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Leading teams through complexity, building resilience, and making high-stakes decisions—lessons for AI-era sales leadership  

• Sales Readiness Expectations & Performance Outcomes
• Market realities driving change
•  Revenue performance gaps
•  What "sales-ready" means now
•  Business expectations from sales enablement
•  AI as a business lever
•  Critical readiness metrics that matter
•   Investment  thesis
•  What we need from our organizations

•  Translating business expectations into capability requirements
•  Workforce planning for the AI era 
•  Change management 
•  Performance management reimagined 
•  Building a culture of continuous learning and experimentation  
•  Strategic HR-Sales-Technology partnerships 

Understanding AI capabilities: What can it actually do? 

Use cases and applications across different sales contexts 

Organizational readiness: People, process, technology 

Key questions to answer before starting 

Setting realistic expectations and timelines  

Creating effective AI roleplay scenarios and simulations 

Personalization at scale: Adaptive learning paths based on performance data 

Quality of AI feedback: What makes it developmental vs. generic 

Gamification and engagement mechanics in AI platforms 

Connecting AI practice to real-world sales outcomes  

Using AI insights and data to guide coaching conversations 

When to intervene: Human judgment in AI-driven learning 

Manager enablement: What training do managers need for AI tools? 

Balancing AI automation with human connection and peer learning 

Making coaching sustainable with AI support  

The challenge: Training distributed advisors at massive scale 

Identifying the right use cases for AI intervention 

Change management strategy: Overcoming initial resistance 

Rollout approach: Pilot → regional expansion → national deployment 

Achieving 80%+ adoption rates: What worked and what didn't 

Manager enablement: Turning field managers into AI champions 

Metrics that mattered: From engagement to business impact  

What we wish we knew before starting: Honest reflections 

Biggest surprises (good and bad) post-implementation 

Driving Adoption: What actually worked with reps and managers 

Pilot strategies: How we tested before scaling 

Content creation realities: Effort, resources, quality control 

Measuring what matters: Metrics that drove decisions 

Course corrections: What we'd do differently  

Celebrating innovation and excellence in sales enablement