Human + AI Leadership Lab

Preparing people to work with AI—and lead with the human capabilities technology cannot replace.

The Spirit Bloom Human + AI Leadership Lab is a technology-enabled workforce development initiative designed to help young adults build practical experience using artificial intelligence while strengthening the judgment, communication, collaboration, and responsible leadership skills needed in a rapidly changing workplace. The program is built around a simple premise: AI literacy should go beyond learning how to use an AI tool. Participants should have opportunities to see how professionals are applying AI in real industries, ask questions directly, practice using AI themselves, evaluate its limitations, and make decisions in situations where technology and human judgment must work together.

The initial pilot is being designed for approximately 100 participants ages 18–28, with an emphasis on expanding access for economically underserved young adults who may have limited access to emerging-technology education, professional networks, and career exposure.

How the Lab Works

The pilot combines a short foundational course with four AI Application Cycles. Each cycle introduces participants to a different area in which artificial intelligence is changing work and creating new questions, skills, and opportunities.

The learning sequence is intentionally consistent:

Learn → Meet → Discuss → Apply → Reflect

Rather than relying primarily on lectures, participants repeatedly move from learning a concept to seeing it demonstrated by a professional and then applying it to a realistic problem themselves.

Phase 1: Human + AI Foundations

Participants begin with approximately five hours of foundational training delivered across three learning sessions.

The foundation introduces practical AI fluency alongside Spirit Bloom's human-centered approach to leadership and decision-making.

Participants explore topics including:

practical uses and limitations of generative AI;
effective prompting and AI-assisted research;
evaluating AI-generated information for accuracy;
misinformation and hallucinations;
privacy and responsible use;
bias and the importance of human review;
professional communication;
judgment and decision-making;
collaboration and stakeholder awareness; and
responsible leadership in technology-enabled environments.

Participants are introduced to Spirit Bloom's Human Impact Leadership Framework, which encourages them to consider not only what technology can do, but how it should be used in situations involving people, organizations, and communities.

Throughout the Lab, participants return to four practical questions:

What can technology help us accomplish?
What information requires human verification or judgment?
Who could be affected by the decision?
How should the recommendation be communicated responsibly?

These questions become part of the applied work participants complete throughout the program.

Phase 2: AI Application Cycles

Following the foundation, participants complete four themed learning cycles examining how AI is being used across different areas of the economy.

Each cycle follows the same four-part structure.

A. Industry Masterclass

Participants attend a live virtual masterclass with a professional who has experience with technology or AI in the workplace.

Rather than giving a general motivational talk, the guest professional is asked to demonstrate how AI is affecting actual work in their field: what tools or applications are emerging, what problems organizations are attempting to solve, where human judgment remains essential, and what skills young professionals may need.

A sample first masterclass is: "AI Applications in the Green Economy”

A professional working at the intersection of technology, sustainability, business, energy, or related fields introduces participants to examples of how AI may be used to analyze information, improve operations, support sustainability goals, or address environmental challenges.

The session concludes with a live participant Q&A.

Future cycles may explore areas such as:

AI + Green Economy
AI + Media & Creative Industries
AI + Public Service & Social Impact

Themes may evolve as technology and workforce needs change.

Phase 3: The Digital Discussion Week

Learning does not end when the masterclass ends.

For approximately one week following each session, participants enter a moderated digital discussion environment where they can continue exploring the topic, raise questions, share relevant resources, and discuss the implications of what they learned.

Program facilitators guide the conversation and may bring selected questions back to participating professionals when appropriate.

This component is intended to address a common limitation of one-time professional events: participants often think of their best questions after the presentation is over.

The Lab therefore treats the masterclass as the beginning of a learning cycle rather than the end of one.

Phase 4: Real-World AI Application Case

Each masterclass is paired with an applied workplace challenge.

Participants are placed in a realistic scenario and asked to approach the problem as though they were an employee, team member, analyst, entrepreneur, or project contributor.

For example, following “AI Applications in the Green Economy,” participants might receive a fictional case involving an organization seeking to reduce energy use or improve the sustainability of its operations.

