Prosper Insights - Consumer Futures

The May 2026 Prosper Consumer Intentions Snapshot provides a comprehensive analysis of U.S. economic sentiment and purchasing behaviors following a period of high energy costs. The data reveals that while inflationary pressures on fuel and groceries persist, consumer confidence and overall mood have begun to stabilize compared to the previous month. Households are increasingly adopting disciplined shopping strategies, such as prioritizing store brands and utilizing membership platforms like Walmart Plus to maximize value. Despite making trade-offs in discretionary areas like travel, many individuals still intend to move forward with major investments in housing and vehicles. Ultimately, the podcast highlights a shift from initial market shock to a more practical and adaptive approach to spending.

AI Has A Data Problem - Causal Data May Solve ItDespite massive investments, most artificial intelligence initiatives fail because they rely on transactional data that only tracks historical patterns and past behaviors. These traditional datasets explain what happened but fail to capture the underlying intentions or emotions that drive future actions. To overcome this, organizations must shift toward causal data, which identifies the specific mechanisms and reasons behind decision-making. By focusing on upstream signals like consumer expectations and sentiment, models can predict market shifts months before they appear in sales records. This transition from correlation to causation makes AI systems more robust, transparent, and capable of delivering meaningful outcomes in changing environments. Ultimately, the future success of AI depends less on improving algorithms and more on integrating high-quality causal insights.

The AI Paradox: World-Class Algorithms and Second-Class DataThis podcast explores a significant disconnect in the tech industry, where businesses are aggressively increasing AI spending despite a sharp rise in project failures. This "AI Paradox" occurs because organizations frequently deploy sophisticated algorithms on a foundation of low-quality, unorganized, or insecure data. Beyond technical hurdles, the research highlights a lack of clear business objectives and widespread employee anxiety regarding data privacy and job security. To bridge this execution gap, leaders are advised to prioritize rigorous data governance and intentional, outcome-based strategies over simple financial investment.