Master Thesis within: Enterprise AI Lifecycle Governance
Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 23, 2026. Husqvarna Group scores B on the Alion truth index.
Last date to apply:
15 October 2026We are now looking for master’s students within Industrial Engineering, Engineering Management, Business and Technology, or an equivalent engineering program who are interested in doing their thesis project within Husqvarna Group’s Enterprise AI Hub.
Background
Many organizations have established software development processes, yet AI introduces additional considerations regarding experimentation, validation, risk management, model monitoring, compliance, and lifecycle ownership.
This thesis project will investigate how academic literature and relevant industry practices describe and steer governance throughout the AI lifecycle. It will examine how lifecycle stages, decision gates, and evaluation criteria can support effective and responsible AI delivery.
The focus will be on providing structured knowledge and decision support for Husqvarna Group’s Enterprise AI Hub, which develops AI capabilities and solutions for the wider Husqvarna Group.
The thesis will not define Husqvarna Group’s future AI governance model or make organizational decisions. Instead, it will provide research-based insights, alternatives, trade-offs, and evaluation criteria that can support future discussions and decisions in this area.
The objective
The overall goal of the thesis is to investigate governance models for enterprise AI, with particular focus on decision gates, risk management, and lifecycle oversight from ideation to production and continued operation.
The student is expected to investigate and contribute within the areas outlined below. The exact scope, lifecycle stages, AI use-case categories, and degree of practical application will be agreed upon between the student, academic supervisor, and Husqvarna thesis sponsor.
Investigate AI lifecycle governance models
- Review academic literature describing AI lifecycle management.
- Analyze governance mechanisms used throughout the AI lifecycle.
- Compare AI-specific governance approaches with traditional product and software development frameworks.
- Identify common lifecycle stages, decision points, and ownership responsibilities.
Investigate decision-making mechanisms
- Examine how organizations assess progression between AI lifecycle stages.
- Analyze governance criteria used when moving from experimentation to production.
- Investigate how risk, value realization, and technical feasibility are balanced in decision making.
- Explore governance practices for model changes, retraining, continued operation, and retirement.
Develop a decision-support framework
- Summarize governance principles identified in academic literature.
- Develop an evaluation framework for assessing AI lifecycle governance.
- Identify strengths, weaknesses, and trade-offs between alternative approaches.
- Provide research-based insights and recommendations for future discussions within Husqvarna Group.
Proper area of education
We are primarily looking for Master of Science student(s) in Industrial Engineering and Management, Business and Technology, Innovation Management or equivalent business-oriented engineering program
The student should preferably have:
- Strong analytical and conceptual capabilities.
- An interest in artificial intelligence, business transformation, and technology management.
- An interest in performance measurement, value realization, or management control.
- Strong communication and stakeholder-management skills.
- The ability to work independently in an organizational setting.
Prior technical AI development experience is not required. However, an interest in understanding the characteristics and lifecycle implications of different AI use cases is valuable.
The thesis will include work such as
- Literature review on AI lifecycle governance
- Benchmarking of AI governance and lifecycle models
- Analysis of lifecycle stages, decision points, and governance criteria
- Review of risk, value, feasibility, and operational readiness considerations
- Stakeholder interviews or workshops within Husqvarna Group
- Development of a proposed AI lifecycle governance framework
- Documentation and presentation of findings and recommendations for Husqvarna Group
Expected deliverables
- Literature review of AI lifecycle governance.
- Benchmark of governance approaches used by relevant organizations, if included in the agreed scope.
- AI lifecycle governance framework.
- Decision-gate assessment model.
- Set of evaluation criteria for future governance discussions.
- Research-based insights and alternatives to support future decision making within the Enterprise AI Hub.
How to apply
Please send in your application with CV and cover letter as soon as possible. Due to GDPR, we do not accept applications by email.
Start date of the thesis project is in Spring 2027, Q1 (Preferred start in January, kick-off and introductions in December)
For questions regarding the thesis project, please contact:
Åsa Björndahl,[email protected]
Read about Husqvarna Group here: https://www.husqvarnagroup.com/
Husqvarna Group is a world-leading producer of outdoor power products for garden, park, and forest care. Products include chainsaws, trimmers, robotic lawn mowers, and ride-on lawn mowers. The Group is also the European leader in garden watering products and a world leader in cutting equipment and diamond tools for the construction and stone industries.