Before diving into implementation, understand this fundamental truth: AI can define emotions, but it doesn't know what they feel like.

When AI triggers an emotion in someone, it won't understand how to deal with it. That's when human intuition: emotional intelligence, comes into play.

​This is why certain aspects of your business should remain human-driven, especially in service businesses where client relationships matter. AI excels at tasks like finance (numbers, computations, data processing) but struggles with nuanced human interactions that require reading between the lines.
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​The people doing the daily tasks can tell you:

When someone says "this part sucks," don't take it personally. Listen, because that becomes a huge opportunity where AI could potentially help.

Notice how we're still not putting any new tech anywhere? You're taking a step back to understand what you're working with first.

​Look at your current technology setup and identify:

Why this matters: If you have tech overlap, you don't want to add more complexity on top of an already complicated setup. Before adding AI tools, see if you can remove some existing tech to streamline your stack.

Don't rely on what marketing departments tell you about what tools can do. Talk to your team, the people who use these tools daily, because they'll give you the real story about capabilities and limitations.

Now comes the actual AI tool evaluation. With your process mapped and tech stack understood, you can identify specific opportunities where AI makes sense.

Real-world example: When I was a senior consultant for Salesforce, I spent hours in meetings taking notes, tracking action items, then manually transferring everything to our task management system. I'd assign tasks, estimate timelines, and write detailed descriptions so everyone knew exactly what to do.

​Today's AI note-taking apps can:

The Ninja Pro Tip: During meetings, naturally dictate assignments by saying "So-and-so will complete this task." The AI picks up these cues and automatically assigns tasks to the right people.

This type of implementation would have cut my post-meeting workflow from hours to minutes, while letting me stay fully present during actual meetings instead of multitasking between listening and note-taking.

​Look for these low-hanging fruit opportunities—tasks that involve creating text, managing data, or organizing information that doesn't require human intuition.

This is the most undervalued skill in business, and it determines whether your AI implementation succeeds or becomes expensive shelf-ware.

​I can build you a system that saves $20,000 a year in employee time, but if no one on your team actually uses it, you've wasted money and created frustration instead of efficiency.

The key question: How do you get your team emotionally invested in the outcome?

Your employees need to see how AI implementation will make their lives easier. They need to get excited about the prospect of going home an hour earlier or focusing on work they actually enjoy instead of repetitive tasks.

Here's the reality: If you implement AI correctly, you can turn 8-hour workdays into 6-hour workdays by eliminating time-wasting manual tasks. Whether you give employees that time back or redirect it to higher-value work is up to you, but they need to see the personal benefit to buy in.

Without positive emotional investment from your team, even perfectly designed AI systems will fail. I've seen amazing implementations sit unused because businesses skipped the human element of change management.