Expected Outcome:
While today’s AI agents still have limited capabilities, advances in model architecture, memory, reasoning, and autonomous behaviour are paving the way to unlocking their potential across economic sectors. The Apply AI Strategy[1]acknowledges this trend and the need to advance research on next-generation AI agents. Project results are expected to contribute to some of the following expected outcomes:
- Significant improvements in the autonomy, robustness and reliability of AI agents through advanced planning mechanisms, memory management, and reasoning capabilities.
- Innovative multi-agent frameworks and protocols demonstrating effective decentralized coordination and collaboration among multiple AI agents beyond the capabilities of individual agents.
Scope:
Next-generation AI agents are autonomous systems powered by large AI language models (e.g., large language models or large multimodal models), that can plan, utilize tools and perform actions autonomously to achieve specified goals based on high-level instructions. The large AI model acts as the agent's "brain," capable of interpreting instructions, generating plans, and using tools. This capability enables agents to autonomously plan and adapt behaviour in real-time to accomplish complex, multi-step tasks. AI Agents hold significant promise in numerous applications areas such as data analytics and coding.
Effective AI agents require careful design, incorporating structured planning and reasoning methods to manage complex tasks, and be equipped with appropriate validation and monitoring techniques. Multi-agent collaboration frameworks further enhance capabilities by enabling structured interactions among multiple agents.
Key aspects in designing effective AI agents include robust planning, reasoning, and search mechanisms that allow agents to approach complex tasks by breaking them down into structured subgoals. Effective memory and state management are necessary to maintaining coherent long-term interactions, achieved through a balanced integration of short-term and external long-term memory solutions. Moreover, integrating external tools and APIs is essential for overcoming limitations in large AI models, enhancing agent performance in tasks requiring accuracy and reliability.
Potential research areas include enhancing AI agent autonomy through advanced self-planning and self-optimization capabilities, enabling agents to improve their decision-making and strategic planning. Other research directions include innovation in memory-augmented AI agents to facilitate robust long-term reasoning and lifelong learning; developing advanced multi-agent frameworks specifically tailored for collaborative agents, including research on AI agent frameworks based on mixed AI architectures, and advancing multimodal reasoning capabilities to enable real-world applications.
All proposals are expected to incorporate mechanisms for assessing and demonstrating progress, including qualitative and quantitative KPIs, benchmarking, and progress monitoring. When possible, proposals should build on and reuse public results from relevant previous funded actions. Communicable results should be shared with the European R&D community through the AI-on-demand platform.
Projects selected in this topic should link to the resources offered by the AI Factories, including the Data Labs. The results may be validated in the Testing and Experiment Facilities and further deployed via the European Digital Innovation Hubs (EDIHs) and will contribute to the Apply AI strategy.
This topic implements the co-programmed European Partnership on AI, data, and robotics (ADRA), and all proposals are expected to allocate tasks for cohesion activities with ADRA and the CSA HORIZON-CL4-2025-03-HUMAN-18: GenAI4EU central Hub. Proposals should also build on or seek collaboration with relevant projects and develop synergies with other relevant International, European, national, or regional initiatives.
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Activities are expected to start at TRL 2 and achieve TRL 5 by the end of the project – see General Annex B.
[1] COM xxxx(2025) Apply AI Strategy - PLACEHOLDER
News flashes
2026-10-08
EVALUATION RESULTS
Published: 15.01.2026
Deadline: 15.04.2026
Available budget: EUR 85,500,000.00
The results of the evaluation for each topic are as follows:
HORIZON-CL4-2026-05-DIGITAL-EMERGING-02
HORIZON-CL4-2026-05-DIGITAL-EMERGING-03
HORIZON-CL4-2026-05-MAT-PROD-25
Number of proposals submitted (including proposals transferred from or to other calls)
83
59
108
Number of inadmissible proposals
1
2
0
Number of ineligible proposals
3
1
1
Number of above-threshold proposals
64
42
99
Total budget requested for above-threshold proposals
1,170,345,703.75 €
499,059,353.25 €
682,299,097.77 €
Number of proposals retained for funding
2
2
3
Number of proposals in the reserve list
1
2
2
Funding threshold1
15
15
15
Ranking distribution
Number of proposals with scores lower or equal to 15 and higher or equal to 14
13
6
24
Number of proposals with scores lower than 14 and higher or equal to 13
15
8
23
Number of proposals with scores lower than 13 and higher or equal to 10
36
28
52
1 Proposals with the same score were ranked according to the priority order procedure set out in the call conditions (for HE, in the General Annexes to the Work Programme or specific arrangements in the specific call/topic conditions). For HE, to determine the ranking for ‘Innovation actions’, the score for ‘Impact’ is given a weight of 1.5.
Summary of observer report:
The evaluation of the proposals of this call followed the standard procedure for single stage call evaluations. The evaluation was performed in two phases: a remote one and a central one in Brussels.
The evaluation ran smoothly, and all deadlines were met. The evaluation complied with the applicable rules.
The process was transparent and fair. The quality of the consensus reports and the evaluation summary reports was excellent.
All experts complied with the requirement to act with independence, impartiality, objectivity, accuracy, and consistency. All experts worked at the highest level of quality and performance.
The guidance provided by the responsible HaDEA service through briefings, documents, and direct consultation, was excellent.
The quality of this evaluation was excellent and achieved its purpose of funding proposals of the highest quality.
We recently informed the applicants about the evaluation results for their proposals.
For questions, please contact: the Research Enquiry Service.
2026-10-08
PROPOSAL NUMBERS
Call HORIZON-CL4-2026-05 has closed on 15 April 2026.
A total of 250 proposals were submitted in response to this call.
The number of proposals for each topic is shown below:
HORIZON-CL4-2026-05-DIGITAL-EMERGING-02 - Next-Generation AI Agents for Real-World Applications in the Apply AI sectors (RIA) (Partnership in AI, Data and Robotics)
83 proposals submitted (indicative topic budget 38 EUR million)
HORIZON-CL4-2026-05-DIGITAL-EMERGING-03 - Apply AI: Next-Generation Agile and Intelligent Robotics Platforms for Industrial and Service Applications (Partnership in AI, Data and Robotics) (RIA)
59 proposals submitted (indicative topic budget 25 EUR million)
HORIZON-CL4-2026-05-MAT-PROD-25 - New or enhanced Innovative Advanced Materials (IAM) enabled sensing functionality (RIA)
108 proposals submitted (indicative topic budget 22.50 EUR million)
The evaluation results are expected to be communicated in July 2026.
2026-10-08
The submission session is now available for: HORIZON-CL4-2026-05-MAT-PROD-25, HORIZON-CL4-2026-05-DIGITAL-EMERGING-02, HORIZON-CL4-2026-05-DIGITAL-EMERGING-03
