AI Hackathons as Change Management: Beyond the Memo

Last week, I stepped off a plane in England with an unusual mission: run an AI hackathon with a team of educators for the Invictus Education Trust where students, faculty, and administrators would dive headfirst into the world of generative AI.  Fresh off the announcement from the Chinese government that every primary and secondary school will give students at least eight hours of AI lessons per year starting Sept. 1, 2025, the Trust CEO understood the urgency around increasing AI literacy for his community of schools.  

When introducing AI into organizations, there are real challenges to consider: cheating, AI hallucinations, and the impact of “effecient learning” on cognitive development. Still, it’s more important than ever to find a starting place where people can experiment, learn, and better understand how AI can help solve real problems today and ensure we all have the skills for today's job market.  

Three key insights emerged: 

1. Those of us immersed in AI, especially when consuming content on social media,  overestimate where people and organizations are in their AI literacy journey. 
2. AI is a general-purpose technology relevant to a broad set of disciplines and organizational functions, not just technical teams. 
3. Even a small, structured event can rapidly accelerate adoption and inspire organization-wide transformation.

This experience mirrors what's happening in companies worldwide. In this article, you'll discover:

• How forward-thinking CEOs are making AI adoption an explicit expectation. 
• Why "learning by doing" beats traditional training approaches for AI literacy.
• How hackathons create psychological safety for experimentation across departments.
• What we can learn from Microsoft's decade of hackathon experience.
• How companies are transforming hackathons from internal events into client engagement models.
• Resources to help you envision how an AI hackathon could work in your organization

CEOs Say It Out Loud

Many organizations are in the initial stages of creating AI policies, strategies, and transformation approaches, but a few leaders are being public about the “how”.  What can you learn from these leaders about your organization's journey?  

Shopify's Tobi Lutke dropped a memo that leaked online, explaining what many executives only hint at: "Using AI effectively is now a fundamental expectation of everyone at Shopify." No ambiguity there. His directive wasn't just aspirational. Every department must show AI implementation. Every prototype phase must leverage AI tools. The subtext? This is the way work gets done here.  

Key points from the memo:

• Every department must demonstrate AI implementation
• AI competency is now a core job requirement
• "You need to learn AI the same way you learned to use a computer."
• Both technical and non-technical roles must adapt
• Changing work habits is more complex than installing software
• Leaders must showcase their own AI adoption

Duolingo's CEO Luis von Ahn took a similar stance, declaring an "AI-first" future that echoes their 2012 bet on mobile—a gamble that ultimately defined their success. They're already replacing contractors with AI systems, moving from theory to practice.

The email stated five constructive constraints to help guide the shift:

• Contractor work that AI can automate will be phased out
• AI proficiency will be evaluated in both hiring and performance reviews
• New headcount will only be approved when teams cannot automate more work
• All functions must develop initiatives to change their workflows fundamentally
• Teams will receive AI training, mentorship, and tooling support to adapt

These aren't isolated cases. For every public mandate, hundreds of companies quietly rewrite job descriptions, shift budget priorities, and set internal deadlines for AI integration. The gap is in figuring out how to execute without derailing existing operations.

Learning by Doing in the GenAI Era

Organizations face a critical implementation gap.

The World Economic Forum reports that "the skills needed for work are expected to change by 70% by 2030." That's not gradual evolution. Six of ten business leaders see generative AI reshaping their entire organization, yet few have concrete plans for how people will develop these capabilities.

This insight was reinforced during my England hackathon. Finance directors, HR executives, and administration staff faced the same fundamental challenge: AI literacy cannot be achieved passively or individually. 

Hiring an "AI leader" to magically transform operations doesn’t work; the experts you're looking to hire are working through their first GenAI projects alongside everyone else. Many companies still believe they can send videos or purchase learning platform subscriptions. They can't. 

As Shopify's CEO bluntly put it, mastering AI "needs to be carefully learned by... using it a lot."

What we're discovering is that AI competency develops through experimentation in context. Learning happens organically when teams solve real departmental problems in real time. The marketing team doesn't need courses—they need to experience using AI to solve marketing challenges alongside colleagues.

There's no substitute for hands-on experience—that’s where AI hackathons come in.

AI Hackathons Deliver Where Training Programs Fail

Nobody loses when value creation becomes the centerpiece of engagement.

Recent research from learning platform Pluralsight provides compelling evidence for hackathons' effectiveness. Their study found that "hackathons decrease anxiety and increase belonging" among participants. Participating in a hackathon "can decrease participants' skill-related anxiety and significantly increase their sense of belonging in their workplace communities."

Hackathons are inherently playful. The format encourages experimentation without penalty, creating psychological safety essential for learning. When finance teams create AI art generators and HR builds interview preparation bots, technology adoption becomes enjoyable rather than threatening. This element of fun matters enormously for adoption across non-technical departments.

