The simpler way to get your team to use AI

There are two ways to use AI to improve your team’s effectiveness: one simple and one complex.

The complex approach involves developing or purchasing specialized AI tools that integrate with existing databases and processes. This path typically requires significant investment, extensive compliance reviews, and coordination across multiple stakeholders.

The second approach consists of giving your employees access to general-purpose AI assistants (such as ChatGPT, Copilot, Gemini, or Claude) and training them to use them to improve their personal effectiveness. This method yields substantial productivity gains for knowledge workers with minimal infrastructure changes (we will see examples shortly).

While these two approaches complement each other, many organizations overlook the second one, missing huge effectiveness gains. This hesitation often stems from uncertainty about practical applications and concerns about adoption and potential errors or misuse. This short article explains how to deploy this simpler approach while avoiding most of these concerns.

Practical Applications for Immediate Impact

Let’s begin by looking at a few concrete ways AI assistants can help you and your team (we will cover implementation later; for now, let’s focus on the possibilities):

• Reducing Errors: AI can review communications not just for typos and similar mistakes but also for potential misunderstandings, likely objections, and missed action items and deadlines.

• Pre-empting Failure: AI assistants excel at pre-mortems: ask the AI to imagine scenarios where a meeting, sales call, or project might go wrong and suggest countermeasures.

• Improving Soft Skills: Writing clear emails is a core skill for every knowledge worker, yet it is seldom trained. The same applies to compiling reports, preparing proposals, and drafting presentations. AIs are not yet capable of completing these tasks autonomously, but they can provide feedback and opportunities for improvement.

Before we continue with a few more examples, let me highlight a key pattern. In all the examples above, AI is used not to replace a worker or automate a task but rather to help workers be more efficient, effective, or reliable, and to improve their skills. In 2025, I believe this is where the lowest-hanging fruit lies.ShareCopy

Let’s see a few more high-value applications:

• Decision Support: Helping analyze options against criteria, identify blind spots, and expand consideration of variables and consequences.

• Process Documentation: Creating and updating standard operating procedures, training materials, and process documentation.