Trust and Generative AI in Agile Software Development: Building the Next-Generation Trust Maturity Model

About the Project

Trust is the invisible glue that holds Agile software development together. Teams rely on openness, accountability, and shared confidence to deliver high-quality software at speed. Yet in today’s fast-moving digital landscape, trust is fragile: distributed teams, growing complexity, and the introduction of AI-based tools can strain relationships between developers, stakeholders, and organizations. The collaboration between humans and AI should be aimed at ensuring human get the most out of the AI systems in terms of trust and transparency for effective Agile processes (Tyagi et al., 2022; Caldwell et.al., 2022).

This PhD project explores how Generative AI can be embedded into the Agile process to strengthen, rather than undermine, trust. You will build on an Enhanced Trust Maturity Model, mapping how teams evolve from low-trust beginnings to trusted partnerships. At each stage, you will investigate how AI can support beginning from simple tools that make work more transparent, through predictive analytics that improve planning, to advanced AI advisors that help teams self-adapt, and finally to responsible AI systems that reinforce trust as part of organizational culture.

The scope of this research focuses on shaping the future of software development process especially digital transformation to depend on the ability to foster reliable and ethical collaborations. The project sits at the heart of current debates in computing and society and will try to answer the following or related research questions

• Can AI support human creativity rather than replace it?
• How do we ensure AI is explainable and fair in collaborative workplaces?
• How do we balance automation with human judgment? etc.

These are open challenges with implications for both the tech industry and wider society. As a doctoral researcher, you will design new AI-supported methods for Agile practice, conduct empirical studies, and contribute to theory on trust in socio-technical systems. Possible research activities include building prototypes (e.g., AI-assisted sprint planning tools), developing trust measurement frameworks, and conducting real-world case studies with industry.

This will be an exciting opportunity to work at the intersection of cutting-edge AI, human–computer interaction, and software engineering. You will not only contribute to academic knowledge but also help shape the future of teamwork in an AI-driven world. If you are motivated by combining technical creativity with social impact, this project offers the chance to pioneer approaches that could redefine how software teams collaborate globally.

Academic qualifications

A first degree (minimum 2:1 classification)

Background in Computer Science, Software Engineering, AI/ML, or Human–Computer Interaction.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

• Ability to conduct research
• Good communication skills in both speaking and writing
• Ability to demonstrate initiative and conduct independent research
• Effective Time management

Desirable attributes:

An understanding or background in Agile methods, trust in socio-technical systems, or applied AI would be beneficial.

APPLICATION CHECKLIST

• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about
  1. Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
  2. Research questions or objectives.
  3. Methodology: types of data to be used, approach to data collection, and data analysis methods.
  4. List of references.

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

To be considered, the application must use

• the advertised title as project title

For informal enquiries about this PhD project, please contact O.Bamgboye@napier.ac.uk

Application Enquiries: https://www.napier.ac.uk/research-and-innovation/doctoral-college/application-guidance

Application link: https://evision.napier.ac.uk/si/sits.urd/run/siw_sso.go?ElOlarlItFiG37xnH5PRRBvv3d563wLdwX4JfhYskMa3bJWTuc