WHO SHOULD ATTEND?

 Leadership, resilience, and building high-performing organizations

• 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: Competitive pressure, customer expectations, regulatory complexity
• Revenue performance gaps: Where sales teams are falling  short today
• What "sales-ready" means   now:   Speed to productivity, compliance confidence, consultative capability
• Business expectations from sales enablement: Faster onboarding, higher win  rates, consistent messaging, risk mitigation
• AI as a business lever: Accelerating capability development to meet commercial goals
• Critical readiness metrics that matter: Time-to-first-deal, quota attainment curves, customer engagement quality
• Investment thesis: Why AI in sales readiness deserves budget priority
• What we need from our organizations: Talent quality, manager capability, learning culture, HR-Sales partnership  

• Translating business expectations   into capability requirements: Redesigning sales roles and competency frameworks
• Workforce planning for the AI era: Talent acquisition, development, and retention strategy
• Change management: Building organizational readiness and overcoming resistance to AI adoption
• Performance management reimagined: Real-time coaching and development in an AI-enabled environment
• Building a culture of continuous learning and experimentation
• Strategic HR-Sales-Technology partnerships: Aligning on transformation priorities  

Getting Started - Evaluation & Readiness  

• 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  

AI Coaching for High-Stakes Clinical Conversations

Joint session with Johnson & Johnson MedTech 

• 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  

Scaling AI Adoption in Insurance (Joint session with SBI Life)

• 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  

Lessons from Practitioners 

• 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  

 Karan Singh- Mentalist 

Celebrating innovation and excellence in sales enablement