Organizations are making one of the biggest decisions about AI without realizing it. Every time we automate a process… Every time we deploy a generative AI copilot… Every time we trust an AI recommendation… We’re answering a question that most leadership teams have never actually discussed. Who — or what — should be making the…
Ransomware remains one of the most disruptive cyber threats organizations face. Companies have strengthened their cyber defenses over the years, but attackers in 2026 have become faster, more targeted, and increasingly reliant on AI, forcing the need for a change in how organizations approach cyber resilience. From the rise of AI-enabled attacks and extortion-only campaigns…
Artificial intelligence is rapidly reshaping the business landscape. It can summarize meetings, generate presentations, personalize communications, analyze customer behavior, automate repetitive tasks and uncover insights that once took teams days to uncover. Organizations that embrace AI thoughtfully will almost certainly be more productive than those that don’t. That’s the good news. The challenge is that…
Sometimes, the demo works but the actual rollout doesn’t. An agent on one task is reliable, but run several against the same codebase and the results stop adding up: they rebuild what a neighbor just shipped, make conflicting changes to the same file, take an approach another agent ruled out an hour earlier. The gap…
When several agents work the same codebase, the way their assignments are divided determines the outcome. Done well, their merges fit together and align to the team goals. But not done well and you get a series of changes that each look right on their own but don’t add up. How you split the work…
The call usually opens with praise. The AI feature shipped on time, users love it and engagement charts are pointing the right way. Then finance closes the quarter, and the feature everyone celebrates loses money on every single request. That is the part the CTO called about. I get some version of this call every…
At their deepest level, LLMs are still a kind of magic. Even the developers who build them find them to be, channeling Winston Churchill, “a riddle, wrapped in a mystery, inside an enigma.” That’s why everyone working with LLMs in their enterprise stack needs a way to peer into the dark mass of weights to…
For a long time, the role of the chief information officer has been defined around systems, architecture and innovation. The expectation was straightforward: ensure uptime, modernize infrastructure and occasionally introduce transformative technologies. From where I sit, the most important technology decisions are no longer purely technical. They are capital allocation decisions. Every architecture choice, platform…
Brands like Snickers, M&M’s, and Twix are familiar to most consumers, but Mars Inc. doesn’t just produce snacks. The family-owned company, with a revenue of approximately $65 billion, is also one of the largest manufacturers of pet food and ready meals, and its more than 100 production facilities operate around the clock. Of course, this…
A fraud model looks at an insurance claim and returns a score of 0.23: low risk. A SHAP explanation lays out exactly why: no prior claims, a modest claim value, an unremarkable claimant profile. A human adjuster reads the explanation, agrees with it and signs off. Every box that explainable AI asks us to check…