinking twice. Both are guessing.
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The knowledge leaves with the session
Nothing gets written down, so the training has a shelf life. The next hire starts at zero and the company pays for the same room twice.
The UK Department for Business and Trade gave a thousand people Microsoft 365 Copilot licenses for three months and published what happened. Average use came to 1.14 actions per person per working day. Seventy-two percent said they were satisfied. The evaluation found no robust evidence that the time savings turned into productivity.
Satisfaction is not adoption. A room that enjoyed the session and a department that changed how it works are two different results, and only one of them shows up in a number.
What we do - What you get
Awareness is cheap. Fluency on the real work is the whole point.
This engagement trains people against the work they already own, and every session is tied to a workflow AI is going into. That is deliberate. The skill has to land on something real to survive the first full week back.
10 01
Deliverable 1 of 10
What you walk away with
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AI literacy baseline
The shared floor for the whole company: what these models do well, where they fail, and what never goes into one.
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Role workshops
Live, task-based sessions built for one role at a time. Sales runs a different session from finance because they run different weeks.
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Role playbooks
A written guide per role: where AI fits that job, where it does not, and how to tell the difference. Each person keeps theirs.
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Prompt library
The prompts that survived contact with real work, versioned in one place your team can reuse and improve.
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AI use policy
Plain-English rules on what is allowed, what is not, and where company data can go. Short enough that people read it.
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Adoption dashboard
Who is using AI, on what, how often, and which departments have gone quiet.
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Workflow tie-ins
Each department leaves with two or three of their own workflows already running on AI, so the skill has somewhere to land.
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Champion bench
One trained internal champion per department, briefed to answer the questions that come after we leave.
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Model refreshers
When a major model lands, your team gets the update and the revised playbook instead of falling behind quietly.
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Enablement report
Adoption before, adoption after, department by department, with the gaps named and a plan for each.
What actually happens once you start?
Role by role, department by department. Four to six weeks to working fluency.
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We watch how each role actually works
Before we train anyone, we sit with each department and study how the work really gets done, including the workarounds nobody put in the process doc.
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We build the session around what we found
Every workshop is written for one role and one week of real tasks. The exercises use the proposal due Thursday, the report due Friday, and the inbox waiting right now.
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We train on live work
People bring the proposal they owe on Thursday and leave with it drafted. The habit forms on something that mattered, which is the only place habits form.
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We leave a playbook every person keeps
Each role gets a written guide plus the prompts that worked. The sessions end. The playbook, the policy, and the prompt library stay inside the company.
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We measure adoption and close the gaps
Two weeks and six weeks out we look at who is actually using AI and who quietly stopped, then run the follow-up sessions where the numbers say they are needed.
Where does this sit in the engagement?
Enablement is phase two. Each phase ends with something you own and a decision about whether to keep going, so nothing here commits you to the next one.
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AI Consulting
The audit that finds where AI belongs and what it is worth.
See AI Consulting → - 02
AI Enablement
You are here. Your team gets fluent on the work AI is about to touch.
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AI Implementation
Agents and systems that run the work, built and embedded.
See AI Implementation →
This is for you if:
- Your team has AI tools but adoption is uneven or stalled.
- Leadership wants AI to be how the team works, not a side experiment.
- You'll let us tie training to real workflows, not run it in a vacuum.
This is not for you if:
- You want a single all-hands webinar and nothing after it.
- Nobody will change how the work actually gets done.
- Your team has no AI tools yet. Start with foundations first.
What does enablement look like once it is scoped?
Two ways in. One is the full role-by-role engagement. One is a deep rollout of the model your company has already standardized on.
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Team Training
The role-by-role engagement: we observe each department, train on their real tasks, and leave a playbook every person keeps.
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Claude for Business
As an Anthropic partner, a real Claude rollout across the company: projects, permissions, shared context, and the training that makes it stick.
Why does AI fluency look different in every industry?
A logistics dispatcher, a claims adjuster, and a paralegal all lose time to desk work. None of them lose it in the same place. The training reads each operation on its own terms.
Don’t see your industry?
If your work runs on drafting, summarizing, or answering from your own documents, there is a fit.
Book a callWhat does this actually change?
Companies come to Phos AI Labs because the tools landed and the habit did not. They leave with one standard, skills written down, and a team that stops flinching every time the models move.
OUTCOME #2
Skills that stay after we go
The playbooks, the policy, and the prompt library live inside your company. Onboarding a new hire on AI becomes a document instead of a favor.
OUTCOME #3
A team that keeps up on its own
When a major model lands, your champions read the change and update the playbook. Your company absorbs the next release instead of waiting for the next vendor.
Does enablement actually show up in the numbers?
It shows up in three places: administrative hours that disappear, work that stops routing through one person, and teams who start building their own automations without calling us.
GAF
The largest roofing contractor training program in North America, rebuilt so 51 field trainers run 1,200 events a year from a phone.
We were using spreadsheets and hoping nothing fell through the cracks. After working with Phos AI Labs, their AI implementation handles 75% of the administration and the team handles the work they're actually great at.
Matt Hegge, Director, GAF
LowCode Agency
Five departments audited, then the two AI employees the findings pointed at, including one that read 2,400 dormant leads.
