In the era of rapid technological development, integrating artificial intelligence is no longer a choice—it is a necessity. That's why SoftServe launched a series of knowledge-sharing sessions within the company called Design Meets AI. In doing so, we got a unique chance to explore how the latest AI tools can transform designers' daily work.
As a logical follow-up, we organized a series of AI hackathons to promote these technologies among our designers. These events were aimed at demystifying AI for designers, providing them with the necessary tools and knowledge to innovate and optimize processes, as well as teaching them how to develop AI-integrated design solutions.
We've held a lot of webinars and panel discussions, but we really missed something practical and live. Hackathons have become a great format that allows designers to unleash their creativity and work without limitations
We wanted to organize the AI hackathon so that participants could try themselves in new roles and go beyond the usual design tasks. It helped to expand their horizons and improve their skills at different stages of the design process.
One of the main goals of the hackathon was to demonstrate that artificial intelligence is not only about popular ChatGPT or MidJourney, and certainly not a "substitute" for a designer. We wanted to show how a wide range of AI tools can make work much easier and more efficient.
Organizing the hackathon
Our team of three designers and a community manager took on the task of adapting a conventional design sprint to the needs of AI integration, encouraging teams to use both traditional and new approaches to find innovative solutions.
The process was only a suggested structure that allowed participants to experiment with it to get the most out of it. For example, one of the teams tweaked the framework, and it worked well.
Choosing theme
The hackathons' themes were chosen to inspire and relieve the participants of their everyday routines. The first one, held in December, had a Christmas theme that allowed participants to get creative. The second one, held in April, was dedicated to Eurovision, which allowed the team to showcase its internationality.
It was an opportunity for our colleagues from Mexico, Colombia, and the USA to learn about a part of European culture
The organizers also actively used AI to create tasks. For example, for the Christmas edition, we created a story in which Santa faces the difficulties of modern gift logistics. This gave participants a better understanding of the context and issues.
Library organization and toolkit
Before this hackathon, our community tested the most well-known tools that can help optimize a designer's work. More than 7 experts participated in this process, testing different tools for several months and giving their assessments. Based on their recommendations, we created a list of the best-of-the-best tools that we recommended to use during the hackathon.
Also, our previous AI events served as a foundation for designers during the hackathon. We added links to useful materials from our knowledge-sharing sessions to make the start smoother and provide participants with additional assistance.
We paid special attention to the ethical review of solutions developed with AI. To avoid possible negative consequences, we created guidelines for participants on the ethical use of AI, which later became a separate product for client workshops and assessments: ethicards.
Read more about trust issues with AI here.
Structuring teams and setting up processes
During the first kick-off call, we noticed a slight panic among all the participants. They saw the tasks and roughly estimated the amount of work and time they had to complete them. On the first day, panic was everywhere: participants tried to do everything on their own but quickly realized that it was almost impossible.
We deliberately formed teams of designers of different levels: junior, middle, and senior. This approach ensured equal opportunities for everyone. One of the teams shared their experience during the presentation:
At first, we tried to do everything ourselves, but we didn't have time. Then we had to delegate some of the work to AI, and then everything started working, and the process went on.
Delegating tasks to AI helped not only save time but also increase work efficiency.
What did the participants do? With the help of AI, of course
Of course, everyone is now interested to see the teams' results. Since there were a lot of artifacts, we divided them into several groups.
Finally, the teams presented their concepts to the jury and other participants. They demonstrated their concepts and explained in detail how AI helped create these solutions, what challenges they overcame, and what new opportunities were opened by using AI.
Hackathon results
The hackathon results exceeded expectations every time, demonstrating the incredible potential of AI tools and, above all, how effective these tools can be in the hands of professionals. We watched participants from different design fields come together to create innovative solutions using artificial intelligence in unexpected and creative ways. In the hands of talented and experienced designers, AI becomes not just a technical addition but a powerful assistant in realizing the boldest ideas.
Initially, we thought the hackathon would focus more on data analysis, but the participants impressed us by paying close attention to the visual component, creating a WOW effect.
It was especially nice to see that the participants used tools that were not on the list provided by the organizers. We even discovered something new and interesting for ourselves by observing their solutions and approaches.
At the end of each hackathon, we voted to select a winning team that received a small incentive bonus: a subscription to GPT chat or any other AI tool of their choice.
What were the challenges?
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Motivating the super-busy participants. Everyone had their own main work tasks. In addition, different time zones, workloads, and busy schedules made participation much more difficult.
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The week-long duration of the event also required additional efforts to engage the team.
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Information overload. Participants noted that the amount of new data was excessive, and it caused fatigue. Much of the time was spent learning how to work with new tools, such as writing prompts to generate texts or images. It takes time to gain quality experience, which became apparent during the hackathon.
Despite all the challenges, we managed to engage participants and create a positive experience. After the first hackathon, we received a lot of positive feedback, which was a powerful incentive to prepare for the next events. Now, we are actively working on organizing the third hackathon, taking into account all the previous lessons.
Impact of the hackathon
A month after the hackathon, we asked participants about their impressions and received feedback to understand the event's impact and learn what could be improved in the future.
- Application of AI at work
- New tools
- Main struggles
- Great expectations
Most participants started using AI tools daily or several times a week after the hackathon. This proves that they found practical ways to integrate AI into their work, which increased their efficiency
Participants tried 1 to 10 new tools during the hackathon. This shows that they are open to experimentation and ready to learn new technologies to improve their projects.
Writing the right prompts and the limitations of free versions of tools were the main challenges. However, participants overcame these difficulties and learned how to use AI effectively.
AI exceeded the participants' expectations in scenario generation, illustrations and animations, and speed and depth of data analysis. This shows that AI can significantly facilitate and speed up creative and analytical processes.
The hackathon participants noted that AI greatly facilitates operational tasks, saves time, and provides starting points for generating ideas. These tools have become a valuable addition to designers' work, proving to be effective in creative processes. In addition, AI has helped to improve teamwork by facilitating the execution of everyday tasks and creating conditions for more effective collaboration.
The hackathon experience was important not only for the company but also for each participant. They gained new knowledge, skills, and confidence in using AI. After two successful events, an extensive database of materials was created that will become the foundation for the next hackathons. Participants now have access to ready-made solutions from which they can draw inspiration. The success of these hackathons has also spurred the creation of a community of AI enthusiasts, promoting AI culture among designers within and outside the company.
