Copenhagen, Capital Region of Denmark, Denmark
Data and AI executive with ~20 years experience who built the data and AI capabilities served at scale at Novo Nordisk. I bring in depth expertise of setting strategic goals and how to achieve them. Technology and architecture, robust process framework and operating model. Identifying and documenting strategic sources of data, setting a global organisation up for success, including talent and performance management, as well as enabling a thriving engineering culture. Passionate about how data and ai might transform organisations, improve our way of living, and accelerate creation of value. Married to Line and a family father of 4 fantastic kids. We live in Copenhagen.
Accordance AI Engineering is an advisory and engineering firm helping organisations navigate the real, hard work of scaling AI, with genuine depth, close partnership, and a commitment to creating lasting value. I founded Accordance to share what 20 years of building AI and data capabilities inside one of the world's most complex industries taught me: that AI at enterprise scale is not a technology problem. It is a strategic, organisational, and data challenge. At Accordance, I work alongside CxOs and leadership teams to close the gap between AI ambition and execution, from strategic clarity and data foundations, through to engineering and organisational readiness. If you are working through these challenges, I would love to connect.
Independent Executive Advisor. Scaling Data & AI in Large Enterprises Most AI initiatives fail; not because the technology doesn't work, but because organisations lack strategic clarity, data maturity, and organisational readiness. I help executive teams and boards solve this. Drawing on nearly two decades scaling Data & AI at Novo Nordisk - from 5 people to 300+ - delivering 500M+ DKK in annual quantified business value I advise leaders navigating the shift from AI experimentation to enterprise-scale value creation. My advisory work is built around a practitioner-led framework covering five interdependent dimensions, addressed sequentially: → Strategic Objective: Defining where AI creates material impact: revenue, cost, or asset optimisation. Distinguishing broad horizontal enablement from vertical transformation of significant importance. → Data Strategy: Mapping strategic data sources, establishing governance, and building the data foundation AI requires to scale. → Technology & Platform Architecture: Making deliberate "one-way door" technology choices that simplify rather than fragment. Platform thinking over scattered initiatives. → Processes & Operating Model: Designing risk-based, repeatable delivery from ideation through production, with portfolio discipline and clear gate criteria. → People & Organisation: Building engineering culture, scaling teams, and creating true business-IT partnerships that sustain transformation. I work with organisations across regulated industries, pharma, biotech, life sciences, and beyond, where compliance (GxP, GDPR, SOX, AI Act), data complexity, and organisational scale make AI execution uniquely challenging. Open to advisory engagements where I can bring this playbook to a mission-driven organisation
Results: - Served +50.000 users - Won the Databricks 2025 healthcare & lifescience award - Setup a global platform engineering organisation (100 engineers) across orchestration, data, ai, analytics, compute, security, and governance. - managed a global platform budget of 300 mDKK - Completed platform architecture, user journeys, roadmap, playbooks - Scaled global data and ai platform in months - Vendor and cost optimisation - Build a brand (datacraft) Responsible for Platform Engineering in Global Data & AI, Interim Head of Global Data & AI Architecture. In this role I am responsible for building data, bi, ai and advanced analytics capabilities scaling data and ai in Novo Nordisk. Solution spans across hyperscalers, including AWS and Microsoft Azure as well as integration to on premise solutions such as Gefion. Driving engineering culture, software development, and solutions that allows the business to scale data and ai. The organisation is divided amongst locations in India, US, Poland & Denmark and is organised in engineering teams where engineers, scientists, and business analyst works together. Leadership * Democratising Data * Enterprise Enablement of Data & Analytics * AI/ML * Data Lake * Data Mesh * CI/CD * Software Engineering * Orchestration * Data Science * Data Engineering * Public Cloud * AWS * MS Azure* Better Tools and Optimised Processes.
Results: - Enabled global data and ai strategy for R&D - Laid the fundament for AI agents in clinical trial data - Scaled GenAI to 35.000 users (GPT models) - Defined global data and ai architecture - Merged and managed a global organisation of data, ai, machine learning and business intelligence engineers and consultants - Redesigned organisation and operating model - Managed portfolio of ai and analytics use cases - Created value of +500 mDKK through use case execution Role: VP and global head of business intelligence, data management, ai, machine learning and advanced analytics in Data, Digital & IT. Technology offerings spanning across MS Azure and AWS, serving the enterprise. In this role i merged two teams in to an organisation of 300 platform, cloud, data, ml, bi engineers, data scientists, and data & ai business partners. Established a hub of skilled engineers in Poland. Global responsibility. Budget, strategy, execution & architecture, engineering culture, and operating model.
Results: - Established and executed a portfolio of hundreds data and ai use cases driving tangible business impact - Scaled data, ai, advanced statistics, and machine learning capabilities - Build data lake, cloud data warehouse, high intensive compute, and analytical platform on AWS - Introduced cloud fluency training for the organisation - Implemented machine learning algorithms on production lines, build solutions to capture patient data, enabling advanced analytics for commercial execution, adhering to regulation and ethics, enabled in silico drug discovery - Enabled streaming analytics in production Role: I established a global data, ai, & analytics organisation from a team of five colleagues to a global organisation with +100 people spanning data platform, data management, and ai centre of excellence to drive process optimisation and innovation using data, ai, and machine learning in a heavily regulated environment. Solutions: Enterprise Data Lake, enterprise data mesh, and Enterprise AI platform, capabilities and processes across four locations (US, DK, & IN). Solutions broadly adopted across the enterprise. Solutions based on AWS (cloud native, everything as code, server less infrastructure). Processes: CI/CD, Regulated environments, Scrum. People: Global training, Innovation, learning and development, strategic anchoring and adoption of use cases to value supporting the digital transformation.
IT Security and Internal Controls Financial statement audit ERP process audit