Agency launches tender for generative AI learning tools
Tender seeks suppliers to embed generative AI into an institutional training platform, signalling growing demand for trusted AI in workforce learning.
Tender seeks suppliers to embed generative AI into an institutional training platform, signalling growing demand for trusted AI in workforce learning.
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The European Maritime Safety Agency has opened a contract for generative AI tools to upgrade its EMSA Academy training services, moving advanced technology into a specialist maritime learning environment. By seeking “innovative tools to enhance the EMSA Academy's learning services through generative AI and related technologies”, the agency is looking for suppliers that can blend robust AI capabilities with the demands of technical training and regulation.
Published on 22nd May 2026, the Enhanced Technical Capabilities contract notice is focused squarely on implementation rather than exploration. The agency wants concrete tools that can be deployed in the EMSA Academy to improve how learning is delivered, supported and managed.
Across education and training, generative AI is being used to create or adapt learning content, support learners through conversational assistants and provide richer analytics on progress. The notice does not spell out which of these functions are in scope, but the emphasis on “enhanced technical capabilities” for the academy signals a move towards more automated and responsive learning support.
For a body rooted in maritime safety, training is a central way to spread consistent standards across many actors. Embedding AI into that training environment could help the agency refresh material more quickly as rules evolve, tailor learning to different audiences and maintain a clearer picture of how staff and partners are progressing.
The academy’s plans sit within a wider pattern of education and training bodies turning to AI to support learners and educators. In December 2025, Land Saarland, represented by the Ministry for Education and Culture, launched an AI Tool for Education for its Online School Saarland, seeking an AI-based web application to assist teachers and students in educational tasks, backed by training programmes for effective use.
Later that month, ITS Tirreno Academy-Fuscaldo went to market for software for digital laboratories, combining immersive teaching and artificial intelligence in five digital labs as part of a national recovery and resilience plan. In April 2026, Nacionalinė švietimo agentūra followed with a tender for AI learning platform services, seeking the acquisition and implementation of an AI technology-based learning platform tailored to specific needs.
In March 2026, Państwowa Akademia Nauk Stosowanych im. Ignacego Mościckiego w Ciechanowie published a notice for an AI micro-learning platform, covering implementation, maintenance and analytical and technical support services. Around the same time, Ypourgeio Paideias, Thriskevmaton kai Athlitismou launched an AI support system for education to provide immediate and accurate information for primary and secondary education using AI and natural language processing, while Epiteliki Domi ESPA Y.PAI.TH.A. set out plans for a smart predictive staffing system to allocate education resources more transparently.
Together, these notices show public education and training institutions commissioning AI not just to add new tools but to reshape how information flows, how staff get support and how resources are planned. The EMSA Academy tender sits in that same stream, but in a niche domain where the content is highly technical and closely tied to safety and regulation.
The focus on generative AI inevitably brings questions about governance, bias and accountability. Several recent procurements suggest public bodies are now building governance into AI projects from the outset. In May 2026, BOLD TEHNOLOGIES SRL advertised a contract to support AI governance software development for its MA'AT project, aiming to build a platform that includes ethical audits, bias detection in language models and ESG reporting.
Closely linked to that, in February 2026 Academia de Studii Economice Bucuresti sought research infrastructure for an AI project, including a generative AI processing system and IT&C equipment, again for MA'AT. The pairing of infrastructure and governance underlines how serious AI adopters are treating model development, deployment and oversight as parts of a single continuum.
Other buyers are prioritising secure, compliant access to large language models. In February 2026, Folkhälsomyndigheten published a call for a hosted LLM service that includes an end-user assistant and agent platform, plus customisation, support and maintenance. The specification highlights scalability, security and compliance with legislation for the public health agency, signalling a preference for controlled enterprise services over consumer-grade AI tools.
Similarly, in December 2025 Oesterreichische Nationalbank went to market for a legal AI tool in the form of an AI-supported cloud service for legal research and answers to complex questions on Austrian and EU law. BG-Phoenics GmbH, meanwhile, is establishing a framework for support services focused on machine learning and data engineering roles in its enterprise services division.
For EMSA, bringing generative AI into its academy will sit squarely in this governance-heavy landscape. Any tools that support learning about safety-critical topics will need to be accurate, explainable and aligned with institutional policies, even as they promise faster content production and more responsive support for learners.
While the EMSA Academy notice focuses on learning services, many peer organisations are using AI to optimise day-to-day operations. In May 2026, HOMELAND SECURITY, DEPARTMENT OF in the United States signalled plans to extend AI/ML support services for security screening systems, using systems engineering and technical assistance to refine existing artificial intelligence and machine learning efforts and improve the experience of the travelling public.
Emergency and critical infrastructure services are heading in the same direction. In January 2026, Serviciul de Telecomunicatii Speciale tendered for AI and ML software development services to build a platform that optimises operational processes within the national emergency management system SNUAU, combining new software components with training and integration. Anexartitos Diacheiristis Metaforas Ilektrikis Energeias AE (ADMIE AE) has a contract notice for data management and AI services, using AI and machine learning to clean and enrich operational data, support real-time interoperability and create secure data management procedures.
N-ERGIE Aktiengesellschaft is seeking software development services to design, implement and optimise data platforms and AI solutions, while 2M-IT Oy has gone to market for expert services in information management, explicitly covering AI, machine learning and modern information platforms for social and healthcare sectors. Rete Ferroviaria Italiana S.p.A, meanwhile, is commissioning an algorithm and analytical system based on machine learning to enhance railway infrastructure maintenance and diagnostics.
Viewed together, these operational projects and the EMSA Academy initiative point to a public sector that is commissioning AI as core infrastructure. Training, planning and frontline services are being redesigned around data-rich, AI-enabled platforms rather than treated as isolated pilots.
The EMSA contract notice is concise, emphasising implementation of generative AI and related technologies but leaving detailed specifications to the procurement documents. The key signal is that a specialist European agency now sees generative AI as mature enough to embed in its formal training offer.
Other training-focused procurements suggest how the market for learning services is evolving at the same time. In February 2026, NS Groep N.V. launched a tender for an external learning service provider, while Rivamadrid’s municipal services company is creating a dynamic acquisition system for training services, and EMUASA is seeking a similar system for management services and training delivery. The infrastructure around learning – from content and platforms to procurement models – is changing alongside the technology itself.
For the European Maritime Safety Agency, success will mean delivering AI-enhanced learning that is trusted by maritime professionals and proportionate to the risks of the domain it serves. For the wider market, the Enhanced Technical Capabilities tender will be another test of how generative AI can be woven into public-sector workflows in a way that improves productivity without diluting human oversight.
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