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ECF CASE STUDY

The European Climate Foundation (ECF), a pivotal force in climate advocacy, recognised Generative AI's transformative potential but faced significant challenges: limited AI literacy within its vast partner network, the unsuitability of generic AI tools for specialiSed advocacy needs, and no established framework for collaborative AI innovation. 

This risked diminishing their impact in the urgent climate fight. Hack Belgium Labs (HBL) architected a multi-phased strategic engagement, moving beyond a simple event to build foundational AI understanding, co-create highly relevant use cases, facilitate a targeted GenAI Hackathon, and nurture the development of tangible AI-powered projects. 

The result was a profound shift: two funded AI solutions (Kotakima and Commons in Madrid) directly addressing ECF needs, a marked increase in AI literacy and buy-in across the ECF network, the cultivation of a new "innovation mindset," and the establishment of a "collective innovation process"—a replicable prototype for future grantee-supplier-funder collaborations. HBL demonstrated its distinctive value in not just executing events, but in architecting sustainable innovation ecosystems, effectively bridging knowledge gaps, and transforming organizational capacity.

Participants
84

 Ideas Generated
25

Pitched Projects 
8

Funded Projects
2

 Addressed Challenge Areas
4

Experts & Mentors
33

Hackathon Duration
48

The AI Imperative in Climate Advocacy: ECF's Challenge & Opportunity

The European Climate Foundation stands as a crucial enabler in the global response to climate change. Recognising the seismic shifts brought by Generative AI, ECF saw an opportunity to revolutionize its network's approach to climate policy advocacy, strategic communications, and impact tracking. However, unlocking this potential was fraught with challenges.


The primary obstacle was the "buy-in bottleneck." As one ECF leader noted, "Without genuine buy-in for AI tools, deploying any tools emerging from the project would be very hard work indeed." This stemmed from a generally "limited AI literacy among ECF partners and a conservative approach" to new methodologies. There was a critical need to "bridge the gap between Grantees’ needs and what AI can do?"

Tool Mismatch

Generic, off-the-shelf AI tools were ill-suited for the nuanced and specialised needs of policy advocacy, campaign creation, and impact reporting.

Resource Constraints

Like many non-profits, ECF partners often lacked the dedicated time, substantial funding, and specialised AI expertise prevalent in the private sector.

Siloed Efforts

The existing landscape highlighted that network members "simply cannot work in a completely siloed manner and need effective collaborative methods" to truly leverage AI's potential.

Lack of Community

No pre-existing community focused on GenAI best practices, leading to missed opportunities for mutualisation, economies of scale, and peer learning.

Architecting the Solution: A Collaborative Phased Approach to AI Innovation

Hack Belgium Labs (HBL) believes that successful AI adoption within complex, diverse ecosystems is achieved not through isolated events but through a carefully orchestrated, multi-stage journey. Our guiding principle is that lasting change requires a deliberate approach, systematically building internal capacity, co-designing solutions tailored to specific needs, and fostering vigorous, sustained collaborative action. This philosophy underpinned our engagement with the European Climate Foundation (ECF), working in close partnership throughout the project.



Phase 1 & 2: Research, Frame & Analyse – Building the Foundation

The initial Research, Framing, and Analysis phase, jointly undertaken by HBL and key ECF personnel, was foundational. To "help ECF partners identify and then truly grasp the efficiency and effectiveness gains they can realise by using AI tools," HBL led a comprehensive context exploration. This involved in-depth interviews, facilitated by HBL, with ECF program directors and grantees, targeted surveys co-designed with ECF, and strategic consultations where both HBL and ECF teams analysed the findings. These activities were designed to meticulously map the existing landscape of AI understanding and pinpoint the core operational and advocacy needs within the ECF network. This collaborative groundwork was crucial for cultivating initial stakeholder buy-in and establishing a clear, shared definition of the problem space, thereby informing all subsequent stages of the project.

Phase 3: Ideate & Define – The Strategic Workshop(s)

Following this, the Ideation and Use-Case Definition phase, facilitated by HBL with active participation and content expertise from ECF and its selected partners, focused on translating broad needs into specific, actionable opportunities for GenAI. The objective, as ECF articulated, was to "create a minimal necessary understanding of the impact of AI tools... [and] help them identify use cases for AI tools that are clear, sharply defined, and very obviously beneficial." HBL facilitated a series of intensive strategic workshops, including a key session in June 2024 heavily involving ECF stakeholders. Here, structured ideation frameworks like "How Might We" (HMW) were employed, enabling ECF partners to deconstruct complex challenges from diverse user and stakeholder perspectives, guided by HBL's facilitation. Proposed use cases, largely surfaced by the ECF community, were then rigorously scrutinised by a joint HBL-ECF working group based on their potential Impact versus the Effort required. This prioritisation process, with HBL guiding the methodology and ECF providing the contextual expertise, resulted in a refined list of 5-7 validated GenAI use cases. These carefully selected challenges, co-owned by ECF, formed the core agenda for the hackathon.

Phase 4: Prototype & Test – The GenAI Hackathon

The Prototyping and Hackathon Execution phase in November 2024, designed and managed by HBL with ECF providing essential logistical and participant recruitment support, was where these use cases were brought to life. Its central aim, set by ECF and operationalized by HBL, was to "fine-tune requirements... identify the most likely suppliers, and create a running start for development..." while critically ensuring "maximal knowledge transfer from AI professionals to ECF ecosystem members." The two-day event in Brussels, logistically supported by ECF, convened approximately 100 participants. Teams, strategically blending ECF expertise with AI specialists under HBL's team formation guidance, were guided by HBL's 'Hacking Guide.' Participants utilized tools like the Lean Canvas and User Journey Map, benefited from scheduled check-ins with expert panelists (recruited by HBL and ECF), and had access to a dedicated Data Desk. This phase, led by HBL's facilitation, successfully generated concrete solution "blueprints," with teams evaluated based on criteria co-developed by HBL and ECF.

