Wednesday, April 17, 2024 | 3:30–4:00 p.m.
Converting the AI Opportunity to Value With a Client-Centric Data Strategy
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Wednesday, April 17, 2024 | 3:30–4:00 p.m.
Speaker
Jason B. Miller
Head of Innovation
Ramboll
Jason is the Head of Innovation for Ramboll, a global architecture, engineering and consultancy company founded in Denmark in 1945. With a team of more than 18,000 experts, Ramboll is known for creating sustainable solutions across Buildings, Transport, Energy, Environment & Health, Water, Management Consulting, and Architecture & Landscape.
Jason leads Ramboll’s efforts to identify, validate, deliver, and scale new services and products aimed at resolving clients’ complex challenges, and creating a sustainable future where both people and nature flourish. In 2023, he played a pivotal role in formulating Ramboll’s AI strategy. This work involved assessing AI trends affecting the AEC industry and creating a robust plan to capture the opportunities. Foundational enablers of the strategy include development of the workforce of the future, innovative commercial models, maximizing the value of historical data, AI education and the ethical use of AI, reflecting the firm’s longstanding values.
Jason has more than 15 years of experience developing analytical and generative AI systems. His expertise spans natural language processing models for mining historical, technical data sets; computer vision models for vegetation typing and delineation; and, most recently, the use of OpenAI APIs to improve the efficiency of myriad tasks.
Jason B. Miller
Head of Innovation
Ramboll
ABOUT THE SESSION
Jason discussed building a corporate data strategy centered on clients to improve the odds of AI investments rapidly returning on initial investment and helping secure a broader corporate transformation, all while fostering client loyalty.
Developing and implementing a data strategy can be daunting, so this session explained how to break the process down into manageable steps to gain stakeholder buy-in, and how to identify priority pilot projects based on the strengths of existing data and staff expertise. Jason also discussed some of the key issues around data ownership and governance, which are necessary to ensure that future AI systems are secure, private and produce high-quality results, while keeping with corporate ethics.
Jason concluded by touching on how to ensure a data strategy is sufficiently flexible to keep up with emerging AI technologies and changing market needs.
