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Adaptive AI ERP Interfaces (APART): Technical framework and Evaluation Methodology for building adaptive AI user interfaces within an ERP environment.

Doctoral Training Grant Funding Information 

This funding model includes a 36 month fully funded PhD Studentship, set in-line with UK Research & Innovation values. For 2025/6, this will be £20,780 per year. The tax-free stipend will be paid monthly. This PhD Studentship also includes a Full-Time Fee Scholarship for up to 3 years. The funding is subject to your continued registration on the research degree, making satisfactory progression within your PhD, as well as attendance on and successful completion of the Postgraduate Certificate in Research Practice.    

All applicants will receive the same stipend irrespective of fee status. 

Application Closing Date: 


Midday (UK Time) on Wednesday 17th September 2025 for a start date of 2nd February 2026.  

How to Apply 

To apply, please follow the below steps:  

  1. Complete the BCU Online Application Form. 
  2. Complete the Doctoral Studentship Proposal Form in full, ensuring that you quote the project ID. You will be required to upload your proposal in place of a personal statement on the BCU online application form.  
  3. Upload two references to your online application form (at least one of which must be an academic reference). 
  4. Upload your qualification(s) for entry onto the research degree programme. This will be Bachelor/Master’s certificate(s) and transcript(s). 
  5. International applicants must also provide a valid English language qualification. Please see the list of English language qualifications accepted here. Please check the individual research degree course page for the required scores. 

Frequently Asked Questions 

To help support you to complete your application, please consult the frequently asked questions below: 

Project title: Adaptive AI ERP Interfaces (APART): Technical framework and Evaluation Methodology for building adaptive AI user interfaces within an ERP environment

Project Lead: ​​Dr. Samer Bamansoor​ 

Project ID: 14 - 45489912 

Project description:

This PhD project will examine how AI-driven personalisation- using machine learning (ML), natural language understanding (NLU), and natural language generation (NLG) can be effectively embedded into Enterprise Resource Planning (ERP) systems to enhance user experience and operational efficiency. 

​While these technologies promise automation of workflows and less manual data entry, deploying them in real-world settings often encounters significant challenges. AI features within ERP systems often face usability and user adoption difficulties, primarily because of the insufficient application of User-Centred Design (UCD) principles during development. Common problems include user reluctance, lack of trust, and inefficient interactions, revealing a disconnect between technical capabilities and user needs. 

​This research aims to address these challenges by developing a comprehensive technical and design framework that integrates artificial intelligence into Enterprise Resource Planning (ERP) systems in a manner that is user-aware and human-centred. The focus will be on: 

  • ​Designing architectural patterns and implementation strategies for AI-enhanced personalisation in ERP 
  • ​Applying UCD principles to ensure AI features are understandable, usable, and trustworthy 
  • ​Defining and applying new metrics to evaluate the usability and effectiveness of AI-enhanced ERP interfaces 
  • ​Validating these approaches through user studies and technical assessments in real or simulated ERP environments 

​The project provides an exciting chance to connect advanced AI with real-world enterprise applications. You will contribute both theoretical knowledge and practical advice for creating AI-enabled ERP interfaces that are both technically robust and user-friendly. 

Anticipated findings and contributions to knowledge:

  • ​The research aims to address a significant deficiency in current knowledge by offering practical, technical guidance on the implementation of User-Centred Design (UCD) principles in AI features such as personalisation within complex ERP systems. Additionally, it will establish methodologies for assessing their usability and effectiveness from a technical perspective. 

  • ​Findings from the research will enhance our understanding of the relationship between technical and human factors in AI integration. The project will pinpoint key barriers to user interaction and acceptance and suggest strategies to reduce user resistance through design and engineering methods. 

  • The research will develop a comprehensive technical framework, reusable architectural patterns, and practical design guidelines to facilitate the development and assessment of AI-enhanced ERP interfaces. This effort encompasses the establishment of measurable metrics for evaluating user experience and system performance.

  • ​Ultimately, these results will facilitate more effective and user-friendly AI implementations in ERP systems, resulting in tangible enhancements in operational efficiency, user satisfaction, and technology adoption throughout enterprise settings.​ 

Person Specification:

Essential Criteria: 

  • ​Minimum of a 2:1 Honours degree (or equivalent) in Computer Science, Information Systems, Software Engineering, or a related discipline. 
  • ​A completed or near completed Master’s degree in a relevant field such as Computing, Data Analytics, Digital Transformation, or Enterprise Systems.
  • Knowledge or experience of Enterprise Resource Planning (ERP) systems and/or Artificial Intelligence (AI), including awareness of implementation or integration challenges. 
  • ​Strong written and verbal communication skills, with the ability to explain technical concepts to non-specialist audiences. 
  • ​Ability to work independently and collaboratively in a research setting. 
  • Evidence of critical thinking, reflective practice, and enthusiasm for cross-disciplinary research at the intersection of technology, organisations, and human-centred design. 

​Desirable Criteria: 

  • ​Prior industrial experience or project involvement related to digital transformation, ERP implementation, or user experience design. 
  • ​Familiarity with AI personalisation techniques, Natural Language Processing (NLP), or human-centred AI development. 
  • ​Experience working with software tools and platforms such as Power BI, Azure, SAP, Salesforce, or similar enterprise platforms. 
  • ​Published work in conference proceedings, journals, or contributions to academic research projects. 
​Candidates will be expected to engage fully with the academic and professional development opportunities offered by the Doctoral Research College and the wider research community at Birmingham City University. 

Overseas applicants:

International applicants must also provide a valid English language qualification, such as International English Language Test System (IELTS) or equivalent with an overall score of 6.5 with no band below 6.0.  

Contact:

If you have any questions or need further information, please use the contact details below: 

- For enquiries about the project, please contact: Samer Bamansoor Samer.Bamansoor@bcu.ac.uk, Gerald Feldman Gerald.Feldman@bcu.ac.uk  and Essa Shahra Essa.Shahra@bcu.ac.uk.​

- For enquiries about the application process, please contact: research.admissions@bcu.ac.uk