TL;DR: Zapier's AI Hackathon Boosted Company-Wide Innovation
Zapier held a week-long AI hackathon to drive enterprise-wide adoption of artificial intelligence after releasing GPT-4, halting regular operations to focus on tangible AI projects.
• Employee usage of AI tools rose from 10% to 50% in one week.
• Teams across finance, marketing, and support built practical AI solutions.
• Company culture shifted, embracing AI as a skill amplifier rather than a threat to jobs.
Curious how your startup can achieve similar results? Check out Zapier's insights on AI adoption for actionable strategies.
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When Zapier ran a week-long hackathon focused entirely on embedding artificial intelligence (AI) into its culture and workflows, it didn’t just experiment with a trending technology, it fundamentally rewired how its organization operated. For a company anchored in automation, the stakes were clear: adopt AI meaningfully or risk falling behind competitors who would. As someone who has built ventures in education and AI-powered tools, I can tell you: Zapier’s approach holds lessons for all founders and leadership teams exploring AI adoption today.
Why a “Code Red” Made It Urgent
Zapier’s hackathon came on the heels of OpenAI’s GPT-4 release in mid-2023. While the earlier GPT-3.5 model had intrigued businesses, the leap in capabilities with GPT-4 forced many to realize this wasn’t just about chatbots; this was about structural shifts in how work could be done across every function. According to Zapier CEO Wade Foster, the company was initially stuck at less than 10% of employees actively using AI in their work. For a team specialized in automation, this represented not just a missed opportunity but a competitive liability. That’s when Foster declared a “code red”, a term the company had never used before, to initiate a full organizational pivot around AI.
Here’s the kicker: Zapier stopped its entire operation for a week. All employees, from engineers to marketers and finance staff, were tasked with building something using AI. Thinking about your own organization, ask yourself: when was the last time your team got hands-on with any emerging tech, not just reading about it, but truly experimenting with what’s possible?
Hackathons: Just for Developers? Not Anymore
Many companies hear “hackathon” and assume it’s meant for coders building prototypes from scratch. Zapier proved otherwise. This was an all-hands exercise in creativity: marketers applied AI to campaign testing, customer support tested automation for ticket resolution, and finance started experimenting with AI-backed forecasting models. Most importantly, results were shared during a demo day at the end of the week, creating what Foster called “contagious momentum.” When employees saw their peers using AI to save hours and create new efficiencies, adoption spread naturally.
Based on my own experience running hackathons and edtech simulations through Fe/male Switch, where “gamepreneurship” is the foundation, one lesson stands out: hands-on experience builds confidence and breaks fear of failure. Theory never matches the transformative power of building something tangible, even if it’s small. For founders hesitant to roll out such programs, ask yourself what’s stopping you, then automate it. Usually, it’s logistics or perceived complexity, both of which you can simplify with no-code tools or AI systems.
How Did This Change Zapier’s AI Adoption?
- From 10% to 50% usage, immediately: In just five days, weekly AI users at Zapier skyrocketed. Notably, this was across all departments, not just engineering.
- Improved AI fluency company-wide: Employees learned the limits and strengths of AI, which is critical when deploying these tools responsibly.
- Spreading the “why” of AI adoption: Seeing real use cases during the demo day erased skepticism. Peers discovered practical, viable applications of AI within their roles.
- Catalyzed culture change: Once employees realized AI wasn’t replacing them but amplifying their capabilities, a bottom-up embrace replaced hesitance.
When I implemented my own hackathon-driven approach to training founders within CADChain, I saw similar shifts. Skepticism melts away the moment stakeholders, even those with no technical background, see highly tailored, deeply practical solutions for their day-to-day challenges. From automated IP claims in CAD files using blockchain to game-like training templates in Fe/male Switch, the parallels with Zapier’s success are everywhere: learning by doing works.
What Founders Can Learn From Zapier
Zapier’s hackathon is not just a feel-good success story but a blueprint for founders who want to integrate AI into their businesses. Here’s how you can replicate (and scale) it at your company:
- Don’t wait for perfection: Wade Foster admitted that some of the projects built during the hackathon were “messy.” But messy experiments spark learning. Waiting for polished plans delays growth.
- Make it inclusive: AI adoption isn’t just an engineering effort. Involve marketing, sales, support, finance, everyone can benefit from automation.
- Run repeat sessions: One hackathon is powerful, but organizational habits form through repetition. Zapier now runs these every six months. This keeps adaptive thinking alive.
- Focus on small wins first: Have teams identify manual tasks or bottlenecks they face, and start there. For instance, automating responses to high-frequency customer tickets can deliver immediate results.
- Leverage tools people already use: At Zapier, integrating AI into existing workflows (e.g., Google Docs, Slack) made adoption seamless. For founders, this means embedding AI into your team’s daily tools rather than introducing entirely new systems all at once.
Common Missteps You Must Avoid
While Zapier’s example is inspiring, there are pitfalls companies often face when adopting new technologies. Based on my own missteps, here’s what to watch for:
- Failing to demystify AI: Buzzwords and vague promises of AI “transforming” work scare people. Simplify the language and show concrete, relatable use cases.
- Making it optional: If exploration feels secondary to their primary responsibilities, employees won’t buy in. This is why Zapier paused operations temporarily, it signaled priority.
- Leaving results unshared: A compelling demo day creates excitement and accountability. Results breed enthusiasm.
