Havior

Accountability gets a bad reputation. In most organizations, it's code for blame, punishment, or micromanagement, and that misunderstanding is costing teams more than they realize.

Our CEO Krystyna Riley joined Ayo Lawrence on Episode 66 of his podcast to reframe it: accountability isn't about catching people doing something wrong. It's clarity. Clear expectations, visible commitments, follow-through, and feedback that helps people succeed.

In Havior's own research, only 13% of organizations report strong, clear accountability across their operations — the lowest excellence score in our entire study. That gap directly impacts ex*****on, results, and opportunities at every level.

The biggest missed insight? Accountability isn't something you demand. 𝗜𝘁'𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂 𝗱𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿. 𝗪𝗵𝗲𝗻 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗶𝘀 𝗶𝗻 𝗽𝗹𝗮𝗰𝗲, 𝗳𝗼𝗹𝗹𝗼𝘄-𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘁𝗵𝗲 𝗻𝗮𝘁𝘂𝗿𝗮𝗹 𝗼𝘂𝘁𝗰𝗼𝗺𝗲 — 𝗻𝗼𝘁 𝘁𝗵𝗲 𝗲𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻.

So here's something worth reflecting on: does your team know exactly what's expected of them, and do they hear about it before something goes wrong?

🎙️ Listen to Part 2 — link in the comments.

Most AI investments are failing. Not because of bad technology — because of 𝗯𝗮𝗱 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻.

Organizations pour budget into AI deployment and almost nothing into helping people actually change the way they work. 𝗘𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝗮𝗿𝗲 𝗵𝗮𝗻𝗱𝗲𝗱 𝗻𝗲𝘄 𝘁𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗹𝗲𝗳𝘁 𝘁𝗼 𝗳𝗶𝗴𝘂𝗿𝗲 𝗶𝘁 𝗼𝘂𝘁. 𝗦𝗼𝗺𝗲 𝗿𝗲𝘀𝗶𝘀𝘁. 𝗦𝗼𝗺𝗲 𝗰𝗼𝗺𝗽𝗹𝘆 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗲𝘃𝗲𝗿 𝗿𝗲𝗮𝗹𝗹𝘆 𝗮𝗱𝗼𝗽𝘁𝗶𝗻𝗴. 𝗣𝗶𝗹𝗼𝘁𝘀 𝘀𝘁𝗮𝗹𝗹.

Only 34% of organizations provide any resources to help employees use new AI tools. That number should concern every leader with an AI strategy.

The organizations getting real value from AI aren't winning on technology. They're winning on people.

There's a more hopeful version of this — where leaders are transparent, employees are supported, and AI becomes something teams actually want to use.

If that's the outcome you're after, let's talk.

𝘐𝘯𝘴𝘪𝘨𝘩𝘵𝘴 𝘧𝘳𝘰𝘮 "𝘕𝘦𝘸 𝘞𝘢𝘺𝘴 𝘰𝘧 𝘞𝘰𝘳𝘬𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘈𝘐," 𝘣𝘺 Brian Crowley-Koch PhD