From Ideation to Implementation: How AI-Driven Development is Reshaping the Future of Early-Stage Ventures

You are invited to apply for a fully funded PhD investigating the intersection of artificial intelligence and software engineering. Embedded within a live venture-studio, the project explores how AI-first development reshapes startup creation, engineering practice, and innovation economics in real-world, high-uncertainty settings. Location This PhD is a full time, on campus position based at Aston University. You'll spend most of your time working within the university's research and innovation community, with a 3 to 4 month placement at Greater Things (located within the Aston Design Factory). Background and context Generative AI and large language models are transforming how software is designed and built, dissolving the traditional boundaries between design, development, and deployment. Tools such as intelligent code assistants and automated UX systems are enabling non‑technical founders to co‑create digital products alongside developers and AI systems. Venture studios like Greater Things are leading this shift, experimenting with “AI‑first” development practices to accelerate early‑stage venture creation within a regional innovation ecosystem. Yet, we still know little about how AI‑assisted software development changes teamwork, decision‑making, and innovation over time. Academic research in this space is still emerging. This PhD aims to address that gap by studying AI‑native engineering practices as they evolve in real‑world venture settings. Project focus In this project, you will explore how AI‑first software engineering is reshaping the methods and economics of early‑stage venture creation. You will examine how non‑technical founders, developers, and AI systems work together to scope, design, and build software — and how these collaborations influence productivity, software quality, inclusivity, and innovation cycles. Your work will combine perspectives from digital innovation research and socio‑technical systems theory, with a strong focus on understanding human–AI collaboration in high‑uncertainty environments. You will propose and validate a systematic framework explaining how these new forms of co‑creation operate in practice. Research design and methods You will start with a focused literature review on digital innovation, human–AI collaboration, software engineering, and entrepreneurship to identify core theoretical and practical gaps. The main part of your research will be empirical. You will conduct ethnographic fieldwork within Greater Things, observing venture creation in action and interviewing founders, student developers, and AI tools throughout full venture cycles. This will help you capture patterns of collaboration, learning, and decision‑making as they unfold. You will then carry out comparative case studies of several ventures that use different levels of AI integration. These cases will help you understand how AI shapes team coordination, workflow design, and innovation outcomes. Alongside this, you will analyse quantitative data such as development velocity, feature delivery, and participation diversity to provide a holistic view of performance and inclusivity. Using design ethnography, you will also study co‑creative sessions in depth, looking closely at how human–AI interaction influences design choices, technical decisions, and innovation pivots. Finally, you will synthesise your findings into a new theoretical framework for AI‑native venture creation, refining and validating it through stakeholder workshops, expert feedback, and pilot applications in new venture cohorts. Why this project matters This PhD offers a rare opportunity to study AI‑first software engineering as it happens. You will gain firsthand experience inside an active venture studio, contribute original research to a fast‑moving field, and help shape future debates about software development, entrepreneurship, and regional innovation. Your findings will have practical value for founders, educators, and policymakers who are building the next generation of AI‑enabled ventures.

Candidates should have been awarded, or expect to achieve, EITHER:

A Bachelors degree in a relevant subject with an award of First Class or 2.1.
OR

A Bachelors degree in a relevant subject with an award of First Class or 2.1, and a Masters degree in a relevant subject with an award of Merit or higher.
Qualifications from other countries which are considered by Aston University to be equivalent to that described above will be eligible to apply.

You'll ideally have a strong foundation in AI and software engineering, with a keen interest in how generative models are changing development workflows and innovation practices. Experience in areas such as machine learning, human–AI interaction, or intelligent software tools will be valuable. You should enjoy combining technical insight with qualitative research, exploring how teams and technologies co create in real world venture settings.
Contact information

Dr Shereen Fouad at s.fouad@aston.ac.uk.

Apply here

Interviews

Interviews will take place remotely via Microsoft Teams. If shortlisted, you will be invited to share a short presentation about your research interests or relevant experience as part of the interview process. This will help us learn more about your approach to research and your motivation for joining the project.