- Underestimating fear of replacement: Zapier framed AI as “augmentation,” not substitution. Founders need to communicate this distinction consistently.
- One-time effort: A single AI workshop doesn’t produce culture change. Commit to iterative learning and experimentation over time.
The Takeaway for Entrepreneurs
At its core, Zapier’s week-long hackathon wasn’t about technology, it was about cultural transformation. By demystifying AI, encouraging experimentation, and enabling employees to experience results first-hand, they planted the seeds of a company-wide mindset shift. Imagine what your startup could accomplish with the same energy.
For founders, here’s the real test: could you stop operations for one week, dedicate yourself to solving challenges through experimentation, and come out with new tools that reshape how you work? If yes, you’re closer to unlocking AI’s true potential. And if not, maybe it’s time, pull your own “code red,” organize a hackathon, and find out what your team is truly capable of.
To see how an AI-first mindset could work for your business, track Zapier’s ongoing transformation via their company blog or explore startup-building experiments inside real-time platforms like Fe/male Switch. Let inspiration meet action, today.
FAQ on Zapier's AI Culture Transformation via Hackathons
How did Zapier's hackathon accelerate AI adoption across the company?
Zapier's week-long hackathon encouraged hands-on experimentation, increasing weekly AI usage from 10% to 50% company-wide. Employees built AI tools for practical applications, fostering enthusiasm and collaboration. Explore AI Automations For Startups.
Why did Zapier implement a "code red" approach to AI adoption?
The "code red" signaled urgency after GPT-4's release, reshaping workflows with AI. It united the company around a single goal of meaningful exploration. Discover hidden benefits of hackathons.
What practical tools emerged during Zapier's AI hackathon?
Employees built tools like AI-backed forecasting models for finance and improved campaign automation in marketing. Simple yet impactful innovations became drivers of cultural change. Learn about AI-powered automation workflows.
Can hackathons benefit non-technical departments?
Absolutely. Zapier’s hackathon showed marketers, support staff, and finance teams how to integrate AI into everyday workflows, amplifying their productivity. Find out how WP Engine boosted innovation.
How do recurring hackathons sustain AI culture over time?
Repetition fosters habit formation and cultural adaptability. Zapier holds hackathons every six months, ensuring ongoing innovation and AI fluency across teams. Read actionable insights on task-based pricing.
How does leadership influence successful AI adoption?
Zapier’s leaders participated directly in hackathon efforts, blending hands-on guidance with transparent communication to drive organizational buy-in. Dive into leadership examples during AI transitions.
How can AI improve everyday employee workflows sustainably?
Tasks like automating frequent customer queries or generating predictive insights using AI workflows save time and improve focus on strategic tasks. Discover tools for humanizing AI-driven workflows.
What lessons can startups learn from Zapier's hackathon success?
Start small, automate bottlenecks first and use existing tools. Inclusive participation and hands-on experience foster confidence and wider adoption. Learn AI-based tips for startup scalability.
Why is sharing hackathon results critical for culture change?
Demo days spark contagious momentum, showing employees tangible outcomes of AI experimentation and promoting peer-driven learning. Explore cultural impacts of AI events.
How can startups apply Zapier’s hackathon principles effectively?
Run hands-on sessions focused on specific use cases, involve all departments, and prioritize regular iterations over one-off efforts. Enhance AI implementation strategies.
About the Author
Violetta Bonenkamp, also known as MeanCEO, is an experienced startup founder with an impressive educational background including an MBA and four other higher education degrees. She has over 20 years of work experience across multiple countries, including 5 years as a solopreneur and serial entrepreneur. Throughout her startup experience she has applied for multiple startup grants at the EU level, in the Netherlands and Malta, and her startups received quite a few of those. She’s been living, studying and working in many countries around the globe and her extensive multicultural experience has influenced her immensely.
Violetta is a true multiple specialist who has built expertise in Linguistics, Education, Business Management, Blockchain, Entrepreneurship, Intellectual Property, Game Design, AI, SEO, Digital Marketing, cyber security and zero code automations. Her extensive educational journey includes a Master of Arts in Linguistics and Education, an Advanced Master in Linguistics from Belgium (2006-2007), an MBA from Blekinge Institute of Technology in Sweden (2006-2008), and an Erasmus Mundus joint program European Master of Higher Education from universities in Norway, Finland, and Portugal (2009).
She is the founder of Fe/male Switch, a startup game that encourages women to enter STEM fields, and also leads CADChain, and multiple other projects like the Directory of 1,000 Startup Cities with a proprietary MeanCEO Index that ranks cities for female entrepreneurs. Violetta created the “gamepreneurship” methodology, which forms the scientific basis of her startup game. She also builds a lot of SEO tools for startups. Her achievements include being named one of the top 100 women in Europe by EU Startups in 2022 and being nominated for Impact Person of the year at the Dutch Blockchain Week. She is an author with Sifted and a speaker at different Universities. Recently she published a book on Startup Idea Validation the right way: from zero to first customers and beyond, launched a Directory of 1,500+ websites for startups to list themselves in order to gain traction and build backlinks and is building MELA AI to help local restaurants in Malta get more visibility online.
For the past several years Violetta has been living between the Netherlands and Malta, while also regularly traveling to different destinations around the globe, usually due to her entrepreneurial activities. This has led her to start writing about different locations and amenities from the point of view of an entrepreneur. Here’s her recent article about the best hotels in Italy to work from.
