AI Innovation Leadership

Leading the integration of AI and ML technologies to drive business value.

Generative AI Practice at Tapestry

As the Sr. Director of Product Management leading Tapestry's Generative AI practice, I spearheaded initiatives to integrate AI across the organization's house of brands (Coach, Kate Spade, Stuart Weitzman). My approach focused on practical applications that delivered tangible business value while maintaining brand integrity.

AI-Enhanced Customer Experiences
Transforming how customers interact with brands
  • Implemented AI-powered product recommendations that increased AOV by 15%
  • Developed conversational shopping assistants to guide purchase decisions
  • Created personalized post-purchase experiences based on customer behavior
Operational Efficiency
Streamlining processes with AI automation
  • Reduced customer service resolution time by 35% with AI-assisted support
  • Automated content generation for product descriptions and marketing materials
  • Implemented predictive inventory management to optimize stock levels
Strategic Decision Making
Leveraging AI for better business insights
  • Developed AI models to predict emerging fashion trends
  • Created dashboards that surfaced actionable insights from complex data
  • Implemented scenario planning tools to evaluate strategic options
Innovation Acceleration
Using AI to drive creative solutions
  • Led AI-powered design exploration for new product development
  • Created rapid prototyping workflows using generative AI
  • Established an AI innovation lab to test emerging technologies

AI Implementation Framework

Through my experience leading AI initiatives, I've developed a framework for successfully implementing AI in enterprise environments:

  1. Value Identification

    Start with clear business objectives and identify specific problems AI can solve.

  2. Data Strategy

    Assess data availability, quality, and governance requirements.

  3. Capability Building

    Develop internal expertise and partner with external specialists as needed.

  4. Pilot & Prove

    Start with high-impact, low-risk use cases to demonstrate value.

  5. Scale & Integrate

    Expand successful pilots and integrate into core business processes.

  6. Ethical Governance

    Establish frameworks for responsible AI use and ongoing monitoring.

Future of AI in Product Management

I believe AI will transform product management in several key ways:

  • Enhanced customer understanding: AI will enable deeper insights into customer needs and behaviors, allowing for more precise problem identification.
  • Accelerated experimentation: AI tools will enable rapid testing of hypotheses and faster iteration cycles.
  • Personalization at scale: AI will enable truly personalized product experiences tailored to individual user needs and contexts.
  • Augmented decision-making: AI will help product managers analyze complex data sets and identify patterns that inform better strategic decisions.
"The most successful product leaders won't be replaced by AI, but they will be those who effectively leverage AI to amplify their teams' capabilities and deliver exceptional customer value."