Public procurement plays an essential role in shaping economic and social development across the UK. With around 195 billion pounds spent annually on public contracts, the decisions made by government buyers influence innovation, local growth and service delivery. Recent innovation funding through programmes such as Innovate UK’s Growth Catalyst Early Stage New Innovators has supported research examining how artificial intelligence can improve fairness, visibility and accessibility in public procurement. This work explores how AI systems may help public bodies identify qualified small and medium sized enterprises and diverse owned businesses more effectively, and how structured data can reduce barriers that often prevent these suppliers from being considered.
The Procurement Act 2023 aims to strengthen transparency and equality in public procurement. To meet these expectations, public sector teams require modern data infrastructure, updated processes and technologies that can interpret complex information. Artificial intelligence is increasingly recognised as an important enabler of these ambitions and is being studied for its potential to support more inclusive and evidence based procurement practices.
Why Inclusion Still Lags Behind
Small and medium sized enterprises and diverse owned businesses contribute significantly to the UK economy, yet many remain underrepresented in public procurement. Procurement processes are often resource intensive, documentation can be lengthy and technical, and supplier information is dispersed across multiple systems. These factors reduce visibility and can place smaller and diverse owned suppliers at a disadvantage compared with larger organisations.
These challenges reflect systemic limitations rather than capability gaps. Improving fair access requires procurement frameworks that are more accessible, more consistent and supported by tools that help buyers understand suppliers at scale. Research into AI driven procurement models aims to address these issues by enabling teams to analyse large datasets and identify capable suppliers who may otherwise remain overlooked.
How AI Supports Fairer Procurement
Artificial intelligence can assist procurement teams by analysing complex documents, detecting patterns and identifying potential barriers that may unintentionally exclude SMEs and diverse owned businesses. Natural language processing can examine tender documents and highlight requirements that restrict participation. Machine learning can support more objective supplier matching by assessing capabilities and relevance. Automated insights can also help public bodies meet transparency expectations introduced under the Procurement Act.
These technologies are designed to support human judgment rather than replace it. By reducing manual workload and presenting clearer information, AI can enhance evaluation processes and contribute to more consistent and evidence based decision making.
The Role of Innovation Funding
Innovation funding is playing a meaningful role in advancing research focused on fairer procurement practices. Programmes such as Innovate UK’s New Innovators initiative are supporting work that examines how structured procurement data, AI matching models and barrier detection techniques may contribute to more inclusive supplier participation. This research aims to generate evidence on how new technologies can be responsibly integrated into procurement environments while upholding principles of transparency and equal access.
This aligns with the broader goals of the Procurement Act, which emphasises openness, fairness and improved economic outcomes across the public sector supply chain.
Academic Contributions and Research Partnerships
Universities and research institutions are an essential part of this work, contributing expertise in algorithmic fairness, ethical governance, data quality and user engagement. Their involvement ensures that emerging AI tools are assessed rigorously and that methodologies remain aligned with public sector values.
Academic research also helps identify potential risks early, including biased datasets or uneven representation of supplier groups. These findings support the development of responsible AI systems that prioritise fairness and accountability before wider adoption.
Turning Policy Into Practical Outcomes
Although the Procurement Act provides clear principles, public bodies require practical tools to apply them consistently. AI can support this transition by enhancing supplier discovery, identifying restrictive wording in tender documents and generating transparent audit trails. Systematic analysis of procurement data can help uncover inclusion barriers earlier, enabling teams to adjust requirements before opportunities are published.
These tools can support more uniform application of fairness and improve accessibility across different procurement categories and regions.
What the Future May Look Like
As AI and data systems evolve, procurement processes are expected to become more transparent, more data driven and more inclusive. Predictive tools may help identify suitable SMEs and diverse owned businesses earlier in procurement planning. Interoperable supplier databases could improve visibility across sectors. Real time dashboards may offer public bodies better insights into inclusion outcomes and participation levels.
Advances in explainable AI may also make supplier evaluations more transparent, increasing trust across the procurement landscape.
Building a System That Works for Everyone
Fair procurement supports innovation, strengthens competition and contributes to inclusive economic development across the UK. Innovation funding continues to play a key role by enabling research that explores responsible and effective ways to modernise procurement. As AI capabilities grow, the UK has an opportunity to build procurement systems where capability and quality determine access. Achieving this requires collaboration between policymakers, researchers and public sector teams. Together, these efforts can support a procurement environment that is more transparent, more equitable and aligned with public interest.
