Gary Drenik

Across industries, artificial intelligence is entering a more disciplined phase. While the early cycle rewarded novelty, the current market exclusively rewards proof.

The procurement industry is entering a new phase of AI adoption. While technological advancements have dramatically improved workflow

Artificial intelligence has already transformed how machines process information. Generative AI and agentic systems can now reason, coordinate workflows, and automate increasingly complex digital tasks.

Using AI for Searching in InternetGetty Images - BlackJack3D When a global technology company was looking for a way to manage its narrative

When a global technology company was looking for a way to manage its narrative in the market, its CMO didn't start with a Google search. He asked an AI engine.

AI agents can change budgets, shift target audiences, personalize messages, and move to the next decision before anyone on the marketing team sees what happened.

Artificial intelligence is rapidly integrating into daily life and business, yet public confidence is paradoxically declining. Americans aren't rejecting AI but increasingly question society's ability to manage its profound consequences, particularly regarding job displacement and privacy. This unique trend sees AI adoption rise while trust falls, fueling widespread demand for accountability and human oversight. Surveys reveal strong bipartisan support for robust government regulation, treating AI similarly to industries like pharmaceuticals. The public seeks assurances that AI's economic benefits will be broadly shared. Earning public trust through transparency and addressing legitimate concerns is now crucial for AI's future.

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consumers and enterprises, content volume now significantly outpaces visibility, leading to governance issues like outdated or off-brand assets.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.