Participants could be asked to:

define the problem;
use AI to support research and idea generation;
evaluate the reliability of AI-generated information;
identify information that requires independent verification;
consider potential risks, limitations, or bias;
identify stakeholders who could be affected;
compare possible approaches;
develop a recommendation; and
communicate that recommendation in a concise professional format.

The objective is not to determine whether participants can produce the “perfect” answer.The objective is to observe whether they can use AI as a tool while continuing to think, question, verify, decide, and communicate as human professionals. By the end of four cycles, each participant will have encountered multiple workplace scenarios across different industries rather than learning AI within a single occupational context.

Phase 5: Participant Portfolio

Applied assignments are designed to leave participants with evidence of what they have learned.

Depending on the cycle, participant work may include:

an AI-assisted research brief;
a professional recommendation memo;
a stakeholder-impact analysis;
a presentation or recorded pitch;
an entrepreneurial concept;
a communication exercise; or
another practical workplace deliverable.

Participants therefore finish the program with more than attendance hours. They will have completed a small collection of work demonstrating how they approached real-world problems with AI and human judgment.

Industry and Professional Engagement

A central goal of the Lab is to reduce the distance between learning about the future of work and meeting people already participating in it. Spirit Bloom will recruit volunteer professionals from fields including technology, business, sustainability, media and creative industries, entrepreneurship, academia, and public service. Professionals may participate as masterclass speakers, Q&A guests, project reviewers, or contributors to educational resources. The model is intentionally based primarily on group engagement rather than one-to-one mentoring. One professional can expose a large group of participants to an industry, while selected educational content and cases can be adapted for future cohorts. This allows professional participation to have value beyond a single individual interaction.

Recognition and Community Participation

Participants who satisfy program requirements will receive a Spirit Bloom Human + AI Leadership Lab Certificate of Completion.

Completion criteria are expected to include participation in the foundational training, required masterclasses, and completion of applied assignments. Spirit Bloom also plans to invite businesses and community organizations to contribute small donated recognition benefits for participants reaching program milestones. Depending on participating partners, these could include modest food, educational, cultural, fitness, wellness, or community experiences. They are a way for local organizations to recognize participant effort and help make achievement visible within the broader community. This creates an additional layer to the model: while much of the educational experience can be delivered digitally across geographic boundaries, community partners can provide locally meaningful recognition and connection.

Measuring the Pilot

The first cohort is not intended simply to demonstrate that Spirit Bloom can hold four successful events.

It is designed as a pilot of a repeatable workforce-learning model.

Spirit Bloom plans to evaluate measures such as:

enrollment and completion;
foundation-course participation;
masterclass participation;
applied-case completion;
changes in participants' demonstrated understanding of responsible AI use;
ability to evaluate and verify AI-generated information;
quality of professional communication and recommendations;
participant confidence applying AI to unfamiliar workplace problems;
exposure to industries and career pathways;
participant feedback and engagement; and
program elements requiring modification before future cohorts.

Where feasible, Spirit Bloom will also conduct follow-up outreach to understand whether participants subsequently pursue additional training, employment, internships, entrepreneurship, or other career-development opportunities.

From Pilot to Replicable Model

The first 100-participant pilot will help Spirit Bloom determine what works before expanding the program. During the pilot, Spirit Bloom will develop and refine a standardized set of program resources, including:

5-hour Human + AI Foundations curriculum
4 industry application modules
4 applied workplace cases
facilitator materials
participant resources
masterclass guidelines
discussion prompts
assessment tools
completion criteria
participant feedback instruments

The goal is to create a model that does not require Spirit Bloom to reinvent the program for every cohort.

Over time, standardized digital materials and facilitator resources could allow the Lab to be delivered with nonprofit organizations, educational organizations, workforce programs, and other community partners serving different geographic areas.

Virtual professional participation further reduces geographic constraints: an industry professional in one location can engage participants from multiple communities without requiring travel or a permanent local instructor.

The long-term objective is therefore not simply to make the first cohort larger. It is to determine whether Spirit Bloom can create a high-quality, repeatable Human + AI learning model that additional communities can realistically adopt.

contact@spiritbloominc.com