AI HACKATHON
AI Hackathons & Why Not
From Individual Tools To A Collective AI Culture: The AI Hackathon
Move beyond solo tool experimentation and start building as an organisation.
Many businesses are currently stuck in a cycle of individual tool adoption, where employees experiment with AI in isolation. However, AI is not merely a technical initiative; it is a shared language for the entire business.
To transition from simple curiosity to a practical, AI-native culture, leadership must prioritise collaborative building.
The Natural Evolution: From Workshop to Hackathon
For organisations that have already conducted an AI workshop or are currently considering one, the AI hackathon is the essential next step to move forward.
Move Beyond Training: While training programmes are valuable, workshopping practical use cases gets people up the curve of practical use much faster.
From Lite Touch → Learning → Doing (Then Delivery): A workshop introduces the concepts, but the hackathon provides the environment to build something useful in a matter of hours.
A Statement of Intent: Transitioning to a hackathon sends a clear message to the business that AI is about active problem-solving and creation, not just theoretical discussion.
What is an AI Hackathon?
An AI hackathon is a structured event where a multidisciplinary team takes time out from their usual duties to solve problems and "hack" products together using AI tools.
It brings together the AI enthusiasts (called "AI-pilled" in AI World) and the sceptics to collaborate on tangible outputs.
Key Benefits for the C-Suite and Leadership:
Breaking Down Silos: This format brings Marketing, Sales, Operations, Finance, and IT into the same room to solve real-world problems together.
Conquering Resistance: Seeing a multidisciplinary team build a functional tool in a few hours conquers fear and resistance far more effectively than traditional training.
Shared Resources: Teams develop shared prompts, shared workflows, and a collective confidence that remains within the organisation long after the event.
Skin in the Game: Because the staff builds the solutions themselves, they are significantly more likely to use, refine, and advocate for those tools.
This also works as a prototype for Product and ENGG to deliver something that addresses issues and wouldn’t score high enough in effort vs reward sizing exercises.
The AI Hackathon Blueprint
The process focuses on rapid prototyping to ensure that AI initiatives do not get stalled in long-term roadmaps
Identify the Friction Points: Pick problems that have previously been identified as "medium effort/medium reward" - the ones that usually never get touched.
Map the Process: Step-by-step, map out a specific workflow (e.g., in finance or marketing) to identify exactly where AI can improve the process.
Build and Prototype: Using tools such as CustomGPTs or Gemini Gems, teams work to build a solution within a few hours.
Demo and Accelerate: Teams demo their prototypes, a winner is selected, and the solution is fast-tracked into the business roadmap.
"Prototyping is so quick now with AI. If you don't have something prototyped within an hour or 90 minutes, you need a check-in to get it back on track for delivery” from my upcoming AI Moment podcast - you can listen exclusively first here