AI Fluency
Chaining tools together
A one-day power module — or a three-day immersive upskill — that puts your department heads in front of your own data, with four AI tools open, learning by doing. Three core pillars. Five rules of thumb. Zero theory-only slides.
AI 360 starts from a simple position: AI is disrupting how operational work gets done, it is not displacing the people who understand the operation. Your department heads already hold the context. What they need is the fluency to put that context to work.
Every attendee gets accounts and access to the free tiers of ChatGPT, Claude, Gemini and Grok, then works a real department dataset — raw guest review feedback and issue reporting — through a repeatable loop: illuminate, amplify, solve. No scraping, no browsing, no made-up examples. Paste-in data, evidence out.
The capability model the whole day is built on — taught with worked examples, then practised on live department data.
Pillar 01
Chaining tools together
Knowing which model to reach for, and how to pass work between them so the output compounds instead of resetting.
Pillar 02
Judgment and critical thinking
You stay the decision-maker. The model drafts; you interrogate, verify and own what ships.
Pillar 03
Tool-agnostic market scanning
The leaderboard changes monthly. Build the habit of scanning, testing and switching without re-learning from zero.
The habits that keep AI useful, safe and honest once the room goes back to work.
You brief it, you review it. Delegation, not abdication.
It has never run your department. You have.
Verify the work before it leaves your desk.
You give the context that makes the answer useful.
Learn to read the smoke signals early.
Disruption, not displacement.
Housekeeping, engineering, F&B, security, front office, operations, culinary — anyone accountable for a metric.
GMs and ExCom who need their teams using AI on real data this quarter, not "someday".
Review data, audits, incident logs, guest feedback — insight that is already yours but unread.
Rolling out AI capability with evidence of application, not attendance certificates.
Each module hands the room a task, a dataset and a tool. Discussion happens after the doing, not instead of it.
Paste raw department review data into the tools and surface what's really driving the scores — strengths and weaknesses, quoted as evidence.
Build a plan to double down on the strengths the data confirms, with owners and success measures.
Work the issues into fixes you can start this week, pressure-tested against the 5 rules of thumb.
Ground rule throughout: no scraping, no browsing for data. Attendees work only with the data they are given and the context they bring.
The nine-step human–AI partnership loop the room works through, on their own data — AI on the left, you in the middle, the best work in between.
AI
Speed, scale and insight
Human
Context, judgment and accountability
Together
Stronger thinking, better outcomes
The loop
Human + AI, every cycle
Results feed straight back into step 1.
Analyse the dataAI
Read the department data and surface the patterns.
Validate the findingsHuman
Review, challenge and confirm what is actually true.
Explore the optionsTogether
Generate the possible courses of action.
Select the best actionHuman
Decide what matters most for the guest and the business.
Draft the action planAI
Turn the decision into a first-draft plan with owners and steps.
Refine and stress-testTogether
Review, tighten and pressure-test the plan.
Build the pitchAI
Create the management pitch with the right AI tool for the job.
Present and persuadeHuman
Take it to the table and secure buy-in.
Measure and learnTogether
Analyse the results, learn and improve the next cycle.
AI provides speed, scale and options.
You provide context, judgement and accountability.
Together better guest outcomes and business results.
09:00 – 17:00 · on site · up to 12 leaders
A short history of AI
How we got here, fast.
The AI landscape today
ChatGPT, Claude, Gemini, Grok — positioning and market approach.
Industry spotlight
How operators and leaders are using AI right now.
Break
20 minutes.
The 3 core pillars
Fluency, Agency, Adaptability — with worked examples.
The 5 rules of thumb
The habits that keep AI useful and safe.
Lunch
Action learning modules
Department heads work their own review data across four tools.
Share-back
Each department presents evidence, amplify plan and fix plan.
Wrap and 30-day commitments
Build your action plan in ChatGPT.
Product spotlight
What custom tooling makes possible next.
Three consecutive days of applied action learning
The one-day module builds capability. The three-day version goes deeper on each AI tool individually, uses client-specific relevant datasets, and links every exercise back to a real business issue — including how to stand up proprietary LLMs under proper corporate oversight, with custom tooling from Consensys AI.
Day 1
History, landscape, the 3 pillars and 5 rules — then straight into tool-by-tool drills so leaders feel where each model is strong and where it fails.
Day 2
ChatGPT, Claude, Gemini and Grok worked one at a time against client-specific, relevant datasets — reviews, issue reports, ops and financial extracts — each tied back to a real business problem you're carrying now.
Day 3
Standing up proprietary and private LLM setups with corporate oversight — data boundaries, approval, policy and risk — plus agents and workflows that hold after the training.
You keep
A department prompt library with guidance, real data-analysis snapshots from your own datasets, and custom tooling from Consensys AI tuned to your reporting cycle.
Content, datasets and tasks are customised to each client's departments and metrics before delivery.
Two facilitators, each with over 20 years in learning and development and more than 22,000 training delivery hours between the room and the boardroom.

Co-designer & facilitator · Redbike HRD
20+ years in L&D with over 22,000 delivery hours. Before that, a telecom executive in North America and Asia with General Electric, AT&T and XO Communications — through four mergers, one IPO and multiple start-ups.
That history is why his sessions land on change and disruption across multinational operations. Our leadership and management guru — bad management to be precise — having worked for five companies that declared bankruptcy.
Certifications
ATD Master Instructional Designer · ATD Creating Leadership Development Programs · ATD CHANGE and COACH Models · Biomimicry for Creative Innovation · David Novak Leadership · Facet5 & TeamScape · Kirkpatrick Four Levels · LEGO® Serious Play® · Marshall Goldsmith Stakeholder-Centered Coaching · Prosci ADKAR · TotalSDI
Outside the room
Accredited member of the International Federation of Journalists and National Writers Union; writes the Globalists column at Dispatches Europe and in The RedBikeHRD Peloton. Executive Bourbon Steward, investor in Havalina Wine and co-founder of the NBA2Lou movement. Born in Paraguay; raised in Puerto Rico, New Jersey, Louisville and Miami; has lived and worked in Hong Kong, Guangzhou, Tokyo, Singapore, New York and now Bangkok.

Co-designer & facilitator · Platinum Training
20+ years in L&D with over 22,000 delivery hours. Originally an international tax consultant with Deloitte, PricewaterhouseCoopers and KPMG before moving into L&D after arriving in Japan in 2002.
A key partner for Redbike HRD, he runs Platinum Training in Tokyo and is a Professor at the Kenichi Ohmae Graduate School of Business — leading many of our Japanese engagements.
Certifications
Advanced Training in Conflict Management (Kilmann Diagnostics) · David Novak Leadership · Global Leadership Coach · Hogan Assessments · Kirkpatrick Four Levels · Marshall Goldsmith Stakeholder-Centered Coaching · Points of You · Prosci ADKAR · Virtual Training (Center for Accelerated Learning)
Outside the room
An avid cyclist and co-Chair of The Knights in White Lycra, a Japan-based fundraising group that has raised over ¥130 million to give marginalised children living in care better prospects in adult life. Born in Newcastle; has worked, studied and lived in Sri Lanka, Leeds, South Carolina, London, Sydney and now Tokyo.
Tell us your departments and the data you already collect. We'll shape the afternoon around it and send back a run sheet.