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📺 Why Seattle Seahawks coaches rely on this analyst every game
An NFL analytics assistant describes his path from backup quarterback to a behind-the-scenes game-day support role. The account focuses on how football information is organized and how Microsoft Copilot in Excel is used to assist coaching decisions.
■ Background and Career Path
- Childhood NFL aspirations and a father’s role in Minnesota Vikings research and development
- Advice about the value of being a great assistant
■ Analytics and Technology in Football
- The art and science of football analytics
- Using Copilot in Excel to review plays, snap counts, and personnel
■ Role and Impact
- Serving as a right-hand resource for football information and digital tracking
- The significance of a Super Bowl ring and family connection
Suitable for viewers curious about NFL analytics roles, coaching support, or practical applications of Copilot in Excel. It offers a high-level overview of the responsibilities and tools involved without detailing specific methods or outcomes.
📺 2,000 people. One team. | Microsoft x Mercedes-AMG PETRONAS F1
We show how a Formula One team uses Microsoft 365, Azure Batch, GitHub Copilot, and Power BI to coordinate 2,000 people, run race simulations, accelerate development, and make data-driven decisions. The focus is on practical applications across communication, computing, development, and analytics.
■ Communication and collaboration
- Microsoft 365 for direct communication across the team
■ Simulation and data processing
- Azure Batch to scale computing nodes for race simulations
■ Development acceleration
- GitHub Copilot to increase development throughput
■ Data visualization and decision-making
- Power BI to combine manufacturing, finance, and car performance data
For those interested in how cloud, AI, and data tools are applied in high-stakes engineering environments, this provides a clear view of specific Microsoft services used in Formula One operations.
📺 Tech, labor, and token costs: the new AI math
📺 This company has more AI agents than employees
Andy Doyle, Chief People and Agent Officer at Kantar, explains how the market research company moved from a small Copilot pilot to an organization-wide AI transformation with more agents than employees. He shares the practical steps, challenges, and lessons from building an “agent factory” and combining people and agent management into one role.
■ AI Transformation at Kantar
- Rolling out Copilot to all 12,000 employees and reaching an 85% daily usage rate
- Moving from individual experimentation to enterprise-wide agent adoption
- Saving an average of two hours per person per week in the first year
■ The Agent Factory and Governance
- Managing 15,000 agents, with about 150 enterprise-level agents
- Categorizing agents into no-code, low-code, and pro-code tiers
- Centralizing successful agents while preserving grassroots innovation
■ People, Change, and Adoption
- Addressing employee anxiety and the fear of failure with AI
- Using internal influencers and “citizen agent builders” to drive adoption
- Redesigning HR work, including a people agent that handles 40% of queries without human intervention
■ Advice for Leaders
- Going all in on AI while focusing on human-centered change
- Building skills for experimentation and iteration rather than perfection
- Measuring ROI through productivity, engagement, and quality metrics
This episode is valuable for HR leaders, executives, and change managers who want a realistic, example-rich look at how a non-tech company is integrating AI agents into its workforce and what it takes to bring people along.
📺 The AI shift most companies didn't see coming
In this live Work Lab recording from the Copilot Summit, host Molly Wood speaks with Ali K Miller, founder and CEO of Open Machine, about how enterprises must rethink AI strategy as the technology shifts into a multi-agent era. Miller explains why treating AI as a simple productivity tool limits transformation, and outlines practical approaches for leadership, workforce upskilling, and frontier experimentation.
■ The Current AI Shift
- Moving from chatbots to reasoning models to multi-agent systems
- Cost pressures and the need for targeted experimentation rather than company-wide rollout
■ Leadership and Culture
- The importance of C-suite hands-on AI use and middle-manager modeling
- Moving beyond productivity metrics to measure growth, trust, and new business creation
- Addressing employee fear and building motivation through care and clear vision
■ Building Frontier Teams and Practical Steps
- Creating small, cross-functional frontier units with higher budgets and minimal layers
- Developing skills like high agency, curiosity, and systems thinking
- Immediate actions: build a company-wide context layer, make AI proactive, and stop typing
This session is for executives, AI leaders, and transformation teams seeking a realistic view of how to move from AI-curious to AI-first within their organizations.
📺 The sound of survival
Underwater noise from cargo ships poses a serious threat to the critically endangered Southern Resident killer whales in the Salish Sea. This video looks at how acoustic monitoring buoys and AI are being developed to detect whales in real time and help reduce ship noise.
■ The problem of underwater noise
- How ship noise interferes with orca communication and hunting
- Why real-time whale detection is essential
■ An autonomous detection system
- Buoys equipped with hydrophones and edge processors
- Cloud-based AI classification and automatic alerts to mariners
■ Conservation at scale
- Informing ships to slow down when whales are present
- Applying the same approach to marine habitats worldwide
This is a valuable resource for those interested in marine conservation, AI for environmental monitoring, and wildlife protection. Viewers will learn how technology can support endangered species recovery.
📺 Your job will never stop changing
📺 The future of work has no org chart | Microsoft Katy George
Host Molly Wood speaks with Katy George, Corporate Vice President of Workforce Transformation at Microsoft, about how organizations can move from AI pilots to genuine business transformation. The conversation explores the mindset shifts required, the importance of involving employees in redesigning work, and how to measure AI progress beyond simple productivity metrics.
- Why AI transformation is a continuous process, not a one-time change
- Moving from individual productivity to team-based transformation with programs like Camp Air
- Leadership and culture for the frontier firm: business-led, cross-disciplinary, and multigenerational teams
- Measuring AI success: linking adoption to behavior change and business outcomes, and the concept of capability add
Business leaders, HR professionals, and individual contributors will gain practical perspectives on how to approach AI adoption strategically and what practices help organizations move from experimentation to sustainable transformation.
📺 Nations rise on what gets built | Episode 5
This video explores the historical continuity of American infrastructure development, tracing its origins from George Washington's vision for the Potomac Canal to contemporary needs for digital connectivity and AI support. It highlights how past collaborative efforts set a precedent for modern community-first initiatives in building essential technological resources.
- Historical Context: Washington's role in establishing early infrastructure projects and the Mount Vernon Compact as a model for inter-state cooperation.
- Evolution of Infrastructure: The transition from canals and railroads to electricity grids, highways, and airports across generations.
- Modern Challenges: Addressing local concerns regarding data centers, including electricity costs, water usage, job creation, and tax implications.
- Community Engagement: Implementing rules that prioritize community needs and ensure fair contributions, mirroring historical diplomatic approaches.
Viewers gain insight into the strategic importance of balancing national progress with local community interests in the era of artificial intelligence.
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