Explorative AI projects 2025

<p data-start="256" data-end="461">In the videos on this page, you can learn more about the project: why it was launched, how the recruitment and implementation were carried out, and what lessons the organization was able to draw from it.</p>
<p data-start="463" data-end="615" data-is-last-node="" data-is-only-node=""><em><strong>All videos are in Swedish with English subtitles. The translations, subtitles, and video descriptions have been produced using AI tools.</strong></em></p>

<p>The video showcases Chalmers's summer AI projects, emphasizing their unique focus on cultural aspects and the rapid evolution of AI. It highlights the importance of involving a broad range of staff in order to keep pace with technological change. The video describes pilot projects and their successful outcomes, which has led to an expansion to 26 projects planned for 2025. Learning, experimentation, and the engagement of central administration are presented as key strategies for success. </p>
<h4>Key takeaways:</h4>
<ul>
<li>Chalmers is integrating culture into AI project work.</li>
<li>Broad staff participation accelerates adaptation to AI.</li>
<li>Pilot projects inform future initiatives and expansion.</li>
<li>Active learning and experimentation drive innovation.</li>
</ul>

<p>The video outlines Chalmers’ approach to launching exploratory AI projects, describing a structured process that began with workshops involving key operational staff and the use of AI categorization tools for brainstorming. Over 600 ideas were gathered and carefully refined into 24 actionable prompts for student interns, ensuring strong organizational alignment and active stakeholder engagement throughout the process. The viewer learns how systematic ideation, prioritization, and collaborative involvement can foster effective AI project development.</p>
<h4>Key takeaways:</h4>
<ul>
<li>Start with broad idea generation involving diverse stakeholders.</li>
<li>Use AI tools to categorize and prioritize ideas efficiently.</li>
<li>Distill many ideas into a manageable set of focused prompts.</li>
<li>Ensure projects align with organizational needs for lasting impact.</li>
</ul>

<p>The video explains how Chalmers used AI to streamline the recruitment of 24 master's students for summer AI projects. By replacing traditional personal letters with over 50 detailed questions, they gathered richer applicant data and used language models like OpenAI GPT-4.1 and Anthropic Claude Haiku for initial candidate assessment. The approach aimed to build interdisciplinary and diverse teams, with human validation ensuring fairness and accuracy in the final selection process.</p>
<h4>Key takeaways:</h4>
<ul>
<li>AI can efficiently process detailed applicant inputs.</li>
<li>Replacing personal letters with targeted questions yields more relevant data.</li>
<li>Comparing AI models helps optimize recruitment workflows.</li>
<li>Human oversight remains crucial for fairness in candidate selection.</li>
</ul>

<p>The video outlines how 24 master's students at Chalmers participated in collaborative AI summer projects, working in six teams as interns. Their onboarding process combined practical information, meetings with stakeholders, and a kickoff to set expectations. The program featured regular team check-ins, blog updates, and guest speaker sessions, with participants working mostly on-site. Managers and technical staff offered continuous support and provided operational insights, helping students bridge academic knowledge with practical, real-world AI development.</p>
<h4>Key takeaways:</h4>
<ul>
<li>Structured onboarding and team-based work supported learning.</li>
<li>Weekly reflections and expert talks enriched the experience.</li>
<li>Continuous support from staff facilitated practical skills development.</li>
<li>Real-world projects promoted collaboration and innovation.</li>
</ul>

<p>The video presents Chalmers' approach to managing AI project tools, comparing commercial cloud platforms like ChatGPT, Claude, Copilot, and Sana with local open-source alternatives such as Ollama, LiteLLM, KB-Whisper, and Open Web UI. It covers categories like large language models, coding aids (Claude Code, Lovable, Replit), and services for supporting prototypes. The team used a dedicated admin email to manage subscriptions, control costs, and ensure flexible access, especially during staff absences. Source code was centrally managed on GitHub, ensuring proper credit and collaboration.</p>
<h4>Key takeaways:</h4>
<ul>
<li>Cloud and local AI tools serve different project needs.</li>
<li>Using a shared admin account streamlines service management.</li>
<li>Careful subscription control helps manage costs and tool access.</li>
<li>Organizing code and credit on GitHub supports teamwork.</li>
</ul>

