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August 13.2025
3 Minutes Read

Bridging the Gap in Analytics Leadership: Embracing AI Learning and Expertise

AI learning path concept with graph and professional in suit.

Nurturing a Data-Driven Culture in Leadership

In today's rapidly evolving technological landscape, organizations are increasingly leveraging analytics to drive decision-making. However, as Jack Phillips, CEO of the International Institute for Analytics (IIA), points out, the core challenge in analytics is not merely technical—it's fundamentally human. As businesses strive to make data-driven choices, nurturing a culture that embraces analytics at all levels becomes paramount.

The Shift from Supply to Demand in Analytics

Phillips highlights a notable change in how organizations view analytics. The traditional mindset focused on the supply side—concentrating on data procurement, quality control, and software deployment. In contrast, modern organizations are pivoting towards a demand-driven approach. This new perspective emphasizes collaboration with stakeholders across all business units, pushing them to adopt data-driven thinking that affects strategy and operations. Such a shift signifies that merely acquiring technical capabilities is insufficient; embedding a data-centric culture is essential for sustained success.

Redefining Leadership: Big L vs. small L

One of the more intriguing concepts presented by Phillips is the distinction between Big L and small L leadership. Big L leaders are the high-ranking officials, such as Chief Analytics Officers or Chief Data Officers, but Phillips stresses the importance of small L leaders—those managers and domain experts who function on the ground, advocating for analytics in their respective areas. This democratization of analytics leadership allows for a broader understanding of how data can influence everyday decisions within various functions like marketing, HR, and supply chain management.

Customizing Training for Effective Analytics Adoption

Even with strong leadership, the challenge of transforming an organization’s approach to analytics often lies in training. Phillips notes that effective training programs must address the specific needs and contexts of different industries. Customization is key; whether in healthcare or finance, industry-specific use cases make learning relevant and actionable. The IIA's DELTA Plus model, which forms part of the SAS Analytics Leadership Program, emphasizes not only technical knowledge but also the importance of organizational readiness and change management skills. This tailored approach ensures that learning resonates with participants and translates into tangible business outcomes.

The Reality of AI in Business

As the AI hype cycle captures media attention, Phillips urges caution regarding its role in guiding analytics strategy. While artificial intelligence is undoubtedly transformative, it must rest on a solid foundation of basic data analytics. Many organizations hastily seek out Chief AI Officers while overlooking the fundamental issues such as data quality that need addressing first. Phillips warns that as excitement builds around AI, businesses can lose focus on the foundational analytics processes that precede it, thereby diminishing the practical benefits of adopting these advanced technologies.

Looking Ahead: Analytics’ Evolving Role in Business

Understanding the future trajectory of analytics leadership is vital as organizations consider investments in AI and data initiatives. Phillips emphasizes the need for adaptive, resilient leaders who can navigate the complexities of this landscape. By fostering a culture that appreciates analytics at all levels and ensuring that education initiatives are tailored to context, enterprises can better prepare themselves for the evolving demands of data-driven decision making.

As we navigate this landscape, the role of analytics leaders will continue to evolve. It’s crucial for organizations to embrace and champion a culture of data-driven leadership, where insights lead to informed decisions across various business functions. When everyone becomes a small L leader, the collective intelligence of an organization can flourish, leading to innovative solutions and a competitive edge.

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09.27.2025

Teaching AI to Play Video Games: A Gateway to Adaptive Learning

Update Revolutionizing Learning: AI in Gaming As technology continues to evolve, the implementation of artificial intelligence (AI) has expanded far beyond traditional methods to the engaging world of video games. One fascinating area is the training of AI using reinforcement learning, where machines teach themselves to respond and adapt through trial and error. This innovative approach has significant implications not just for gaming but for various aspects of business and technology. Understanding Reinforcement Learning At the heart of many AI advancements lies reinforcement learning—a framework enabling AI systems to learn progressively from their environment. The concept is rooted in how real-life organisms learn; they perform actions and receive feedback that informs future behavior. In gaming, this translates to an AI agent continuously watching the game screen, deciphering actions, and deciding rapidly what to do based on its learned experiences. The Project: Training an AI Agent Recently, a pioneering project involved training an AI to play a video game in real-time. The primary goal was to make this AI agent responsive enough to emulate human players, capable of running, jumping, and reacting in milliseconds. To achieve this, thousands of game simulations were executed, allowing the AI to learn and adapt its strategies based on wins and losses. Equipped with SAS tools and programming languages like Python, the project transformed theoretical insights into practical applications. The AI honed its reaction time to an impressive speed of less than five milliseconds, showcasing its ability to not only process information instantaneously but also make strategic decisions on the fly. Business Implications of Adaptive AI The implications of this technological advancement are extensive, particularly in the business sector. Traditional analytics typically rely on historical data to forecast outcomes, while reinforcement learning offers the innovative advantage of adapting in real time. This shift can provide businesses with agility and responsiveness that are crucial in today’s fast-paced environment. Imagine an AI system capable of adjusting marketing strategies mid-campaign based on real-time user interactions! This adaptability can lead to more effective decision-making, optimizing operations, and ultimately enhancing customer experiences. AI as a Creative Force Beyond analytics, AI's role can extend to creativity, transforming the perception of AI from a strictly digital tool to an engaging co-creator. The gaming project highlighted the playful and imaginative potential of AI, showcasing its role not merely as a rigid statistical model but as a dynamic participant in larger creative processes. This perspective opens new possibilities—what if AI could collaborate with artists, musicians, and designers? Such collaborations could redefine boundaries and generate exciting advancements across various creative industries. Future Predictions: The Potential of Adaptive AI The trend of incorporating AI in gamified environments is just the beginning. The capabilities of such adaptive learning systems will be instrumental in developing smarter AI for more complex tasks. As businesses begin to adopt these technologies, they are likely to foster a culture of innovation within organizations. Future iterations of adaptive AI could revolutionize job training, customer service, health monitoring, and beyond, leading to highly personalized and efficient systems that cater to individual needs. Final Thoughts: Embracing AI Learning The transformation brought on by AI training methods heralds a new era in technology. As we explore these advanced learning pathways, it’s clear that the line between human creativity and machine intelligence is less defined than ever. For those who want to remain competitive in the ever-evolving tech landscape, embracing AI learning and its potential applications will be essential. To dive deeper into how AI is reshaping various sectors, stay updated and informed on the ongoing developments in artificial intelligence.

09.27.2025

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09.26.2025

How AI Learning Technologies Are Combatting Loneliness in Aging Populations

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