The Hybrid Intelligent Enterprise.

AI agents and people in one team, under one set of rules. Hybrid here means AI and people. Not office and home. Not hybrid cloud.

Take the 5-point check See the eight steps

Sales finance headOwns the process and its rules

Claims agentDoes the work

Alone up to 200K · own tools

Priya NairFinance manager · decides above the limit

Above 200K

Audit agentChecks every claim

Never checks its own work

checks

Distributor claims · example

Definition What it is not AI on the org chart Governance Eight steps 5-point check

The definition

A company where AI and people work together as first-class citizens.

Both do the work. Both make decisions. Either one can hand a task or a decision to the other, in both directions, as long as they say why and how. Together they make better decisions, faster.

One named ownerEvery task and decision has one owner, AI or person. Never "the system".
Work moves both waysAI can pass a decision to a person. A person can pass one back to AI.
Both reasons are keptWhoever passes work says why. Both notes are stored side by side.
Authority is earnedA limit widens only when the record proves it should.
No one checks their own workMaker and checker are never the same teammate.
High-risk calls escalateTo a manager, then to leadership. Nothing is lost.

Does the workAIPersonAI agent or person

DecidesAIPersonAI agent or person

ChecksAIPersonAI agent or person

A different seat checks the work. One named owner per task.

Claims agent · limitsSet by you, from the record

1 · AdvisesA person decides every caseEvery claim goes to a personWeeks 1–4

Now2 · Decides up to a limitAbove it, a person decidesAlone up to 200KAfter a clean record

3 · Higher limitWhen you raise itUp to 500KOnly if you change the rule

after a mistake

Tasks per week, from the record

you narrow it after mistakes · it stays until you change it · example

Five things an Intelligent Enterprise is not

Myth 1It is not a maturity level.

One score cannot rate a company that makes thousands of different decisions a day.

InsteadJudge it one decision at a time: who leads, who does the work, who checks.

Myth 2It is not about more AI tools.

Agents with no named owner are sprawl, not intelligence.

InsteadWhat matters is who owns each decision, and who checks it.

Myth 3It is not AI replacing people.

AI and people sit on the same org chart, in the same kinds of roles.

InsteadAny role can be an AI agent or a person. No one checks their own work.

Myth 4It is not something your vendor gives you.

A vendor governs the agents on its own stack.

InsteadYour rules, your cost limits and the record of your decisions stay with you.

Myth 5It is not a policy document.

A policy is where governance starts.

InsteadIt works only when it runs inside every task and every decision, every day.

AI on the org chart

Seven questions. Seven answers.

Next to your people. Same roles, same rules. Try the mix below: any seat can be an AI agent or a person.

Does the work

Decides

Checks

AI drafts. A person decides. Another agent checks.

The agent prepares the case. Your person makes the call and writes why. A separate audit agent checks the decision against your rules.

Same rules for every seatNo one checks their own workOne named ownerCost set before it runsBoth reasons recorded

Where does AI sit on your org chart?

Inside a team, next to your people. Every team has several roles: doing the work, deciding and checking. Any role can be an AI agent or a person. AI drafts and a person refines. A person does the work and AI checks it. One AI agent checks another.

How does AI earn its place?

Like a new employee. It learns your processes and history, not the vendor's defaults. A teammate checks every task at first, and both record why. It earns authority one task at a time, only when its track record earns it.

What goes into AI's job description?

The same six things as your people's: responsibilities, decision rights, handoffs, escalation, limits and checks. Who checks my work? Never me.

Who does AI report to?

The same chain and rules as your people. Escalation goes by complexity and impact: team member, then manager, then senior leaders. Cost is estimated before every task, with a limit no member can exceed.

What does the org chart remember?

Every decision, with its reason, in one place in your environment. It records the work, not surveillance of people. Early on it feels like extra effort. Over time it becomes your enterprise memory.

What changes when AI is on the org chart?

Nothing is lost at handover. No one checks their own work. Every decision and reason is recorded. Cost is known before the work. Memory stays through every change of vendor.