Hackathons cut through the noise of AI hype for companies seeking to boost AI literacy internally or providers looking to engage clients meaningfully. They replace theoretical discussions with tangible outcomes. Most importantly, they transform passive recipients into active creators.

AI Hackathons as a Change Management Solution

During my years driving Gig Economy adoption in Fortune 500 companies, I learned a core lesson about change management.

Despite compelling ROI projections, implementation stalled repeatedly. The breakthrough came when I recognized two distinct forces at work: our neurological resistance to change and legitimate concern around displacement. Our brains are hardwired to conserve energy by maintaining familiar routines.

Hackathons offer a uniquely effective solution to both challenges. Their time-boxed, focused structure creates psychological safety for experimentation. When the VP of Marketing struggles with the same prompt engineering challenges as the junior developer, hierarchies flatten. When finance teams collaborate with product teams, silos dissolve. Collaboration transforms AI into a collective opportunity.

Abstract promises become tangible when teams solve actual business problems in hours rather than quarters. I've watched skeptics transform into champions after witnessing their first successful implementation.

What We Can Learn from Microsoft

Microsoft has been running the world's largest private hackathon for years, refining a model that perfectly suits today's AI challenges.

The Microsoft Global Hackathon isn't a side project—it's a cornerstone of their innovation culture, pulling 70,000+ employees into an immersive creative sprint. I witnessed this firsthand at Microsoft.

What separates this model from typical corporate events is its radical inclusivity. Marketers collaborate with engineers. Finance teams pair with designers. Entry-level employees mentor executives on emerging tech. The collaborative atmosphere creates cross-pollination that formal training programs can't replicate.

A recent first-time participant captured the transformative effect: "I learned the importance of choosing the right project, understanding the context, having diverse skill sets on a team, and having a growth mindset to continue learning." These aren't technical skills—they're the adaptive capabilities essential for navigating constant change.

This highlights a fundamental truth about technology adoption: talking about AI won't build capability. PowerPoints don't create competence. Theories don't spark transformation. People need to get their hands dirty, make mistakes, stumble through problems, and discover solutions. 

In short, they must do the thing, not just contemplate it.

AI Hackathons: Practice to Revenue Stream

There are signs of a trend in the market as companies transform hackathons from internal innovation events into powerful client acquisition tools.

Take Clay AI's recent partnership with Vanta. In a single day, not weeks or months, they co-created three fully-functional AI solutions:

• Trust center mockups that auto-generate for each prospect's brand identity
• A Chrome extension that slashes research time for sales teams
• An AI system that transforms call transcripts into custom presentation decks

These weren't proofs-of-concept destined for the digital graveyard. They went live that same day. As Vanta put it: "The way we show up for a customer is so much more informed and targeted with this approach... This is a wildly different customer experience in such a great way."

"The way we show up for a customer is so much more informed and targeted with this approach... This is a wildly different customer experience in such a great way."

—Vanta Team

Clay flipped the traditional sales funnel on its head. Rather than pitch capabilities through slick decks and hypothetical use cases, they invite prospects to experience value creation in real-time. Their call-to-action isn't "download our whitepaper"—it's "let us come to your office and build something valuable together." 

The hackathon itself becomes both the marketing strategy and the product demonstration.

Resources for Your First AI Hackathon

If you're looking to organize your first AI hackathon, here are a few resources that offer a starting point:

1. HackerEarth's Comprehensive Guide

The HackerEarth Guide to Organizing Hackathons is a goldmine for first-time organizers. Built on experience from hundreds of successful events, it covers everything from planning and promotion to execution and post-event activities.

2. Gates Foundation's Agent Hackathon Framework

The Gates Foundation has developed a comprehensive GPT/Agentic AI Hackathon Playbook that provides a step-by-step approach. Their four-phase process covers everything from initial planning (4-6 weeks before) through execution and follow-up:

• Scope and Format: Define goals, identify participants, and establish the format
• Pre-work: Prepare use cases and knowledge sources
• Day-of Execution: From kickoff through working sessions to presentations
• Follow-up: Document outcomes and identify opportunities for further development

3. A Self-Paced Hackathon Toolkit

For those who prefer a self-guided approach, this Hackathon Toolkit (from the Government of South Australia’s Commission on Excellence and Innovation in Health) offers a comprehensive framework that breaks the process into manageable phases. Their six-step roadmap covers:

• Defining objectives
• Finalizing your challenge question
• Planning format and participants
• Promoting the event
• Providing resources
• Structuring delivery

The toolkit includes detailed attention to post-hackathon implementation, ensuring innovations don't die after the event.

What Comes Next

AI hackathons create a rare environment where technical experimentation, business value, and genuine enthusiasm converge. As CEOs from Shopify to Duolingo make AI adoption a fundamental expectation, organizations need approaches that deliver capability and confidence. Hackathons provide this balance.

Part 2 of this series will summarize the tactical blueprint for implementing your first AI hackathon. Whether building internal capability or exploring hackathons as a client engagement model, the principle remains the same: people learn AI by doing, not by talking about it.

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