Analysis1 of 2
Everyone measures what you do with the AI on. We measure what is left when it is switched off.
The three questions no certificate of attendance answers.
AI-Ready · Executivo AI-Ready
The decisions of your function — about AI and with AI — practiced in the exercise of your role.
Courses teach you to use AI. Here you practice the decisions your role demands — and stand behind the number under challenge. With AI itself as the table, the pushback and the lever.
Learning and practicing about AI — with AI itself
Using AI is a skill. Deciding about AI — and with AI — is a craft: framing the thesis, approving the capital, supervising the risk, defending the number. Eleven months a year, what your role demands is the second.
The center of the program is learning: thirteen decision competencies, practiced in simulations with agent-characters, in Teste Ácido and in Preparar Apresentação. The features come afterward — as differentiators, not as the pitch.
Every course teaches the AI business case. None trains you to defend your function's budget — with AI as a lever — under challenge.
What you will learn
Thirteen competencies. Each one opens with a sentence of what you will be able to do.
01How AI works, where it fails and what that costs in executive decisions
Understand predictive, generative and agentic systems at the decision-maker's level: what each does well, how it fails predictably, what drives cost in production — and when the problem does not call for AI.
02Value thesis: choosing where AI goes first and where it does not go
Turn the pressure to “do AI” into a prioritized, defensible portfolio: start from a named business problem, separate efficiency gains from changes to the model and refuse, in writing, the initiative without demonstrable value.
03AI in the executive's own craft: preparation, analysis and decision without outsourcing judgment
Extract real leverage from AI in the work of leading — meeting preparation, critical reading of decision materials, scenarios, institutional communication — protecting what is confidential, verifying the output and keeping your own judgment in the face of a well-written recommendation.
04The AI bill: cost, measured gain and the decision to scale, keep or shut down
Size what the solution consumes (per-seat license or cost per consumption, plus the operation that only shows up in production), record the baseline before changing anything, measure the realized gain — and decide to scale, keep or shut down with numbers, not perception.
05Data as a precondition: what the company needs to have before promising AI
Judge the condition of the data that sustains or sinks the initiative — origin, quality, ownership, access and fragmentation across systems — and the real cost and time to fix it before committing to a result.
06From pilot to operation: redesigning the process instead of bolting on the tool
Take the initiative from pilot to daily operation by redesigning the work step — flow, roles, review point, acceptance criteria and failure plan — instead of layering the tool onto an untouched process.
07Internal AI governance: policy, authority levels and who approves what
Establish and enforce the internal rule on AI use — what is allowed, what requires prior approval, who reviews before the decision goes out and what gets recorded — calibrated to the organization's stage and risk.
08Personal data on the executive's desk: legal basis, vendors and automated decisions
Decide on the processing of personal data in AI initiatives — purpose, legal basis, minimization, transfer to vendors, the right to review an automated decision — knowing what is within your own authority and what requires an opinion from the data protection officer or legal counsel.
09Security and AI-assisted fraud: the company's exposure and incident readiness
Recognize the vectors AI opens against the company — synthetic voice and video in payment authorization, social engineering, unapproved tools holding internal data, agents with more permissions than needed — and establish verification and incident response that do not depend on recognizing the face or voice of whoever is asking.
10Regulation applicable to the business: what already applies, what is coming and what to do now
Recognize the living regulatory map of your own sector — data protection in force, the Brazilian bill in progress, the European regime with extraterritorial effect, sector rules, risk management frameworks — and turn it into a classification of the use cases under your own authority and into proportional safeguards.
11People and work with AI: role redesign, training and what you tell the team
Steer the effect of AI on people's work: which tasks change in each role, which training to fund, measured actual use rather than licenses purchased — and what to tell the team about routine, performance reviews and jobs, with identifiable human review whenever AI enters a decision about people.
12Accounting for AI: board, customers, market and regulators
Account for AI — what was invested, what is already paying back, what risk exists and what safeguards are in place — with numbers traceable to whoever produced them and without claiming capabilities the company does not have in production.
13Reading what lies ahead and turning it into today's decision
Separate what is already commercially available from what has merely been announced and from what is market expectation — and turn that reading into a dated decision: commit budget now, test at small scale or postpone, with an observable trigger that brings the topic back to the agenda.
