Preparing Your Business

What every executive should know

1. 1. AI amplifies what's already there

   An IT consultant's oldest piece of advice is that a bad process automated is still a bad process, just faster. AI follows the same rule. If three people each handle a task their own way, AI will help all three do it faster, in three different ways, and the inconsistency that used to cost you an hour a week now costs you an hour a day.

   The businesses that get the most out of AI aren't the ones with the newest tools. They're the ones whose underlying operations were solid enough to actually benefit from being faster.

2. 2. Know who can access what, before AI can search all of it in seconds

   Most businesses have some version of permission sprawl: a shared drive where access was granted years ago and never revisited, a former employee's account that was disabled but never removed from a group, a folder everyone can open because narrowing it down once felt like more trouble than it was worth. None of that was a serious problem when finding a stray file required someone to manually dig through folders. It becomes a serious problem the moment an AI tool can summarize or surface everything a person has access to in a few seconds.

   Briefing 3's data-type risks, health, financial, privileged, confidential, don't change based on whether AI is involved. What changes is how fast an access mistake turns into an actual exposure. Before rolling out any AI tool with broad access to your files, do a basic pass: who has access to what, does that still make sense, and are former employees actually removed everywhere, not just disabled in one system.

3. 3. Written processes beat remembered ones

   If the real answer to "how do we handle this" is "ask Karen," there's nothing for AI to help with yet, because there's no process to draft from, only a person's memory. Trying to build an AI-assisted workflow around undocumented work usually surfaces this gap for the first time, which is uncomfortable, but it's also often the first time anyone's had a reason to actually write the process down.

   Businesses that go through this exercise usually end up with real, documented procedures they should have had years before AI ever came up, and those documents keep paying off long after the specific AI project that prompted them.

4. 4. Prepare people honestly, not just inform them

   Sending a memo announcing a new AI tool is informing people. Preparing them means explaining why, being straightforward about what it changes for their day-to-day work, and giving them a real way to ask questions, including the uncomfortable one about whether this affects job security. People who don't trust why a tool was introduced tend to either avoid it quietly or misuse it out of anxiety, neither of which shows up until well after rollout.

5. 5. Match your pace to your actual readiness

   A business with disorganized data and undocumented processes attempting an ambitious, company-wide AI rollout usually ends up worse off than a business with the same limitations running one modest, well-scoped pilot. Readiness gaps are easier to find and fix inside a small pilot than inside a rollout that's already touching every department.

   Competitive pressure to move fast is real, but a rushed rollout on top of an unready business tends to produce exactly the kind of incident that makes leadership pull back from AI entirely, which sets you further behind than a slower, deliberate start would have.

6. 6. Run a basic readiness check before you scale anything

   A few plain questions, rated honestly as low, medium, or high readiness, will tell you more than a formal audit: how well-organized is our data and access, how documented are the processes we'd actually apply AI to, how prepared is our team, and how current is our governance from Briefing 4. Low ratings aren't a reason to stop. They're a reason to fix that specific gap before scaling past a single pilot.

Action plan

This is the seventh in an eight-part series designed to give your leadership team a shared, working understanding of AI, without turning your business into a training exercise.