Advisory and training
AI adoption is an operating change.
LevelUp helps teams, institutions, and regions move from AI curiosity to practical capability: workflow redesign, leadership confidence, governance that holds, and implementation someone is accountable for.
Advisory
Three ways an engagement starts.
Each one produces something the organization can act on — a map, a prototype, or a trained internal owner.
AI readiness sprint
Map the organization before prescribing tools.
Assess use cases, workflows, data constraints, governance needs, team readiness, and the adoption barriers already in the building.
Workflow automation sprint
Prototype better work routines.
Identify high-value workflows, design AI-assisted process changes, and build prototypes employees can actually test.
AI transformation leader
Train the internal champions.
Build leadership capability around use-case selection, governance, measurement, workforce impact, and implementation.
Flagship training menu
AI leadership training for teams, managers, and institutions.
These programs build from practical AI use into leadership confidence, responsible adoption, and capability that transfers to internal staff.
1 day
AI at Work: From Curiosity to Capability
People try AI once or twice, but do not turn it into reliable workflows that improve real work quality or speed.
1 day
Generative AI Fundamentals
Teams are experimenting with AI tools without shared language, safety norms, or repeatable workflow habits.
1 day
Practical Prompt Engineering
Most AI use fails because requests are vague, context is missing, and outputs are not evaluated systematically.
1 day
Building and Evolving Custom GPTs
Custom assistants often fail because they lack a clear job, useful context, guardrails, testing, and improvement routines.
1 day
Become Your Team's AI Champion
AI adoption stalls when everyone waits for central experts or when early adopters cannot coach peers safely and consistently.
1 week
AI Leadership Implementation Intensive
Leaders need enough depth to guide teams through adoption, redesign work, govern responsibly, and measure value.
1 month
AI Mini MBA
Leaders need to connect AI to strategy, customers, operating models, team performance, and measurable business change.
1 day
Responsible AI, Governance, and Risk
AI adoption can create reputational, legal, operational, and equity risks when teams lack practical guardrails.
These are drawn from the same catalog partners can license and run themselves. See all courses. For the full executive session stack, see the AI Mini MBA.
AI Mini MBA reach
Corporate sessions and strategy support across countries and industries.
Mitch provides AI Mini MBA teaching, insight, and strategy for managers and leaders across Spain, the United States, Portugal, Australia, Germany, Peru, Canada, and New Zealand.
Organizations
Spark NZ, Anheuser-Busch, Sherwin-Williams, Adobe, and enercity
Enterprise audiences use the sessions to connect AI adoption with leadership decisions, productivity, governance, and credible implementation.
Operating companies
Billie-Ann Plastics Packaging Corp and CanLift Equipment Ltd.
Managers explore practical AI use cases tied to operations, customer communication, internal knowledge, workflow support, and day-to-day team performance.
Market and ecosystem audiences
AI Forum New Zealand, Daylight Studio, and Harcourts Auctions
The sessions also support sector-facing conversations about strategy, service innovation, market change, and what responsible adoption looks like in practice.
Advisory method
From curiosity to operational capability.
The sequence is deliberately unglamorous. Most stalled AI programs skipped the second step.
Step 01
Identify the work that matters
Clarify the processes, decisions, and pain points where AI could create operating value.
Step 02
Prioritize what is feasible and valuable
Rank opportunities by value, risk, data readiness, team capacity, and implementation complexity.
Step 03
Build prototypes and adoption routines
Develop assistants, workflow maps, operating guides, training materials, and lightweight evaluation methods.
Step 04
Scale lessons into capability systems
Train champions, update governance, track usage and value, and connect the learning to workforce strategy.
The LevelUp difference
AI transformation is a workforce and economic-development issue.
Adoption inside a single company changes that company; adoption across an ecosystem changes what the region can do. That wider framing is why the same work serves employers, universities, governments, funders, and ecosystem builders — the ones who need AI capability to show up in people and institutions.
Related
Where this sits in the rest of the work.
Capability area
Build talent systems
Adoption inside an organization and capability across a workforce are the same problem at two scales.
Insight
The LevelUp model
Why capability, employers, capital, and institutions have to be designed together.
Curriculum
License the training
Institutions and delivery partners can license these programs and run them under their own banner.
Next step
Start with a readiness sprint.
Tell us what your teams are already trying with AI and where it is stalling, and we will scope the shortest useful engagement.