The Adoption Edge
Practical insights on data adoption, analytics enablement, and AI governance - written for the leaders responsible for turning data investment into business results.
You’ve likely had this moment.
You present a well-articulated data and analytics strategy. The roadmap is solid. The architecture is modern. The tooling is funded. Leadership nods. The initiative mov...
You did everything right.
Your team delivered the dashboard on time. The pipelines are stable. The definitions are clean. Stakeholders nodded in the demo.
And then… nothing changed.
The same meetin...
You’ve seen this play out.
A new dashboard launches. It’s clean, fast, and technically sound. The team celebrates. Leadership nods. For a moment, it feels like progress.
Then… nothing changes.
The ...
You’ve seen the demo.
Someone types a question into a GenAI tool and gets a clean answer in seconds. No dashboard navigation. No SQL. No waiting on the data team.
It feels like the promise of self-s...
Leadership Is Stuck in Pilot Mode
You’ve seen this play out.
A business unit launches a promising AI use case. Maybe it’s a forecasting model, a GenAI assistant, or a pricing optimization tool. It w...
The Overlooked Frontier of AI Risk
Summary: The governance of training data is fast emerging as one of the most critical - and least understood - dimensions of artificial intelligence (AI) risk. Whil...
Regulating Claims, Not Code
Artificial intelligence regulation in the United States is entering a more pragmatic phase. Rather than attempting to define how AI systems must be built, federal regulato...
Navigating the Global Patchwork of AI Regulation
Artificial intelligence governance has entered a decisive phase. By 2026, the debate is no longer whether AI should be regulated, but how regulation s...
Artificial intelligence governance has spent much of the past decade stuck in a familiar place. Organizations publish ethics principles, adopt high-level frameworks, and announce commitments to respon...
How Model Alignment Strategies Are Evolving
Summary
As AI systems become more capable, traditional rule-based safety approaches are reaching their limits. In response, leading AI developers are adopti...
Closing the Gap Between AI Capability and Oversight
Summary
The rapid advance of foundation and frontier AI models is outpacing the capacity of existing governance systems. As international policy bod...
California has emerged as the first U.S. state to enact a transparency-focused law governing the development of frontier artificial intelligence systems. Senate Bill 53 - the Transparency in Fronti...