In our last Tech Blog, we explored how we turn complex claims data into clear sustainability evidence. Since then, we have noticed increasing discussions online about AI technology within company technology strategies, including interest in our own. This is why we will use this blog to go into more detail about Elucid’s AI Strategy, to transparently share how AI supports and strengthens our workflows.

 

At Elucid, AI Strategy is no longer a future consideration — it is part of how we work today. But for a company operating at the intersection of health, finance, and supply chains, adoption alone is not enough. 

Over the past months, we have been exploring how AI can improve productivity, strengthen our internal workflows, and support better decision-making. But the more embedded AI has become in our daily work, the clearer one thing becomes: the real challenge is not only how fast we adopt AI, but how responsibly we do it.

 

AI Adoption: Operationalizing AI with Purpose

 

Our AI adoption did not begin with a grand strategy document. It began with curiosity, which involved our internal teams running proof-of-concepts, discovering what was possible, and sharing what worked. What started as isolated experiments quickly became company-wide AI operationalization, and a fundamental shift in how we approach our work.

 

The results have been evident and clear. Productivity has increased across business operations, from field teams to back-office functions in finance and administration. Tasks that once took hours now take minutes. From documentation, to research, communication, and analysis, AI has touched all of them. For example, processing claims from PDF files has been transformed from a manual process taking several days to an automated task completed in a matter of hours. This frees our team members to focus on higher-value work that requires human judgment, care, and expertise.

 

But productivity is only one aspect of the story. As AI became embedded in our daily workflows, a more important question has emerged: how do we do this responsibly?

 

AI Governance: Responsible AI in Practice

 

The deeper our operationalization went, the clearer it became that technology alone is not enough. AI governance, meaning the policies, principles, and practices behind our Responsible AI approach, became just as important as the tools themselves.

 

For us, governance is not simply a checkbox exercise. It is a commitment to our partners, our clients, and our team. It means being intentional and thoughtful about which AI systems we trust, how data is handled, what decisions we allow AI to inform, and where human oversight remains non-negotiable.

 

This awareness has been one of the most valuable outcomes of our AI journey. It has made us better at asking the right questions before we adopt a new tool, not after.

 

The European AI Act has reinforced and aligned with this thinking. As a company operating in the health finance sector, we see European AI policy not as a constraint but as a framework that reflects our own values: transparency, accountability, and the protection of fundamental rights.

 

AI Expertise: Building a Vendor-Agnostic Stack and a Culture of Knowledge

 

Responsible AI governance shapes the way we select, deploy, and learn from AI tools. This happens at two levels at Elucid: our technology philosophy, and our internal knowledge community.

 

On the tools side, we maintain a deliberate, vendor-agnostic AI stack: every proprietary solution is balanced with an open source alternative. Tools like OpenWebUI, Opencode, and n8n sit alongside commercial products in our open AI ecosystem, not as compromises, but as strategic choices. Open source gives us transparency into how models and systems behave, flexibility to adapt them to our needs, and, crucially, freedom from vendor lock-in.

 

Vendor lock-in is a risk we take seriously. In a fast-moving field like AI, being tied to a single provider limits your ability to respond to better solutions, price changes, or regulatory shifts. By maintaining a mixed ecosystem, we stay flexible.

 

We also prioritize sovereign AI solutions, e.g. EU-compliant alternatives that guarantee alignment with GDPR and the AI Act. For a company working at the intersection of health and finance, this alignment is essential.

 

On the knowledge side, we have built an AI Guild, which functions as a cross-functional community of practice (equivalent to what many organizations call an AI Center of Excellence). The AI Guild brings together people from all departments to share knowledge, define AI usage policies, and ensure AI tools are used in a way that is safe, compliant, and genuinely valuable. It creates a dedicated space for discussion that cuts across team boundaries, and helps  us to collectively shape best practices and distribute the responsibility of AI adoption rather than concentrating it in a single team.

 

Looking Ahead

 

Our AI journey at Elucid is ongoing. What we have built so far is a foundation: a culture of thoughtful adoption, a responsible AI commitment, and a vendor-agnostic toolkit chosen with care. As AI continues to evolve, so will we: guided by the same principles that have brought us this far, we are scaling our impact by embedding data-driven insights across our operations, ensuring responsible governance, and delivering the dependable pipelines that establish trust at every level.

 

For Elucid, the most effective AI strategy is not the most aggressive one. It is the most responsible one that helps us work better while protecting the people, partners, and data at the center of our work.

 

Good Reads

• Why Data Governance Is the Secret to AI Agent Success — Strong data governance is what makes AI agents work
• The Case for Open AI Tooling: Why Developers Need Sovereignty — Why open tools are the sustainable alternative to closed systems
• The AI Governance Mirage — 72% of enterprises lack real AI governance controls
• Sovereign AI Infrastructure: A Blueprint for Escaping Vendor Lock-In — How to build AI independence from big tech providers