Gary Drenik

Artificial intelligence is revolutionizing content creation, making it faster and more personalized for marketing teams. However, this rapid acceleration has created a new challenge: brands are generating content faster than they can effectively manage, control, or ensure its consistency. With widespread AI adoption among consumers and enterprises, content volume now significantly outpaces visibility, leading to governance issues like outdated or off-brand assets. Traditional automation struggles with AI's complexity. The solution lies in establishing a "trusted system of record," such as Digital Asset Management (DAM), to provide a governed environment for approved content, metadata, and brand rules. This context-aware approach allows brands to scale personalization and activate content efficiently, turning governance into a competitive advantage rather than a liability.

Investment firms are adopting AI for efficiency, but using common data often leads to faster consensus rather than unique insights. Drawing an analogy to the Erie Canal, the article posits AI as the canal and data as the water; true competitive advantage stems from differentiated data, not just faster processing of widely available information. The key lies in "zero-party data"—forward-looking information on consumer expectations and intentions, collected consistently over time. This longitudinal data, exemplified by the New York Fed's surveys, provides upstream insights before transactions occur. Building such historical datasets requires significant commitment, making access to existing, well-established longitudinal data assets crucial. These unique data reservoirs, combined with AI, offer a strategic infrastructure that cannot be easily replicated, providing a lasting "technology moat" in the financial industry.

Streaming fundamentally altered the supply dynamics of television advertising. Traditional broadcast operated with scarcity. Prime-time inventory was limited.

Consumer AI is rapidly reshaping healthcare, with patients increasingly using tools like ChatGPT to research symptoms, treatments, and insurance before provider interactions. This trend, evidenced by millions of weekly health-related AI queries, creates a new operational reality where patient expectations often exceed current healthcare systems. While patients are becoming more informed, the disruption lies in healthcare's slow adaptation to this "AI-informed patient." Despite AI's growing use, most adults still prefer human healthcare, citing concerns about accuracy, transparency, and privacy. The solution involves "invisible" operational AI to streamline administrative tasks, organize information, and reduce clinician burden, allowing human providers to focus on judgment and trust. Healthcare organizations must evolve to meet these AI-empowered patients, integrating technology to support informed consumers without increasing staff burnout.

New research warns companies against using AI primarily for headcount reduction, arguing this "status quo bias" risks long-term growth by undermining crucial human capabilities like creativity and judgment. Instead, experts advocate for AI augmentation, which expands employee potential and fosters innovation. Employee surveys reveal significant concerns, with 31% fearing job loss and 25% distrusting AI, underscoring the need for trust and involvement in adoption. An automation-first approach can deplete leadership pipelines and lead to "workslop"—AI-generated content lacking substance, increasing human burden. Truly successful AI strategies will prioritize improving work quality, employee decision-making, and leadership development, transforming AI into a lasting competitive advantage by empowering people, not just replacing them.

Employee using AI In a difficult business environment, artificial intelligence can look like an obvious answer for executives seeking faster work, lower costs and new efficiencies.

New research indicates a significant shift in consumer perception, where the payment experience now dictates whether customers feel truly understood by a brand. Nuvei's "How America Pays" study reveals 57% of consumers choose payment methods based on purchase context, with many regularly switching. This fragmentation means businesses can no longer assume a single "preferred" payment, as preferences vary by age, device, and transaction type. Crucially, 49% expect their preferred option, and 37% will abandon a purchase if it's absent, highlighting revenue-denting consequences. Payments have become a vital trust signal; 55% trust the payment method more than the retailer, and 38% judge retailers based on available options. This trend extends to agentic commerce, where AI must still reflect customer payment preferences. Businesses must move beyond optimizing for conversion, recognizing that the payment experience is now where customer perceptions are formed and trust is built.

Agentic AI As the initial excitement around artificial intelligence settles, businesses are taking a closer look at how these tools perform in the real world.

AI answer engines are the new entry point for brand trust. Marketers have followed the north star of search engine optimization (SEO) for

Organizations have embraced enterprise AI with remarkable speed and aggressive investment. Preparing the data behind it, however, has proven to be far more complex.