AI Training

Move from AI Curiosity to AI Capability: The Definitive Guide to Real Company AI Training

Transform your organisation into an AI-native culture through strategic AI workshops, collaborative AI hackathons, and a clear manifesto of values.

The Three Pillars of AI Transformation

To truly integrate AI, companies must move beyond just "using tools" to embedding AI into their DNA. We offer three structured pathways:

1. The AI Manifesto: Establish Your Convictions: Before you deploy, you must align. The Manifesto helps departments define how, when, what, and why to use AI. I focus on core values: Transparency, Accountability, and Validate & Verify.
2. The AI Workshop: Hands-On Exploration: A structured, interactive session including use-case inspiration, tool exploration (AI browsers, etc.), and "Mock Startup" exercises to solve real business problems.
3. The AI Hackathon: Building the Future: A half day to one-day intensive problem-solving session with cross-functional colleagues. Where teams come together to “hack” products or solve problems using AI tools.
It is the ultimate way to create a shared language, share prompts, and build collaborative workflows.

Why Training Matters Right Now!

AI is accelerating at an unprecedented rate. Organisations are in 3 camps,

(1) Team members playing with AI - no official AI workshop, struggling to get into any adoption of the right tools, workflow or optimisation.

(2) Had an internal AI workshop likely within their department and struggled to identify or problem solve existing issues, address any workflow issues and failed to implement much cross-functionally

(3) Some team members have optimised a sub-section of the team or discipline, some have started to use automations, others have started to prototype, but this isn’t a standard across the business and it causes issues when high performers are way ahead, and others struggle to keep up.

Those who wait aren’t just running a risk of falling behind, they have fallen behind.

My training ensures:

Quality Control: Implementing a "human-in-the-loop" strategy for high-stakes judgment, like workflows, strategy and hiring.
Brand Integrity: Front-and-centre brand guidelines to ensure AI outputs remain consistent with your identity.
Risk Mitigation: Identifying impacts and protecting the company through a centralised prompt library and approved tool lists.

Ready to kick off your AI journey?

Book a call today, email ai@dannydenhard.com or hit the button below.

Or ready to jumpstart your business with AI? Book our AI Workshop and Hackathon together today.

→ GET HELP TODAY

Why AI Is A Transformation Project Not Just Another Tool Roll Out

AI transformation is business transformation, not tool rollout: Most firms are stuck “playing with tools” (ChatGPT, Claude, etc.) without redesigning how work creates value, which is why experiments stay siloed, lack ownership, and don’t change outcomes. Read the full AI transformation guide or the summary below:
Step 1 – Map real workflows and hidden knowledge: Get cross‑functional teams to whiteboard how work actually happens, including “unknown knowns” (informal fixes, go‑to people, undocumented processes), then turn this into a shared company context document (request access to my private explainer document or listen to the dedicated podcast I recorded on it below).
Step 2 – Opportunity Map: Accelerate, Optimise, Cure, Kill: Audit tasks and processes into 4 buckets: accelerate what works but is slow (e.g. proposals, forecasts), optimise bottlenecks (e.g. lead handovers, onboarding, reporting), cure inconsistent quality (sales follow‑up, service replies, investor reporting), and kill work that shouldn’t exist or can be automated (manual CRM updates, data entry, redundant reports).
Step 3 – Training, hackathons, and risk before benefits: Run AI training, workshops, and hackathons at team/department/company level to build capability; in parallel, explicitly map risks (security, data quality, judgment, external comms, money‑spend) and governance (low/medium/high‑risk use cases and required human oversight) before you sell the revenue upside.
Step 4 – Cross‑functional SWAT team, data and governance: Create a small SWAT team with a clear leader and RACI/DACI‑style accountability across functions (sales, marketing, finance, IT, CS) to own AI transformation, centralise and structure data/context (docs, CRM, transcripts, support tickets), and ensure human judgment is applied hardest where AI has agency or touches customers and money.
Step 5 – Execute in 30/60/90/180‑day sprints: Use a now/next/future roadmap: first 30 days map workflows and pain points and pick a few use cases; 60–90 days run pilots and hackathons to get measurable quick wins; 90–180 days scale what works, integrate cross‑functionally, continuously share learning and co‑train teams—aiming ultimately at phase two: doing things AI makes newly possible, not just cheaper or faster.