Spring 2026

Features

The AI Stack: What Decision Makers Need to Know

Organizations are at vastly different stages with respect to their AI stacks, which is not surprising given the rapid pace of advancement in this field within the past few years. Those that are just getting into AI may have experimented but not gone beyond the parameters of their existing enterprise stack. Others may have elements of the AI stack in place but need to expand it in order to build out AI applications.

The Multimodal World of Enterprise AI

Multimodal applications of AI are gaining credence throughout the enterprise at increasingly rapid rates—and for good reason. Firstly, they come close to realizing the full potential of foundation models and large language models (LLMs) which, by default, are multimodal.

Vibe Coding: When Intent Becomes the Interface

For the last 40 years, the history of enterprise software has been a history of translation. Business leaders had intent; engineers had the syntax. The gap between them was bridged by requirement documents, product managers, Jira tickets, and the inevitable friction of misinterpretation.

Industry Voices

The Build vs. Buy Moment That Will Define Enterprise AI in 2026

Untapped AI potential was a defining theme of 2025, reminding business leaders that expectations for new technology often outrun reality, especially in the early stages of implementation. While the C-suite looked to AI as a near-term answer to cost pressure, teams responsible for implementation faced a very different set of constraints on the ground.

AI Reflections

Materials Science and AI

The ironies of modern technology abound. The more important, relevant, and impactful a new technology is, the more entrenched the fundamentals of that discipline are to the history of science.

Crossing the AI Chasm

Why Data Products Break the Binary

In my previous column, I wrote about the mental health AI industry heading toward a chasm between enthusiastic early adopters in research labs and the overwhelmed humans who have to use AI that isn't making them feel better.

Legal Intelligence

AI Governance in the Age of Agentic AI

The rapid maturation of agentic AI systems represents a fundamental shift in how organizations must approach AI governance. Traditional governance frameworks were designed for AI systems that analyze data and generate recommendations for human review. Agentic AI operates differently.