How to implement AI in your businesses

By: Matt Whittle, Edited by: Rebecca Munday

Published: April 15, 2025

Many have taken to using "artificial intelligence" as a catch-all term for anything related to software or technology, but employing it in your business requires clear identification of its applications, objectives, benefits, and potential drawbacks.

Discover a step-by-step process to implement artificial intelligence (AI) in your business, including details on setting goals, delivering actionable outcomes, and assessing its effectiveness.

Steps to implement AI in your business

1. Familiarize yourself and your team with AI

Before implementing AI in your business, its important to know that AI cannot be employed as a one-size-fits-all solution to whatever business challenges you may face.

Using AI can greatly improve your efficiency and services, but doing so requires that you and your team learn this growing technology's true uses and limitations. You can do so by reading about AI from credible sources and completing online AI courses.

2. Identify the problems you want AI to solve

Identify how to implement AI in your business by honing in on the issue or issues that AI could solve in your company. You can then find the right AI platform to use or direct your team to build one.

For example, if you struggle with finding the right candidate for certain roles and receive more applications than you can assess, buying or creating an AI-based HR platform can help you efficiently sort through applicants to identify the ones that are likely to be the best fit.

3. Build a data strategy

Setting clear goals for implementing AI in your business allows you to create an actionable approach to its implementation. Consider the following:

• Analyze the state of your data and make sure to create measurable standards as you develop your strategy.
• Provide stakeholders with easy access to data to ensure the technology helps you reach your goals.
• Take stock of your business's current technology needs and improve processes so you can meet your AI objectives.

4. Choose the right AI tools

Consider the tasks you want AI to help you with when selecting the proper AI tool. If, for example, your company lacks the staff to write code for a specific tool, AI could be a solution.

However, choosing the right AI tools also requires you to act ethically — consider factors such as cybersecurity, data theft, and labor upheaval.

AI-generated code can present significant cybersecurity risks. The technology also learns from the code of other developers without their consent, making it ethically questionable.

5. Develop and train AI models

Training your own AI tool through machine learning can be one way to develop a model that does not depend on assets or data from others.

Using a segment of your data and giving your AI tool specific tasks first can help your tool become familiar with your raw materials and objectives. Implement AI in your business in clear-cut scenarios first before scaling up.

6. Start with a pilot project

A pilot project allows you to assess the effectiveness of a given AI tool without having to commit fully.

Don't be afraid to bring others into the process, as combining employees and external experts can lead to success. Set clear goals and a specific timeline to assess the effectiveness of the pilot project.

7. Evaluate

When evaluating your AI tool's effectiveness, consider the ethical impacts as well as the tool's ability to help you reach your goals.

• Were there any instances of data security vulnerabilities?
• Were there any small-scale issues that could be exacerbated as you scale the project?
• Could any of the tasks have been performed better by a person?

8. Scale implementation

After you evaluate your tool and determine that its ready, you can begin integrating it into company-wide processes.

It may be beneficial to have team members who worked on the pilot describe their challenges and triumphs to those who will use it as part of their daily work.

Slowly scale up, initially using your model for simple tasks before expanding to more significant business concerns.