Master Thesis work within: Enterprise-wide AI Performance Measurement

Last date to apply:

15 October 2026

We 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

Organizations are increasingly investing in artificial intelligence, including generative AI, predictive analytics, optimization, computer vision, and machine learning. However, many still struggle to assess whether AI initiatives create measurable and sustainable business value. Common questions include:

• What constitutes success for an AI initiative?
• How should AI value be measured?
• Which performance indicators are relevant at different stages?
• How should benefits be tracked after an AI solution has entered production?

AI initiatives evolve from early experimentation and concept validation to deployment, scaling, and long-term operation. The information needed to evaluate an early experiment may therefore differ significantly from what is needed to evaluate a mature AI solution in production. At Husqvarna, we work actively with this topic and are keen to understand these questions from an academic perspective.

This thesis project will investigate academic literature and relevant industry practices related to performance measurement and value realization for enterprise AI. The focus will be on providing structured knowledge and decision support for Husqvarna Group’s Enterprise AI Hub. The results may contribute to future discussions about how AI initiatives should be measured and followed up across their lifecycle.

The thesis will not determine how Husqvarna Group should manage or measure AI. Instead, it will provide research-based insights, alternatives, and evaluation criteria that can support future decisions in this area.

The objective

The overall goal of the thesis is to investigate performance measurement frameworks for enterprise AI, from experimentation to realized business value.

The student is expected to investigate and contribute within the areas outlined below. Given the breadth of the topic, the final scope will be refined during the initial weeks of the thesis together with the student(s), academic supervisor, and Husqvarna thesis sponsor.

Investigate AI measurement frameworks

• Review academic literature related to AI performance measurement.
• Investigate value realization frameworks used for AI initiatives.
• Analyze financial and non-financial performance indicators.
• Explore short-, medium-, and long-term value measurement approaches.

Investigate measurement across the AI lifecycle

• Examine how organizations evaluate AI initiatives at different maturity stages.
• Investigate metrics used during experimentation, pilot, and production phases.
• Analyze leading and lagging indicators.
• Explore links between AI investments and realized business outcomes.

Develop an AI KPI framework

• Identify KPI categories supported by academic literature.
• Develop a structured measurement framework.
• Define evaluation criteria for AI initiative performance.
• Provide research-based insights and recommendations for future KPI and portfolio discussions at 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 of different AI use cases is valuable.

The thesis will include work such as

• Literature review on AI performance measurement and value realization
• Benchmarking of AI KPI and measurement frameworks
• Analysis of financial and non-financial performance indicators
• Review of measurement needs across the AI lifecycle
• Stakeholder interviews or workshops within Husqvarna Group
• Development of a proposed AI performance measurement framework
• Documentation and presentation of findings and recommendations for Husqvarna Group

Expected deliverables - to be confirmed during first weeks of work

Research-based insights and evaluation criteria to support future decision making within the Enterprise AI Hub, e.g.:

• An academic literature review of AI value and performance measurement.
• Benchmark of AI KPI frameworks.
• AI performance measurement model.
• Value realization framework.
• Suggested KPI catalogue and classification model.

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.