FOR EXECUTIVE EDUCATION
Add one assessed Lab to a module you already teach. Participants delegate, verify, and decide with AI agents; faculty inspect the decision record.
TWO TRACKS, ONE PROGRAM
Keep the case discussions and management frameworks your program already teaches. Add practice in assigning work to AI agents and changing the team's rules when AI agents become contributors.
01 · PERSONAL TRACK
Participants write an assignment an AI agent can follow, supply the context and sources, and decide where to check progress. They also practice recognizing work they should keep themselves.
02 · TEAM TRACK
Participants assign roles to people and AI agents, plan handoffs and make room for disagreement. They set review points for quality, risk and cost, with a named person responsible for the final decision.
WHAT PROGRAMS ALREADY DO WELL
THE PRACTICE TO ADD
Participants practice both roles within the same module.
THE FIRST ENGAGEMENT
The task, source packet, budget and deadline stay the same. What changes is who contributes to the work and how participants handle those contributions.
Capital allocation case
A manufacturer must choose among three requests and explain which risks it is willing to accept.
Build a service-parts operation in Southeast Asia
Automate the second European plant
Acquire a customer-diagnostics software firm
People only
Participants read the business cases, board minutes and market brief. They allocate the €40 million and sign a one-page recommendation before the second round begins.
People
Participants revisit the same case. Compare how delegation, source checks, disagreement, and human decision ownership change across the two attempts, using the same faculty-approved rubric.
The Lab can stand on its own. Broader work begins only if the school decides it would add value.
WHAT THE LAB GIVES YOU
The Lab makes each participant's judgment visible inside a team exercise. It also shows you, in one bounded example, where your current assignments, assessment or AI-use rules may need to change.
FOR PARTICIPANTS
Participants specify work for AI agents, open the sources behind material claims and explain why their recommendation changed or stayed.
FOR FACULTY
Faculty can review who delegated what, which sources were checked, how disagreement was handled and who owned the final decision.
FOR THE PROGRAM
You see which parts of one management task changed when AI agents joined, and which parts still required human judgment.
HOW WE PREPARE IT
The work starts from one module you already teach. We prepare and test the operating layer; your faculty own the learning design and every academic decision.
8HATS LAB PROVIDES
FACULTY AND THE SCHOOL OWN
WHERE THE LAB CAN RUN
The case and learning logic stay consistent. The workspace and control model follow your program context.
SCHOOL PROGRAM
Runs in an approved participant or 8Hats Lab workspace. Your faculty control the sources, rubric, acceptable AI use and assessment; participant data stays inside the approved workspace.
CORPORATE ACADEMY
Runs inside the client's approved tools, workspace and data boundaries. Faculty, the sponsor and IT or security agree permissions and decision rights before launch.
WHY 8HATS LAB
The team combines assessment, learning systems, and AI in production in one Lab.
Dmitriy Istomin founded and led Examus, an AI assessment company acquired by Constructor Tech. Taras Pustovoy chaired the technology committee of the National Platform of Open Education, used by 2.7 million learners, and was a Coursera content partner.
Alexander Volkov, PhD leads our Human-AI Learning Architecture and research design. Mariam Mamedli, PhD turns research questions into AI agent systems that can be tested.
Dale P. Johnson, Senior Director of Digital Innovation at Arizona State University's University Design Institute and former director of ASU's adaptive learning initiatives, advises on institutional learning design and adoption.
AFTER THE LAB
If you choose to continue, we work with your faculty to apply what the Lab surfaced. Faculty keep academic control and ownership of the curriculum throughout.
Identify modules where AI agents change the management task.
Adapt assignments and learning activities around those changes.
Make delegation, verification and judgment assessable.
Prepare approved AI workspaces and course materials.
Agree rules for data, acceptable AI use and decision authority.
Plan follow-through where it supports the program.
Executive Education Brief
Tell us where to send it. We email a link to the PDF to the address you give, and keep that address only to send the brief and to answer you if you write back.
START WITH ONE DECISION
For the conversation, bring your module, cohort size, available teaching time, and tool or data restrictions. We will discuss whether the Lab fits.