Ljubljana: High Level Conference on AI — Moving from Ambition to Action
The High Level Conference on AI held in Ljubljana brought together policymakers, researchers, corporate leaders and civil society representatives to address a core challenge: how to translate ambitious AI strategies into concrete actions that deliver public benefit while managing risk. This article summarizes the conference agenda, highlights key themes and outlines practical recommendations for national and regional stakeholders seeking to move from strategy to implementation.
Conference objectives and structure
The Ljubljana conference was designed around three interlinked objectives: to align policy with technological realities, to catalyze public-private partnerships for deployment, and to set measurable milestones for ethical and safe AI adoption. Sessions combined panel discussions, technical briefings and workshop-style breakout groups that emphasized practical deliverables over abstract debate.
Key tracks
- Governance and regulation: creating adaptive frameworks that encourage innovation while protecting citizens.
- Ethics and accountability: operationalizing fairness, transparency and human oversight in AI systems.
- Workforce and education: reskilling, lifelong learning and building AI literacy across sectors.
- Deployment and public value: pilot projects, procurement practices and outcome-based metrics.
Main takeaways
Across sessions, several recurring themes emerged. First, stakeholders agreed that ambition without a realistic implementation pathway risks policy failure. Ambitious national AI strategies must be paired with implementation roadmaps that specify funding, timelines, responsible agencies and measurable outcomes.
Second, the conference stressed the need for governance models that are iterative and evidence-driven. Rather than one-size-fits-all regulation, participants advocated for modular rules, regulatory sandboxes and sector-specific guidance. This approach allows regulators to learn from pilots and scale successful practices while mitigating systemic risk.
Third, ethical principles must be translated into engineering and procurement practices. Delegates emphasized practical tools such as model cards, impact assessments, audit trails and procurement clauses that require explainability and post-deployment monitoring. Civil society participation in oversight structures was highlighted as essential for legitimacy and public trust.
Practical recommendations from Ljubljana
- Develop national implementation roadmaps tied to budget lines, KPIs and accountable public agencies.
- Establish multi-stakeholder regulatory sandboxes to test policy options and technical safeguards in controlled environments.
- Embed ethics into procurement: require impact assessments, transparency measures and continuous monitoring for publicly funded AI systems.
- Invest in workforce transition programs focused on digital skills, AI literacy and sector-specific upskilling initiatives.
- Promote public-private partnerships to scale pilots that demonstrate clear public value and measurable social outcomes.
Case studies and pilot projects
Several case studies presented at the conference illustrated how local governments and companies are moving from policy to practice. Examples included a municipal pilot using AI to optimize energy use in public buildings, a health system deploying AI-assisted diagnostics under strict audit requirements, and an education initiative that integrates AI tools into teacher training programs with ongoing evaluation.
Measuring success: metrics and accountability
Measuring impact was a central concern. Delegates proposed a layered KPI model: operational metrics (accuracy, latency, uptime), impact metrics (service access, cost savings, equity outcomes) and governance metrics (audit frequency, incident response times, compliance rates). Transparent reporting and third-party audits were recommended to ensure accountability and build trust.
Next steps and calls to action
The Ljubljana conference concluded with concrete calls to action: governments should move quickly to convert high-level AI plans into funded roadmaps; industry must adopt standardized transparency and accountability practices; academia and civil society should partner on independent evaluation frameworks; and international cooperation should focus on interoperability of standards and shared research infrastructure.
For practitioners, the path from ambition to action requires patience, cross-sector collaboration and iterative learning. Ljubljana demonstrated that with the right mix of ambition, operational detail and accountability, regions can harness AI to deliver public value while managing ethical and social risks. The conference set the stage for follow-up working groups and pilot-funded projects that will test the recommendations in real-world settings.
Conclusion
Ljubljana’s High Level Conference on AI was a crucial moment for reframing the conversation away from abstract targets toward actionable, measurable plans. The outcomes emphasized practical governance, ethical procurement, workforce readiness and robust measurement. For policymakers and practitioners committed to turning AI ambition into tangible outcomes, Ljubljana offered a roadmap grounded in collaboration and evidence-based action.
