Master Thesis: AI-Enabled Operating Models for the Future of Software Supply
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Quick Summary
Key Responsibilities
* Analyze selected Software Supply processes and operational workflows. * Establish a baseline of current work, including task volumes, exceptions, data-quality dependencies, and cost-to-serve.
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## Join our Team
About this opportunity
Software Supply organizations are facing increasing demands for efficiency, scalability, data quality, and operational excellence. At the same time, advances in Artificial Intelligence create new opportunities to transform how operational work is performed, shifting from manual transaction execution toward standardized, exception-based, and insight-led operations.This thesis will explore how AI can reshape the future operating model of Software Supply. The work will analyze current ways of working, identify opportunities for different levels of AI-enabled autonomy, and develop a target operating model that balances automation, human oversight, governance, and decision-making.The expected outcomes include a future-state operating model, recommendations for AI adoption, and guidance on the skills, governance, and organizational capabilities required for Software Supply in 2030 and beyond.
What you will do
During the thesis, you will:
* Analyze selected Software Supply processes and operational workflows.
* Establish a baseline of current work, including task volumes, exceptions, data-quality dependencies, and cost-to-serve.
* Investigate how AI can support different levels of operational autonomy.
Develop a target operating model categorizing activities as:
\- Assist
\- Recommend
\- Execute with approval
\- Execute under defined policy
* Define future roles, responsibilities, decision rights, and human-in-the-loop approval points.
* Assess governance, control, risk, and compliance considerations.Identify implications for future skills, reskilling, and organizational adoption.
* Develop recommendations for the evolution of Software Supply operations toward 2030+.
Present your findings and document the work in a written thesis report.
The skills you bring
This opportunity is suitable for one or two Master's students studying Industrial Engineering, Supply Chain Management, Business Analytics, Data Science, Artificial Intelligence, Information Systems, Operations Management, or a related field.
We are looking for candidates with:
* Strong analytical and problem-solving skills.Interest in AI, business transformation, and future operating models.
* Knowledge of process improvement, operations, supply chain, or service management.
* Ability to analyze data and translate findings into practical recommendations.
* Experience with process mapping, stakeholder interviews, and business analysis.
* Curiosity about how AI can transform enterprise operations.
* Ability to work independently and collaborate with technical and business stakeholders.
This Master's thesis project can be carried out at either our Linköping or Stockholm office.
Why join Ericsson?At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply?Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Linköping
Req ID: 791820
Location & Eligibility
Where is the job
—
Location terms not specified
Listing Details
- Posted
- October 9, 2026
- First seen
- October 9, 2026
- Last seen
- October 9, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 56%
- Scored at
- October 9, 2026
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