Every proposal needed me in the room. The sales team couldn't move without me, which meant I was the bottleneck in my own company. Now the AI handles the routine ones. I review the complex cases. That's the job I should have had all along.
Jesus Vargas, Founder and CEO, LowCode Agency and Phos AI Labs
Payroll Mexico
Weeks after launch the owner was configuring his own recurring AI tasks, which is the clearest sign enablement worked.
I set up two recurring tasks, one daily, one weekly. We have a bunch of leads to follow. I don't know how Phos AI Labs does this. I am amazed.
Franklin Delano Frith II, Owner, Payroll Mexico
Read the full story → - 7 hrs of daily overhead eliminated
- ~$300K projected new ARR from outbound alone
Why Phos AI Labs over a training vendor or an internal champion?
Most training firms hand you a curriculum and a completion rate. Phos AI Labs trains against workflows we are also building, so the skills land on systems that are still there in month six.
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We build what we teach
We are an implementation firm that trains, so every session points at a workflow going into production. The team teaching your people is the same team changing the systems those people will use next quarter.
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We have actually done this
A new AI training company launches every week with a landing page and a slide deck. Most have never run a rollout inside a mid-market operation or trained 51 field workers who are experts in something other than software. We have, again and again.
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The hire you can’t make
A senior AI enablement lead costs $250,000+ and takes six months to find, and one person can not cover every department at once. Phos AI Labs brings the whole team the week you start.
How much does AI enablement cost?
AI enablement with Phos AI Labs starts at $10,000 and scales with how many people and departments are in scope. Most companies find that the seats they already pay for cover a meaningful share of it.
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Department pilot
from $10,000 fixedOne department, four to six weeks, every deliverable above scoped to that team. The usual move when leadership wants a result they can point at before committing the company.
Book a strategy call -
Company-wide enablement
from $10,000 by scopePriced by headcount and departments in scope. Every role trained, one policy, one prompt library, one adoption dashboard across the business.
Talk scope -
Enablement inside an embedded engagement
from $15,000 to $50,000 /mo.Training folded into an ongoing build, so each new system ships with the people who run it already fluent on it.
Talk scope
You are already paying for this twice. The licenses sitting unused have a monthly cost. So do the hours your team spends doing work those licenses were bought to absorb. A department that goes from 20% to 80% weekly AI use recovers more in a quarter than the engagement costs, and the seat count on the invoice never moves.
Keep going
Four ways to see where your team stands before you book anything.
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AI Readiness Scorecard
Ten questions, a personalized score. See where your company stands before you talk to anyone.
Explore → - 02
Claude Code for Business
A free mini course for non-technical founders and operators. The fastest way to give part of the team hands-on fluency this week.
Explore → - 03
Deploy Claude Blueprint
The six-step guide to rolling Claude out across a team, free.
Explore → - 04
Case Studies
The full library of what Phos AI Labs has shipped, with the numbers behind each build.
Explore →
In partnership with
FAQs
What is AI enablement?
AI enablement is the work of getting a whole company to use AI well: the role-specific training, playbooks, policy, and habits that turn purchased licenses into daily practice. Phos AI Labs builds the training around each role's actual work, ties it to workflows AI is going into, and measures adoption afterward.
What is the difference between AI training and AI enablement?
AI training is an event where people learn a tool. AI enablement is the system around it: role playbooks, a written policy, a shared prompt library, internal champions, and adoption tracking that shows whether behavior changed. The difference is scope. Training is the session. Enablement is everything that makes the session last.
How long does it take to get a team fluent on AI?
Four to six weeks per department to reach working fluency. Phos AI Labs spends the first week observing how each role really works, runs task-based sessions on live work, leaves a playbook per role, then measures adoption at two weeks and six weeks and closes the gaps.
How much does AI enablement cost?
AI enablement starts at $10,000 and scales with how many people and departments are in scope. A single-department pilot is the common starting point. Enablement folded into an ongoing build engagement runs $15,000 to $50,000 per month alongside the implementation work.
Do you offer standalone training, or only alongside implementation?
Both. Standalone enablement is a real engagement and companies buy it on its own. Results last longer when training runs beside implementation, because the skills land on workflows that are actually changing, and the playbook describes a system that still exists in six months.
Half our team already uses AI and the other half never touched it. Does that work?
That is the most common room we walk into. The confident half usually has blind spots on accuracy and data handling. The hesitant half usually needs one example from their own week. Sessions are built per role, so both groups leave with something they did not have.
Do we own the playbooks and the policy?
Yes. The role playbooks, prompt library, AI use policy, and adoption data live inside your company and are yours to keep. New hires get onboarded from the same documents, and Phos AI Labs updates them when a major model changes what the guidance should say.
Other government studies say Copilot saved people 26 minutes a day. Which one is right?
Both, and the difference is the method. The cross-government trial and the Department for Work and Pensions trial asked people to estimate their own time savings and reported positive results. The DWP evaluation says in its own limitations that licenses were not allocated randomly. The Department for Business and Trade study looked for productivity evidence and could not find it. That is the whole argument for measuring a number before you start rather than surveying people afterward.