<p>Over summer 2025, Chalmers launched exploratory AI projects that produced over 50 prototypes. These were assessed on impact, feasibility, cost, and scope, then grouped into categories such as AI in education, personal productivity, Smart Campus, and research tools. The initiative plans to rehire student interns part-time to advance promising prototypes, promoting collaboration and centralized coordination. Emphasizing iterative work, stakeholder engagement, resource sharing, and leveraging student expertise, the approach aims to efficiently develop impactful AI solutions for the university.</p>
<h4>Key takeaways:</h4>
<ul>
<li>Iterative development and stakeholder involvement are crucial.</li>
<li>Prototypes span education, productivity, campus, and research.</li>
<li>Student expertise and pooled resources drive progress</li>
<li>Central coordination supports ongoing collaboration.</li>
</ul>

<p>The 2025 Explorative AI project at Chalmers launched 26 AI initiatives through student-led teams and collaborative idea workshops. Emphasizing iterative, exploratory development and organization-wide learning, the project surfaced key challenges in time management, support, communication, and budgeting. Timely feedback via blog posts and robust communication strategies strengthened engagement, while a small, proactive core team with diverse skills played a crucial role. Better preparation before interns arrived, particularly around technology setup and funding, was identified as an area for improvement. Clear stakeholder anchoring and internal networks supported successful outcomes.</p>
<h4>Key takeaways:</h4>
<ul>
<li>Iterative, feedback-driven development is vital for AI projects.</li>
<li>Effective communication and stakeholder anchoring boost success.</li>
<li>Diverse, proactive core teams are essential.</li>
<li>Improved upfront preparation and clear resource allocation are needed.</li>
</ul>

<h2>Project teams</h2>
<p>Each project team has their own webpage where their ideas and protypes are presented:</p>
<p><a href="/en/current/explorative-ai-projects-2025/team-smart-campus/" title="Team Smart Campus">Team Smart Campus</a></p>
<p><a href="/en/current/explorative-ai-projects-2025/team-smart-uni/" title="Team Smart Uni">Team Smart Uni</a></p>
<p><a href="/en/current/explorative-ai-projects-2025/team-10xindividual/" title="Team 10xIndividual">Team 10xIndividual</a></p>
<p><a href="/en/current/explorative-ai-projects-2025/team-data-exploit/" title="Team Data Exploit">Team Data Exploit</a></p>
<p><a href="/en/current/explorative-ai-projects-2025/team-education/" title="Team Education">Team Education</a></p>
<p><a href="/en/current/explorative-ai-projects-2025/team-upskill/" title="Team Upskill">Team Upskill</a></p>
<p><a href="/en/current/explorative-ai-projects-2025/team-ai-based-feedback/" title="Team AI-based feedback">Team AI-based feedback</a></p>

<p>The video explains how Descript streamlines video editing for interviews recorded in Teams by leveraging automated transcription and easy text-based editing. The presenter demonstrates importing a video, using the cloud-based interface, and fixing transcription errors. Descript allows users to cut sections by simply deleting text, merge clips, and automatically remove long pauses, greatly speeding up the process.</p>
<p>Subtitles can be quickly added and customized, and translations to English are supported with editable captions. This workflow is ideal for teams handling numerous videos, ensuring consistency and efficiency. The end result is a polished, subtitled video ready for final review and publication in just minutes.</p>
<h4>Key takeaways:</h4>
<ul>
<li>Descript enables efficient text-based video editing.</li>
<li>Automatic transcription and pause removal save significant time.</li>
<li>Subtitles and translations are quickly added and customizable.</li>
<li>Collaboration and review are streamlined with easy editing tools.</li>
</ul>

<h2>Download presentation slides</h2>
<p>View and download presentation slides of the project.</p>

Summar project AI 2025 presentation

Team Smart Campus

Team Smart Uni

Team 10xIndividual

Team Data Exploit

Team Education

Team Upskill

Team AI-based feedback

Choose subject

Course syllabus for

Subject

Each academic year contains different courses

See programme page at universityadmissions.se

Educational area

Permissible substitutions of compulsory courses

To see your programme syllabus – select the academic year in which you started the programme.

[en: page.studyprogrammepage.syllabusesview.coursesdescription]

Explorative AI projects 2025

Explorative AI projects 2025

About the project

Video description: About the project

Idea generation

Video description: Idea generation

Recruitment

Video description: Recruitment

Execution

Video description: Execution

Tools and services used

Video description: Tools and services used

Exploitation of results and continuation

Video descritption: Exploitation of results and continuation

Main learnings and takeaways

Video description: Main learnings and takeaways

Project teams

Edit and transcribe video with Descript

Video descritpion: Edit and transcribe video with Descript

Download presentation slides