Phase 5 & 6: Pilot, Plan & Diffuse – From Concept to Reality

Finally, the Piloting, Evaluation, and Diffusion Planning phase was primarily driven by ECF, with HBL providing advisory support on the outputs. This stage transitioned the hackathon's outputs towards tangible implementation. Following the event, ECF initiated and managed a thorough selection process, involving its internal scoring mechanisms and detailed review of Proof of Concept (POC) proposals. While HBL was available for consultation, the decision-making rested with ECF. This meticulous process, led by ECF, ensured that only the most robust and viable projects—"Kotakima" (Challenge 1) and "Commons in Madrid" (Challenge 2)—were selected. These projects then received initial funding directly from ECF, formally commencing their journey from hackathon concepts to active development and eventual deployment within the ECF ecosystem, managed by ECF.

The Transformation: Beyond a Hackathon – A New Innovation Paradigm for ECF

The impact of Hack Belgium Labs' engagement with the European Climate Foundation extended far beyond the immediate outputs of the November 2024 hackathon, catalysing a profound and systemic shift within the organisation and its extensive network. While tangible AI solutions were a key deliverable, the broader transformation lay in the evolution of ECF’s organisational culture and its approach to innovation.

From the crucible of the hackathon emerged two promising projects: Kotakima (addressing Challenge 1: Combating Misinformation) and Commons in Madrid (addressing Challenge 2: Communications Strategy Calibration). These initiatives, born from collaborative effort, quickly progressed, receiving initial funding of approximately €50,000 each. This crucial seed investment set them on a path through Proof of Concept development, with further potential backing of up to €200,000 each earmarked for the creation of Minimum Viable Products, demonstrating a clear commitment to bringing these AI-powered tools to fruition.

However, the project's success was not solely measured in code and funding. A more fundamental metamorphosis occurred within the ECF ecosystem. As leadership aptly noted, "the hackathon achieved its goal of generating AI solutions to address problems within their ecosystem, and introduced a new way of working." This new way was characterised by a significantly enhanced innovation mindset. The entire journey, from the initial strategic workshops to the intensive hackathon and the rigorous post-event project selection, acted as a powerful catalyst, instilling a more proactive, experimental, and collaborative approach to leveraging AI for climate advocacy across both ECF internal teams and its grantee network.

This collaborative spirit fostered unprecedented ecosystem cohesion. What was once a collection of disparate entities began to see itself as an interconnected network with shared challenges and opportunities. The project effectively became "a tool for bringing together an ecosystem that doesn't think of itself as an ecosystem," fostering a newfound unity around the potential of GenAI. Furthermore, the process unearthed valuable human capital; critically, "the hackathon has not delivered on its initial goal [of just producing tools] but has also done something more - has also allowed you to identify the key change makers the champions within your ecosystem." These individuals are now pivotal in driving further AI adoption.

The strategic impact of this initiative also resonated externally. The project successfully showcased ECF's forward-thinking commitment to cutting-edge solutions, positively influencing perceptions among existing and potential funders. This resulted in a "strong innovation dynamic" and cultivated active engagement from multiple funders, who recognised the value and potential of ECF's AI-driven approach to climate action.

Perhaps the most profound and lasting outcome was the establishment of what ECF terms a "collective innovation process." The entire engagement served as a successful prototype for a novel way of working—one that strategically convenes grantees (the end-users with deep domain knowledge), technology suppliers (the AI experts), and funders (the enablers) to co-create targeted, impactful solutions. This realisation, that "the overall impact is this innovation change... let's say collaborative," marks a significant evolution in ECF’s operational strategy, offering a replicable model for tackling future complex challenges.

Differentiators & Key Success Factors


Hack Belgium Labs' success in this ambitious project stemmed from several core strengths:

  • Strategic Problem Framing & Structured Innovation: HBL's meticulous advisory phase and the structured hackathon environment, with its clearly defined challenges and guided ideation processes, ensured that efforts were focused on pertinent and high-impact areas. As an ECF leader observed, "the most important is defining the needs and then it's like the solution sort of you know we find a solution eventually but this process of weaning from like this whole big ecosystem..."

  • Facilitating Genuine Knowledge Transfer & Collaboration: The deliberate team composition (mixing ECF expertise with AI specialists) and the structured interactions with expert panels and pitch coaches, as outlined in the Hacking Guide, were central to the successful knowledge exchange and co-creation process.

  • Emphasis on Practical Application and Clear Outcomes: HBL’s guidance on prototyping (focusing on critical user touchpoints and key considerations like data privacy) and the clear success criteria provided to hackathon teams ensured a strong orientation towards practical, viable, and impactful solutions.

  • Adaptive Project Management & Transparency: HBL skillfully navigated the project's complexities, including the extended post-hackathon deliberation phase, maintaining momentum and transparently managing expectations to keep the overarching strategic goals on track.

  • Ecosystem-Centric Design Principles: Our approach recognised that sustainable technological adoption is built on a foundation of community, trust, and shared understanding. We focused on cultivating these elements alongside technical solutioning.

The Future: Scaling Collaborative AI for Greater Climate Impact

For ECF, this project is not an endpoint but a significant milestone on an ongoing journey. The "collective innovation process" prototyped through this engagement offers a powerful, replicable model for addressing other complex challenges within their network and potentially with other funder groups.