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Innovate UK, part of UK Research and Innovation (UKRI), has announced the BridgeAI Deployment Catalyst, a funding programme designed to accelerate the real-world adoption of advanced Artificial Intelligence (AI) and Machine Learning (ML) technologies across strategically important UK industries.
The programme will invest up to £5 million in Phase 1, supporting UK-registered SMEs that have developed innovative AI solutions and are ready to address the challenges associated with deploying them in operational environments.
Unlike funding opportunities focused on early-stage AI research, the BridgeAI Deployment Catalyst targets existing AI technologies at Technology Readiness Levels (TRL) 5 or 6, with functioning minimum viable products that demonstrate potential for real-world implementation.
The competition is divided into three complementary funding strands, each addressing a different application of AI. Together, these strands aim to support the development of trusted, scalable and commercially viable AI solutions.
Across all three phases of the wider programme, Innovate UK expects to make up to £52 million available, subject to approval and funding decisions.
Key Dates and Funding
Competition Opens: 21 October 2026
Competition Closes: 8 December 2026, 11:00 am UK time
Total Phase 1 Funding: Up to £5 million
Individual Grant Funding: £100,000 to £200,000
Project Duration: 3 to 5 months
Three Funding Strands
Applicants must select one of the three funding strands, based on the primary purpose of their AI solution within the proposed deployment environment.
1. AI for Decision Critical Systems
This strand supports AI and ML solutions that assist people in making high-risk or consequential judgements, recommendations and decisions.
The focus is on applications where decisions can have significant consequences for an organisation, its operations or its end users.
Relevant applications could include AI-assisted clinical decision support, financial risk assessment, complex industrial decision-making or other high-stakes environments where reliable and explainable recommendations are essential.
Projects must demonstrate how the AI solution contributes to decision-making, the risks associated with its deployment and the technical or assurance challenges that must be addressed before operational adoption.
2. AI for Operational Systems
This strand focuses on AI solutions designed to perform, control or coordinate operational activities within workflows, equipment, infrastructure, software or industrial processes.
Projects should demonstrate how advanced AI can improve the reliability, performance or coordination of activities that are important to the deployer's core operations.
Potential applications include intelligent manufacturing systems, autonomous equipment, robotics, AI-enabled process optimisation, energy infrastructure management and other operational environments requiring reliable system integration.
The proposed innovation must go beyond routine automation or software implementation and address meaningful technical and operational deployment challenges.
3. AI for Assurance and Compliance
This strand supports AI systems whose primary purpose is to monitor, test, verify, validate or demonstrate compliance with regulatory requirements, standards or operational controls.
The focus is on solutions that help organisations establish whether their systems, processes or outcomes meet defined requirements.
Potential applications include automated regulatory monitoring, AI-enabled quality assurance, compliance verification, safety assessment and systems that generate evidence to support audits or regulatory obligations.
Projects must demonstrate how advanced AI improves the effectiveness, reliability or scalability of assurance and compliance activities while addressing the challenges associated with real-world deployment.
Eligible Technologies and AI Capabilities
Across all three strands, Innovate UK is seeking projects that demonstrate innovative and substantive applications of advanced AI or ML technologies.
Relevant capabilities may include:
Other AI and ML approaches may also be eligible where applicants can demonstrate their technical innovation and importance to the proposed deployment.
The AI capability must be central to the operational use case, rather than a secondary feature of an existing product or service.
Who Can Apply?
The competition is open to collaborative projects led by a UK-registered micro, small or medium-sized enterprise (SME) developing an advanced AI or ML solution.
Each consortium must include an eligible UK-registered deployer organisation that intends to adopt the technology.
Lead Applicant Requirements
The lead SME must:
Academic institutions cannot lead an application.
Deployer Organisation Requirements
Each project must include one UK-registered deployer organisation that is either a medium or large business, or a UK-based public sector organisation.
The deployer must provide access to the operational environment, users, data, workflows, systems or infrastructure required to assess deployment readiness.
The deployer must account for 30% to 50% of total eligible project costs and operate within one of the following sectors:
Consortium Requirements
The minimum consortium size is two organisations, consisting of the AI SME and an eligible deployer.
Applicants may include one additional UK-registered partner, bringing the maximum consortium size to three organisations. This partner may be a business, academic institution, research organisation, research and technology organisation, charity, not-for-profit organisation, public sector organisation or non-governmental organisation.
The additional partner can account for no more than 30% of total eligible project costs.
Subcontractors are not permitted.
A lead SME may submit only one application across all three strands and cannot participate as a collaborator in further applications. Deployer organisations may participate in up to three materially different applications across the strands.
What Must Phase 1 Projects Deliver?
