Continue to Learn Conference 2027 - Day 2

Golf course management is evolving faster than at any point in its history, yet many professionals still face resistance when introducing new ideas, tools or working practices. This session explores how leaders can successfully guide clubs, committees and teams through change, whether technological, environmental or organisational, without losing trust or momentum. Drawing on real-world industry experience, the session focuses on communication, evidence-based decision making and cultural leadership rather than products or brands. Attendees will leave with practical frameworks to help them justify innovation, manage stakeholder expectations and lead their teams confidently into the next era of golf course management.

Learning outcomes:

• Identify common organisational and cultural barriers that prevent new ideas and practices being adopted within golf clubs and course teams
• Apply practical communication techniques to explain change clearly and credibly to committees, boards and non-technical stakeholders
• Evaluate when and how evidence can be used effectively to support decision-making without overcomplicating discussions
• Recognise the leadership behaviours required to guide teams through periods of transition while maintaining trust and morale
• Develop a structured approach to introducing change, enabling more confident, considered adoption of new methods or ways of working

This combined session gives golf course managers a practical overview of how to choose, specify, and run robotic mowers that genuinely work on real courses rather than just in brochures. Demystifying the core technologies navigation methods, RTK positioning, communication options (LTE/LoRa/WiFi), and sensor suites (bump sensors, LiDAR, ultrasonic, AI cameras) so delegates understand how robots “see” and move, and what that means for their specific site.

Introducing the three pillars of success: choosing the right robots for different course areas (fairways, semi‑rough, approaches, surrounds, tees, rough), site‑specific planning with digital boundaries and adaptive course definition (summer/winter lines, step cut, no‑go zones), and proactive maintenance routines. Walk through a real‑world capacity‑planning case study, showing how to move beyond spec-sheet acreages to calculate realistic fleet sizes using complexity factors, overlap, mowing speed, travel and charging times, operating windows and a “real‑world filter” for peak growth periods.

Finally, explore infrastructure and operational excellence; path management to avoid rutting, strategic night/early‑morning scheduling to minimise golfer conflict, and simple “little and often” cleaning and inspection habits that keep machines reliable. Throughout, emphasis is placed on robotics being a tool for workforce preservation and course enhancement: by handing repetitive mowing to robots, clubs can redeploy skilled staff to agronomy, fine presentation and mentoring, and build a long‑term robotic mowing programme tailored to their own course.

Learning outcomes:

• Understand the core technologies that enable robotic mowers on golf courses
• Explain how to match different robotic mowing solutions to specific course areas
• Apply a structured, “real‑world” capacity‑planning method
• Describe how digital course definition and adaptive mowing setups can be used
• Identify the infrastructure, scheduling and proactive maintenance practices

This session explores how drones can be used to support golf course management, promotion and documentation. Participants will discover how aerial imagery can provide a fresh perspective on course activity, assist with mapping and measurement, record infrastructure such as irrigation and drainage, and support turf health monitoring through technologies such as NDVI imaging. The session will also introduce key legal considerations for safe and compliant drone use.

Learning outcomes:

• Recognise the practical uses of drones for golf course promotion, documentation and management
• Explain how aerial mapping and GPS-referenced imagery can support accurate measurement and future infrastructure detection
• Identify how drone imagery can help document irrigation, drainage and new build projects across a course
• Describe how NDVI and other aerial imaging approaches can support real-time turf health monitoring
• Understand the key legal and safety considerations involved in operating drones on or around a golf course

Artificial intelligence is no longer an emerging concept in turf management, it is an operational reality for a growing number of courses worldwide. But as adoption accelerates, so do the questions. How reliable are predictive models after a full season? How do you integrate AI outputs into daily planning without losing the expertise that matters most? And where is the technology heading next? This session continues the educational journey started at BTME 2026, taking a deeper look at how AI is being applied across the agronomic cycle, from pre-season planning through in-season adjustments to end-of-year analysis. We will explore how feedback loops between conditions, actions, and outcomes are becoming the foundation of smarter turf management, and how new capabilities in natural language processing, scenario modelling, and multi-source data integration are opening possibilities that did not exist 12 months ago.

Learning outcomes:

• The feedback loop in practice: how structured data transforms seasonal learning
• From metrics to context: AI that understands the "why" behind the numbers
• Scenario-based planning: testing agronomic decisions before committing resources
• Natural language and voice interfaces, lowering the barrier to data-driven management
• What the next generation of turf intelligence looks like and what it requires from greenkeepers

Most greenkeepers already know the familiar side of AI: chatbots, drafting and quick research. This session moves beyond the obvious to demonstrate practical, less-considered ways AI can streamline a greenkeeping operation. Attendees will explore imaging and branding, operational planning, survey creation, workflow automation and even simple custom code. Using examples from ChatGPT, Google Gemini and other tools, the session will connect each use case to time savings, better communication and measurable return on investment while remaining clear about where AI still has limitations.

Learning outcomes:

• Understand the practical capabilities and limitations of AI in a greenkeeping operation
• Identify less-obvious AI applications that can save time and improve operational workflows
• Apply foundational prompting principles to achieve clearer, more reliable results
• Evaluate where AI can deliver return on investment—and where human judgement remains essential