What kind of platform should run this team?

One built for the whole team, not one agent. Vendor neutral. In your environment. No lock-in. The same rules for agents you buy, agents you build and your people.

Governance

One set of rules for AI and people, on your side.

Roles, checks, authority

Every member has a job description

Every decision has one named owner, never "the system". No one checks their own work. Authority is earned through a track record, one task at a time.

Access

What the job needs. Nothing more.

Which systems each role can use, what it can do in each (view, create, change or approve) and which data it can see. Every AI agent gets its own login, with the access of its role, not of the person who set it up.

Escalation, cost, record

Named people, limits, and memory

Escalation to named people by complexity and impact. Cost estimated before the work runs, with a limit. Every task and decision recorded with the reasons of AI and people, unchanged and open to your auditors.

Claim C-20418420K · North region

03Senior leadersAbove 2.5M
The largest or riskiest calls. Nothing is lost on the way up.
02ManagerUp to 2.5M
Higher value or more complex, as your rule sets out.
Reply within 4 hours · silence is never a yes
01Team memberUp to 200K
The named person for this kind of case. Routine exceptions stop here.
Above this limit · passed up with the reason

One claim · example

Bought and builtSame stop switch, budget and recordSAP JouleLangGraphClaims agent

Whole agencyDefaults set once, used by every new agent

Refunds above 50K need a person
No agent sees payroll

Each agent · Claims agentWhat it may do alone, when it must ask, what it must never do

Approves alone up to 200K
Asks Priya Nair above that
Never changes a scheme

Rules inherit inwards · example

Discover every agent

You can't govern what you can't see.

LeafCraft connects to your ecosystem and finds every agent you run: the ones vendors shipped inside your software and the ones your teams built. Then each one gets an owner, comes under your rules, or is removed.

Shadow AI endsEvery agent ownedUnwanted agents removedMemory starts from day one

How discovery works

Inside software you buySwitched on by vendor updates

CRMERPHR systemService deskOffice suite

Built by your teamsPilots, scripts and side projects

LangGraphCrewAINotebooksAutomationsCopilot studios

LeafCraft connects to your ecosystem and finds every agent

One registerexample counts

23found

9no owner yet

11governed

3retired

How to put it in place

Eight steps. One process at a time.

This is how we run it with every customer, one process at a time.

Start with step one

One ownerReports to the board

One processRoles marked AI or person

Limits firstCost set before work runs

Record on day oneReview against it

Name one senior owner for the rulesWith the CIO, the business head and risk at the table. The owner reports to the board. Not IT alone.
Pick one processMark each role as an AI agent, bought or built, or a person.
Write the job descriptionsGive every role a checker and an escalation path. Give every decision one named owner.
Set access per roleSystems, actions and data. Start narrow. Remove access the day a role or agent ends.
Set cost limits before work runsPer role and per task, charged to a business budget.
Start the record on day oneEvery task, decision, handoff and access change, with the reasons of AI and people.
Widen authority only when the record earns itNarrow it when the record shows mistakes. When a rule is broken: pause, escalate, and record why.
Review against the record on a fixed scheduleKeep your rules and record in a layer you own, independent of any one vendor.

Your 5-point check

Is AI really on your org chart?

Tick the ones your company has today. Then pick one process and ask: which step is missing, and what is stopping it?

Can you name who owns each decision an agent makes?An AI agent or a person, by name. Never "the system".Does every role, AI or person, have the same kind of job description?Responsibilities, decision rights, handoffs, escalation, limits and checks.Is the work always checked by someone other than the one who did it?Maker and checker are never the same, whether agent or person.Does an agent's authority widen only because its track record earned it?Not because a vendor pushed an update.Do you hold one record of every decision, with both reasons, on your side?In your own database, exportable, and not a vendor log.

0 / 5Where you stand

Tick each one you can answer yes to today.

Talk through your gaps Eight steps to close the gaps

Rent the capability. Own the judgement.

Not how much AI. Who decides, and who checks. Let's look at one of your processes together.

Book a demo Experience now