Phase 1 is designed to establish whether an advanced AI solution and its intended deployment environment are ready to progress towards real-world implementation.
Projects must demonstrate a clear operational use case and assess the readiness of both the AI supplier and deployer organisation.
Expected activities and deliverables include:
1. Deployment use case development: Define the operational problem, intended users, expected benefits and value of the AI solution to the deployer.
2. Technical and commercial assessment: Demonstrate why the proposed AI system is an appropriate solution and assess its technical maturity, delivery capacity and commercial potential.
3. AI supplier readiness: Evaluate the supplier's ability to deliver and support the solution, including standards, regulatory compliance and technical capabilities.
4. Deployer readiness: Assess the operational, technical, governance, regulatory and assurance requirements of the intended deployment environment.
5. Future deployment partnerships: Obtain letters of support from potential additional deployers interested in participating in subsequent programme phases.
6. Phase 2 planning: Develop a clear plan for solution assurance, operational integration and deployment preparation.
7. Demonstration: Conduct a demonstration using representative deployer data and systems within a representative operational environment towards the end of the project.
These activities must address significant unresolved deployment challenges and demonstrate why the proposed project goes beyond routine implementation or configuration of an existing AI service.
Funding Rates
Phase 1 grants range from £100,000 to £200,000 per consortium.
The maximum funding contribution depends on the size and type of participating organisation.
Organisation type
Maximum funding rate
Micro and small businesses
70% of eligible costs
Medium-sized businesses
60% of eligible costs
Large businesses
50% of eligible costs
Eligible research organisations undertaking non-economic activities
Up to 100% of eligible costs
Academic institutions undertaking non-economic activities
80% of full economic costs
Research organisations undertaking non-economic activities can collectively account for up to 30% of total eligible project costs.
Applicants must ensure that the consortium's overall funding request remains within the £100,000 to £200,000 limit.
Projects That Will Not Be Funded
The BridgeAI Deployment Catalyst is intended for advanced AI technologies that have progressed beyond initial concept development.
Projects will not be funded if they:
Applicants must carefully select the appropriate funding strand. Applications submitted to the wrong strand cannot be transferred and will not be assessed.
Future Funding Opportunities: Phase 2 and Phase 3
The BridgeAI Deployment Catalyst is structured as a potential three-phase programme, designed to support AI solutions from feasibility assessment through to live deployment and wider replication.
Phase 1: Deployment Feasibility
Funding: £100,000 to £200,000 per consortium
Duration: 3 to 5 months
Phase 1 focuses on developing a robust deployment use case, assessing technical and operational readiness, identifying assurance requirements and demonstrating the solution in a representative environment.
Phase 2: Deployment Preparation
Indicative Funding: Up to £1 million per consortium
Indicative Duration: Approximately 6 months
Phase 2 is expected to support solution refinement, integration planning, operational readiness and the development of assurance evidence required for deployment.
Only projects invited to progress following Phase 1 review will be eligible to apply.
Phase 3: Live Deployment and Replication
Indicative Funding: Up to £2 million per consortium
Indicative Duration: Approximately 22 months
Phase 3 is expected to support live deployment with the initial deployer and replication across two additional organisations.
Later phases are expected to require co-investment from consortium members, with Phase 3 requiring committed co-investment from UK-based investors.
All Phase 2 and Phase 3 funding amounts, durations and requirements remain indicative and are subject to future approval and funding decisions.
Key Considerations for Applicants
Applicants should demonstrate a strong connection between their AI technology and a genuine operational challenge faced by the deployer.
Particular attention should be given to technology maturity, access to operational data and infrastructure, deployment risks, regulatory requirements, commercial value and scalability.
Projects should also explain how the proposed solution could be replicated across additional organisations and markets, supporting the programme's objective of accelerating the wider commercial adoption of advanced UK AI technologies.
Innovate UK will use a portfolio approach to funding decisions, seeking diversity across the three strands, industry sectors, AI technologies, deployment challenges and types of deployer.
How Inventya Can Help
The BridgeAI Deployment Catalyst offers an opportunity for UK AI SMEs to work directly with industry partners and develop a credible pathway towards commercial deployment. However, preparing a competitive application requires applicants to demonstrate more than technical innovation. Proposals must also establish operational relevance, partner readiness, deployment feasibility and a clear strategy for future commercial adoption.
Inventya supports innovative businesses in developing funding applications, strengthening commercialisation strategies and preparing collaborative projects for investment and market entry.
Inventya's support includes:
Through its expertise in innovation funding, business development and commercialisation, Inventya can help AI SMEs strengthen their applications and position their technologies for successful real-world deployment.
