Team size: 12

What are the key projects that you have been involved in over the past twelve months?

Over the past year, my legal team at Polpharma has accelerated digital transformation and AI‑driven innovation to enhance legal operations, compliance and business partnering. We implemented an automated promotional materials review process, a copyrights database, the “Legal Zone” self‑service portal and e‑signatures, which together cut handling times, increased efficiency and improved internal client satisfaction. In parallel, we advanced AI and legal design: working with IT to deploy safe AI use, training users, and redesigning templates, procedures and guidance in clear, plain language.

We are launching LegalChat, an AI assistant integrated with our knowledge base and ticketing system. It resolves routine questions and auto‑creates Jira tickets when escalation is needed, providing 24/7 self‑service and freeing lawyers for higher‑value matters. Our Contract Repository (WEBCON) pilot centralises executed agreements, adds automated reminders and prepares AI‑enabled search/automation and future finance‑system integrations. In eML AI, we are embedding AI into the promotional review platform to automate classification, consistency checks and compliance pre‑screening—standardising checklists, improving data quality and accelerating multi‑level approvals.

Beyond point solutions, our Enterprise Legal Management (ELM) initiative is creating a single source of truth for contract lifecycle, compliance, governance and risk; leveraging LLMs for clause extraction and metadata, with alerts and e‑signature workflows to reduce manual workload and speed decisions. We are also developing Regulatory Change Monitoring to track multi‑jurisdiction legislative change, issue automated alerts, and generate impact analyses mapped to internal procedures. Adoption of DeepL has improved the quality and speed of bilingual documentation.

We complemented this with a training and business‑empowerment programme including ready‑to‑use contract templates, legal/compliance training, risk analysis and extended powers of attorney, reducing lawyer involvement in repeatable processes.

Alongside operations, we supported the Polpharma Group restructuring. I led the legal team end‑to‑end—setting strategy, coordinating closely with business, advising on alternatives in administrative procedures, planning timelines and assessing legal implications, ensuring continuity of essential‑medicine manufacturing and seamless transfer of permits and administrative decisions.

What are the key trends that in-house counsel should be monitoring in 2026?

Rapid adoption of GenAI/agentic AI across CLM, compliance and diligence; success requires “human‑in‑the‑loop,” algorithm auditability, bias testing and governance aligned with the AI Act/GDPR; greater centralisation (Centers of competence, managed legal services), workflow and routine tasks automation, with performance measured through KPIs and SLAs; intensified supply‑chain due diligence, ESG reporting, and compliance in digital health, data governance and cybersecurity; and data‑driven panel management, active fee negotiations and selective in‑sourcing with AI augmentation to maintain efficiency and quality.

What do you think are the most important attributes for a modern in-house counsel to possess?

Business partnering involves linking legal advice directly to business outcomes, ensuring that legal strategies support organisational goals. It also requires strong technological literacy and adaptability to implement innovation and effectively manage change. Additionally, regulatory foresight is essential to anticipate developments in areas such as AI, ESG, and NIS2, allowing organisations to remain proactive rather than reactive. Finally, resilience combined with ethical integrity is crucial to sustain compliance standards while building trust and transparency with stakeholders.

AI is increasingly being integrated into legal teams to maximise efficiency. How can in-house counsel ensure the successful incorporation of these tools without compromising the human element?

Adopting a hybrid operating model allows AI to handle repeatable tasks such as classification, metadata management, clause comparison, and horizon-scanning, while strategic judgment remains with experienced legal counsel. This approach should be supported by role-based access controls, privacy-by-design principles, and robust model governance, including monitoring for accuracy and bias as well as establishing fallback rules. It also requires user training and post-deployment metrics to assess performance, such as turnaround time, error rates, rework, and user satisfaction. Implementing AI in line with the EU Artificial Intelligence Act and the General Data Protection Regulation ensures transparency and strong data security. Overall, this model augments human decision-making and enables lawyers to focus on higher-impact risk management and delivering greater business value.