Tor Sporsem

Tita Alissa Bach, Aleksandar Babic, Narae Park et al.

The maritime industry requires effective communication among diverse stakeholders to address complex, safety-critical challenges. Industrial AI, including Large Language Models (LLMs), has the potential to augment human experts' workflows in this specialized domain. Our case study investigated the utility of LLMs in drafting replies to stakeholder inquiries and supporting case handlers. We conducted a preliminary study (observations and interviews), a survey, and a text similarity analysis (LLM-as-a-judge and Semantic Embedding Similarity). We discover that while LLM drafts can streamline workflows, they often require significant modifications to meet the specific demands of maritime communications. Though LLMs are not yet mature enough for safety-critical applications without human oversight, they can serve as valuable augmentative tools. Final decision-making thus must remain with human experts. However, by leveraging the strengths of both humans and LLMs, fostering human-AI collaboration, industries can increase efficiency while maintaining high standards of quality and precision tailored to each case.

Tor Sporsem, Rasmus Ulfsnes

This short paper explores how a maritime company develops and integrates large-language models (LLM). Specifically by looking at the requirements engineering for Retrieval Augmented Generation (RAG) systems in expert settings. Through a case study at a maritime service provider, we demonstrate how data scientists face a fundamental tension between user expectations of AI perfection and the correctness of the generated outputs. Our findings reveal that data scientists must identify context-specific "retrieval requirements" through iterative experimentation together with users because they are the ones who can determine correctness. We present an empirical process model describing how data scientists practically elicited these "retrieval requirements" and managed system limitations. This work advances software engineering knowledge by providing insights into the specialized requirements engineering processes for implementing RAG systems in complex domain-specific applications.

Tor Sporsem, Anastasiia Tkalich, Nils Brede Moe et al.

Software product innovation in large organizations is fundamentally chal-lenging because of restrained freedom and flexibility to conduct experi-ments. As a response, large agile companies form internal startups to initiate employ-driven innovation, inspired by Lean startup. This case study investi-gates how communities of practice support five internal startups in develop-ing new software products within a large organization. We observed six communities of practice meetings, two workshops and conducted ten semi-structured interviews over the course of a year. Our findings show that a community of practice, called the Innovation guild, allowed internal startups to help each other by collectively solving problems, creating shared practic-es, and sharing knowledge. This study confirms that benefits documented in earlier research into CoPs also hold true in the context of software product innovation in large organizations. Henceforth, we suggest that similar innova-tion guilds, as described in this paper, can support large companies in the in-novation race for new software products.

Anastasiia Tkalich, Nils Brede Moe, Tor Sporsem

To keep up with the pace of innovation, established companies are increasingly relying on internal software startups. However, succeeding with such startups is a challenging task because internal startups need to find a balance between the interests of the company and the interest of the innovator. One approach that is argued to strengthen innovation in existing companies is employee-driven innovation (EDI). This study explores this argument by examining two internal software startups in companies aligned with the principles of EDI and with a strong focus on innovation. The preliminary findings indicate that startups with EDI are characterized by commitment towards innovation, cooperative orientation, and autonomy. The findings suggest that internal software startups may be strengthened when the parent companies practice EDI.

Tor Sporsem, Anastasiia Tkalich, Nils Brede Moe et al.

Large global companies need to speed up their innovation activities to increase competitive advantage. However, such companies' organizational structures impede their ability to capture trends they are well aware of due to bureaucracy, slow decision-making, distributed departments, and distributed processes. One way to strengthen the innovation capability is through fostering internal startups. We report findings from an embedded multiple-case study of five internal startups in a globally distributed company to identify barriers for software product innovation: late involvement of software developers, executive sponsor is missing or not clarified, yearly budgeting and planning, unclear decision-making authority, lack of digital infrastructure for experimentation and access to data from external actors. Drawing on the framework of continuous software engineering proposed by Fitzgerald and Stol, we discuss the role of BizDev in software product innovation. We suggest that lack of continuity, rather than the lack of speed, is an ultimate challenge for internal startups in large global companies.