This podcast covers the August 2025 Consumer Snapshot report Prosper Insights & Analytics, a company specializing in consumer intent data and predictive analytics. This podcast summarizes findings from their ongoing monthly survey, which gathers information from over 7,500 US participants on a wide range of consumer behaviors, motivations, and future purchase plans. Highlights include consumer sentiment, spending intentions, and responses to economic pressures in August 2025, noting a slight increase in confidence despite persistent caution and a dip in overall happiness due to rising costs. The data also reveals shifts toward value-conscious shopping behaviors and provides insights for marketers and investors on navigating the evolving consumer landscape.

Banks, AI, and Consumer Trust: Bridging the Gap

The podcast covers an article by Gary Drenik for Forbes, that explores the current landscape of consumer financial needs and the banking sector's role in addressing them. It highlights that while consumers increasingly seek personalized financial guidance amid economic uncertainty, many banks are falling short in delivering this. The podcast emphasizes that banks are investing in AI to offer tailored advice through digital channels, recognizing the opportunity to strengthen customer relationships. However, a significant challenge remains: consumers, despite trusting their banks, harbor concerns about AI's use of their personal data. Therefore, the piece concludes that banks must prioritize secure and transparent AI solutions to bridge this trust gap and leverage AI's full potential for personalized financial services.

The Good Data Dividend: Fueling AI Success

This podcast covers an article from Forbes, authored by Gary Drenik of Prosper Insights & Analytics, centering on the critical importance of data integrity for businesses utilizing Artificial Intelligence. It highlights how flawed or unreliable data can lead to significant financial losses—averaging $443,550 for U.S. organizations in the past year—and misguided strategic decisions. Conversely, the podcast introduces the concept of a "good data dividend," illustrating that investing in robust information management systems can result in substantial revenue increases, with U.S. organizations reporting an average 10.8% rise. The podcast emphasizes that proactive data management strategies, such as eliminating redundant data, automating quality checks, and embedding security, are essential for maximizing AI's potential and gaining a competitive advantage.

This podcast  presents a summary of findings from Prosper Insights & Analytics' ongoing monthly survey of over 7,500 U.S. consumers. This July 2025 consumer snapshot focuses on consumer behavior, motivations, and future purchasing plans, utilizing unique question formats to gather emotional and psychological insights. The July 2025 snapshot highlights a modest increase in consumer confidence and sentiment, alongside a slight rise in spending intentions for categories like travel and home improvements. However, it also notes persistent inflation fatigue, particularly concerning gasoline prices, and a weak outlook for auto sales, indicating cautious spending habits. The report suggests that marketers should balance value and emotional engagement in their messaging, while investors should monitor growth in membership-based retail platforms like Amazon Prime and Walmart+.

AI Incident Management: The Indispensable Human Element.

The podcast covers an article by Gary Drenik from Forbes, discussing the crucial role of human empathy and judgment in AI-driven incident management. While AI excels at rapid detection and technical issue identification, it lacks the ability to provide business context or understand the "why" behind an incident. The podcast emphasizes that humans are essential for strategic decision-making, effective communication with stakeholders, and orchestrating a holistic response that considers regulatory, reputational, and client-specific implications. Ultimately, it argues that the most successful approach involves a partnership where AI augments human capabilities, allowing humans to focus on the invaluable aspects of contextual awareness and strategic leadership.

Customers Demand AI Security: Are You Listening?This podcast dives into an article by Gary Drenik for Forbes, highlighting the increasing consumer demand for AI security and responsible data practices. It emphasizes that customers are now making purchasing decisions based on their trust in how companies handle their data, with a significant percentage unwilling to engage with organizations they don't trust. The podcast further explores various AI-related concerns, such as the need for human oversight, transparency, and accuracy, alongside emerging security vulnerabilities in AI systems. Ultimately, the podcast argues that building trust through clear communication, ethical design, and adherence to evolving regulations is crucial for businesses utilizing AI, impacting both customer loyalty and financial success.

Kohl's Customer Guesswork: The Cost of Ignoring Data.

This podcast is based on the article, "Rethinking Retail: Kohl's Learns The Cost Of Customer Guesswork" by Gary Drenik for Forbes. It highlights Kohl's past strategic missteps in alienating its core customers by reducing coupon access. It emphasizes that financial data alone does not drive consumer behavior and that understanding customer motivations, psychographics, and future spending intentions is crucial for retail success. The podcast references Prosper Insights & Analytics' extensive consumer data, which clearly indicated Kohl's customers were financially stressed and value-driven, making the decision to limit coupons a significant oversight. The author argues that forward-looking, human-centric data is essential for retailers to avoid costly miscalculations and to build loyalty in a rapidly changing market. Ultimately, the article advocates for a shift from solely transactional analysis to a deeper comprehension of customer sentiment and behavior.

This podcast from Prosper Insights & Analytics presents findings from their June 2025 Consumer Snapshot, which gathers information from over 8,000 U.S. participants to understand consumer behavior and purchase intentions. The data indicates a cautiously improving yet still apprehensive consumer environment, with a slight increase in confidence but persistent inflation fatigue, particularly concerning dining out. Consumers are becoming more practical and realistic in their spending, prioritizing needs and coping with price increases by seeking sales and store brands. While major purchase plans remain flat, subscription services like Walmart+ and Amazon Prime continue to grow, highlighting a consumer focus on value and convenience amidst economic uncertainty.

AI, Privacy, and Data Protection Technologies.

This podcast discusses the critical issue of Generative AI's struggle with data privacy, highlighting how its reliance on vast datasets makes it vulnerable to privacy breaches.

Gary Drenik, a Forbes contributor and co-founder of Prosper Insights & Analytics, features insights from Kurt Rohloff of Duality Technologies, who emphasizes that current GenAIsystems lack sufficient privacy architecture for regulatory realities.

The podcast points to real-world concerns, such as the proposed ban of the DeepSeek AI platform due to data routing to China, and consumer apprehension regarding AI's use of their data. It advocates for Privacy-EnhancingTechnologies (PETs), specifically Fully Homomorphic Encryption (FHE), as a solution to process encrypted data without decryption, ensuring confidentiality and compliance in sensitive sectors like healthcare and finance.

Ultimately, the piece calls for a proactive, built-in approach to privacy in AI development rather than reactiveregulation.

The $100 Billion Illusion - Why Data, Not Hype, Will Drive AI ROI
This podcast covers a Forbes article by Gary Drenik that questions the current perception of a booming $100 billion generative AI market, suggesting it's more hype than reality for most companies. According to the author and expert Stephen Klein, many AI initiatives are costly experiments fueled by fear and the desire for the appearance of innovation, rather than solving real business problems or generating revenue. The core argument is thatthe true value in AI comes not from the technology itself, but from high-quality, human-provided data, such as zero-party data, which can accurately predict future outcomes. Examples are given of how this kind of data has been used to forecast retail revenues and inflation rates with high accuracy, contrasting with failed AI projects built on poor data. Ultimately, meaningful AI returns will be achieved by leveraging good data to address genuine challenges, rather than chasing the latest models.