The thirteen competencies are practiced in simulations, in Teste Ácido and in Preparar Apresentação. Optional layer: application modules by function (CEO, CFO, CMO, CHRO, CIO/CTO/CDO, COO, CLO/GC, CSO). Content is revised within weeks when regulation or the market changes.
The table before the table
Realistic simulations, designed by someone who did this in person, live, for 23 years. In the room, independent AI agent-characters — each with its own role, information and objectives. You decide under time pressure and pushback, with no audience and no political cost.
The CEO. Wants the decision today. Has a preference and does not state it.
The CFO. Asks for the total cost and the sensitivity — and knows when the number has been rounded.
The vendor. Brings market urgency. Some of it is real.
Legal counsel. Reminds you of what the rules require — and what they do not yet say.
You. Decide. No audience, no political cost, with the pushback the real meeting would have.
Preparation
You receive the case material and the triggers — what the table knows, what each character wants, what is at stake. You prepare as you would for the real meeting: with AI, if you wish.
Live meeting
By voice, in real time, with the agent-characters. They disagree, push, withhold, ask for the number. You lead the table to a decision.
Artifact and debriefing
A recommendation, a vote, a plan — the artifact the meeting required. Then the private debriefing: what you did, what it practiced and what remains as a hypothesis.
Confidential data never comes in: the case is built for the simulation. Confidentiality is not a policy — it is architecture.
Differentiators — after the learning
Teste Ácido
Your proposal or position cross-examined before the real meeting — by an AI designed to challenge, not to agree.
Preparar Apresentação
The information you still need to ask for and the likely Q&A from the Executive Committee or the board, assembled before the meeting.
Confidentiality by design
Perimeter protocol, no automatic integrations, isolation per participant, vendor independence.
Content revised in weeks
The topic map comes in by ingestion, with no retraining. When regulation or the market changes, the program changes the same month.
What you receive at the end of a cycle
The debriefing is private and descriptive. It speaks to what you did when facing the cases — not to who you are.
- An overview of your process: how you used the preparation, which prompts you addressed, how you engaged the characters, how you contributed in the meeting and how you led it to a decision.
- Three to five strengths tied to what each simulation practiced.
- Three to five reflections, presented as hypotheses for real situations — never as prescriptions.
No result is shared with third parties. In cohorts contracted by companies, feedback to the contracting company follows what the contract defines, always at cohort level.
What we don't do
- We do not predict performance.
- We do not pass judgment on the person.
- We do not replace the board's or the executive's decision.
- We do not take in confidential data.
- There is no hidden human layer in the flow: what is AI is declared as AI.
Live board — Executive
Sourced data on AI and executive decision-making in Brazil.
Sourced data1 of 3
61%
of Brazilian companies say AI has had little or no impact on their business.
ⓘ Source
Amcham Brasil / Humanizadas, Panorama 2026 — 629 executives
How to enroll
Individual cycle
For those who decide on their own. Online enrollment, by credit card.
- 3-month cycles
- Access to the platform, the cycle's simulations, Teste Ácido and Preparar Apresentação
- Private debriefing at the end of the cycle
- Renewal in new cycles of 3, 6 or 12 months
- Prices and conditions on the enrollment page
Private cohort
For companies and boards. Ten participants per cohort; direct contract and invoicing — not through the site.
- Cohort of 10 participants per 3-month cycle
- Cases adapted to the sector, with no confidential company data
- Feedback to the contracting company at cohort level, as per contract
- Payment by invoice or boleto (bank slip)
Frequently asked questions
?Do I need to know how to code or understand models?
No. The program is about decisions — formulating, approving, overseeing, defending — and the technical level is that of the decision-maker, not the developer.
?How much time per week?
About two to three hours, between preparation, simulation and the preparation tools. Live meetings last 45 to 60 minutes.
?What is the demonstration?
An individual session in which you experience a segment of a simulation and receive feedback. You request it on the site; scheduling is done by email.
?Can I use my company's content in the simulations?
No — by design. The cases are built for the simulation and no confidential data enters the platform. In private cohorts, the cases are adapted to the sector, not to the company.
Get to know the program before you decide.
Request a demonstration: one individual session, with feedback and no commitment.