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Most vegetation programs are built around fixed cycles, static assumptions, and annual planning rhythms.
While these structures create predictability, they often struggle to adapt as conditions change: from new pests and shifting growth patterns to data quality gaps and increasingly volatile storm behavior.
At Liberty Utilities, those limitations became clear as the operating environment grew more complex.
Rather than treating vegetation management as a repeating cycle, Liberty began evolving it into a learning system, one that uses data, validation, and iteration to get more accurate, more targeted, and more confident over time.
Through a joint AI- and satellite-based initiative with LiveEO, Liberty Utilities introduced new ways to observe vegetation conditions at scale, validate insights in the field, surface hidden data gaps, and refine decision thresholds. Each cycle of observation and validation strengthened confidence in the data and improved how effort was directed across the network.
Join us for a live masterclass exploring how Liberty Utilities is building a vegetation management program that doesn’t just keep pace with change, but gets smarter with every season, every validation cycle, and every operational decision.
Who Should Attend
- Utility vegetation managers and utility foresters
- Grid operations and reliability leaders
- Asset management and infrastructure planning teams
- TSO, DSO, and investor-owned utility leaders
- Innovation, analytics, and digital transformation teams
Details
Date: Tuesday, March 4, 2026
Time: 11:30 AM EST | 05:30 PM CET
What You’ll Learn
- Why static vegetation cycles struggle to keep pace with changing environmental and operational realities
- How Liberty Utilities used repeated validation and iteration to improve accuracy and confidence over time, rather than expecting perfection from day one
- How insights that expose data gaps can become catalysts for better asset models and stronger decisions
- How learning systems help utilities move from reactive adjustments to intentional, data-backed program evolution
- How continuous observation supports smarter prioritization, targeted inspections, and better use of limited field resources
- How Liberty’s joint AI and satellite initiative with LiveEO informed long-term thinking around risk, planning, and program maturity
- A live demonstration showing how satellite-based vegetation intelligence supports iterative improvement and learning-driven operations
Meet the Speakers
Jason Grossman, Manager of Vegetation Management, Liberty Utilities
Jason Grossman is a Utility Vegetation Manager at Liberty Utilities focused on sustainable, data-driven vegetation management. He is a published author and frequent industry speaker, with a strong commitment to environmental stewardship and pollinator habitats within utility corridors.
Nick Ferguson, Chief Evangelist at LiveEO
Nick Ferguson is the Chief Evangelist at LiveEO. He has global experience growing deep-tech geospatial companies that serve energy and transportation networks, and has held senior roles at several companies including NM Group, Trimble, and Enview, as well as founding and running a successful independent consulting business, GEO-CEO. Nick co-hosts the award-winning and CEU-accredited UVM Podcast, partnered with the UAA. He holds a BSc, MBA, is a Chartered Geographer and Fellow of the Royal Geographical Society.
Why Join This Session
Utilities are under growing pressure to deliver stronger reliability outcomes with limited resources, evolving environmental risks, and increasing scrutiny from leadership and regulators.
Vegetation programs that rely solely on static cycles and historical assumptions struggle to adapt.
This session shows how a learning-driven approach to vegetation management can unlock:
- Continuous improvement in decision quality
- Higher confidence in planning and prioritization
- Better alignment between field reality and program strategy
- Stronger long-term resilience without constant structural overhauls
Register Now
Join this session to learn how vegetation management can evolve from a repeating cycle into a system that learns, adapts, and improves every year:
