There’s a new investigator pushing their way onto your team. You didn’t hire them, vet them or train them. I’m talking about AI.

While speed gets you to market, expertise is what makes the market believe you.​

The automation works, until it doesn’t, and the cases where it doesn’t are growing. Deterministic systems on their own were never going to handle that variance.

A successful checklist would prioritize core capabilities and workflows first, and save the “boring” tasks for later.

As adoption grows, many are discovering that operating AI is a far bigger job than deploying it.

The accuracy of your cybersecurity predictions will always be proportional to the quality and connectedness of the data behind them.

A good starting point is to go back through projects your team rejected in the past few years because the cost or time couldn’t be justified.

When the thing you bought produces output instead of enabling it, the seat is no longer the unit that matters. The unit of work is.