How Marc Geiger is Turning GenAI Into Real Legal Impact

In our Innovation Spotlight series, we interview innovation leaders about how they approach their jobs and how they’ve implemented and deployed Harvey.

In this edition, we chat with Marc Geiger, Director, Legal Operations & Business Technologies at Gleiss Lutz.

Marc’s responsibilities include operative office management, innovation and business projects, legal tech, process strategies and optimization, digitalization and automation, business intelligence, compliance tasks, relocations, as well as developing and assisting the IT department, particularly from a strategic standpoint.

What does innovation mean to you, and how does it shape your day-to-day work?

At Gleiss Lutz, innovation is part of how we work: aligning people, processes, data, and technology to deliver secure, scalable, and reliable outcomes for clients and the firm. My work covers operational firm organization, innovation and business projects, our legal tech portfolio, process strategies and optimization, digitization and automation, business intelligence, compliance-related initiatives, and crucially, the strategic development of our IT.

Day to day, that means setting priorities, adopting or building enterprise-grade platforms, standardizing workflows, and measuring what matters: quality, speed, and client value. We pilot, validate, and then adopt and scale what works. The objective is simple: free our lawyers to focus on strategic advice while we provide the technology, data, and processes.

What are you passionate about outside of work, and how do those passions influence your professional life?

Outside of work, I recharge by spending time with my family, especially my wife and my two kids, and getting outdoors for long walks with our dog. The balance that brings helps me show up at work with focus, patience, and sound judgment, particularly when matters are complex and fast-moving.

What excites you most about being an innovation leader today?

AI agents can now operate inside real legal workflows — they support work on client matters — while responsibility and decision making remain with lawyers. The opportunity is to close the gap between experiments and scaled impact by deploying task-specific agents that deliver measurable, reliable outcomes in live matters. This is no longer theoretical: We already run tailored agents for settlement comparisons and export-control monitoring, and we see strong momentum for integrated agents embedded across our internal systems.

What led you to select Harvey — and what are you hoping to achieve with it?

We selected Harvey because the platform combines broad legal capability, strong performance, and a secure European infrastructure — a critical requirement for a full-service firm.

We use Harvey for analysis, drafting, translations, and structured document work, all under robust data-protection expectations and mandatory human review. Our goal is to accelerate standardizable tasks so lawyers can focus on strategic advice, while maintaining quality through clear review requirements and transparent client communication about AI use and controls.

Where are you seeing the most adoption and impact so far — by practice area, region, or seniority level? Have any usage patterns surprised you?

Impact is strongest where tasks are repetitive, high-volume, or highly structured, particularly first drafts and structured analyses of larger document sets. Adoption is highest where standardized steps and well-rehearsed review paths exist, because that is where economics and risk management align best.

A key milestone has been expanding Harvey access to all trainee lawyers, embedding AI capabilities early in legal training, and fostering a new generation that pairs technological fluency with building their legal expertise.

What training or change management approaches have been most effective in driving adoption?

We keep the fire burning by pairing clear firm-wide guidelines with hands-on, mandatory training and fast, friendly support — so everyone uses the tech consistently and safely.

We regularly showcase real use cases and tangible results, check in with teams, and share best practices backed by practice area champions. Prompting challenges and "promoted prompts" in a firmwide newsletter also serve as further motivation. Our Legal Tech curriculum ties it all together with ongoing training sessions, prompt-engineering know-how, and governance.

Can you share 2–3 specific use cases where Harvey has made a meaningful impact?

Harvey provides great first-pass drafting, systematic document analysis, and translations. We are also seeing very good results for the analysis of company registry excerpts, drafting concise management briefings, and contract analysis and comparison.

With Harvey Vault, we securely leverage large document collections in live matters, for example in due diligences, antitrust, and insurance cases. In addition, we are increasingly using GenAI as a legal ideation partner to surface arguments, structures, and risk framings for lawyer review.

What does success look like to you with GenAI, and what outcomes or data points are you tracking?

On the one hand, success means sustained effort reduction in standardizable workstreams, with quality preserved through human-in-the-loop review and transparent client communication. We track various performance and adoption metrics, factoring in matter complexity, data quality, and verification needs.

On the other hand, success is a firm culture that embraces AI. We aim for best practices to be shared and prompting to become a core lawyer skillset, supported by continuous training and growing internal know-how.

As an early adopter of GenAI, what are 1–2 key lessons you've learned along the way — and what practical advice would you offer to organizations just beginning their own journey?

Invest early in governance and make it energizing: clear guidelines, regular training, and prompt support complemented by proactive check-ins with users and sharing of best practices by practice area. Pair this with continuous use case evaluation — keep what is reliable, iterate what shows promise, and retire what isn’t ready — so adoption stays safe, consistent, and positively reinforced.

Start where work is repetitive and standardized with established review paths; that is where the economics and risk profile align best. Maintain transparency with clients about AI usage, quality checks, and process steps to align expectations on confidentiality, accuracy, and documentation.

What do you think the most significant impact of GenAI will be on the legal industry of the future?

Generative AI is no longer an experiment but an essential part of our firm. This means embedding AI intelligently into legal workflows so lawyers deliver faster, more consistent, and smarter solutions — while strategic advice t, accountability, and trust remain firmly human. Future ready firms are those that embed AI into their legal workflows end to end – from research and analysis to structuring complex facts.