Why documented processes will help you use AI

The buzz about how artificial intelligence is going to transform our businesses and boost efficiency is everywhere. Every day business publications are putting out more information and ideas about how AI is revolutionizing some aspect of the business world. 

If you take everything written at face value, you might be thinking you need to use artificial intelligence for everything your business does and start eliminating team members. This would be a rash decision. You are better served starting small and experimenting with AI tools and exploring where they can improve your business.

The businesses that will thrive with AI are not necessarily the most technically sophisticated. They are the ones that have done the foundational work of understanding and documenting what they do day in and day out. Start there, and AI becomes a powerful amplifier of your existing strengths rather than just another shiny distraction.

As you start playing around with AI in your business, you might find that jumping in is the best next step. If we agree with the adage “slow down to speed up,” you first need to know what you are doing now to identify the best ways to accelerate with AI.

Here are three reasons why having a full understanding of your processes and workflows, and having them documented, will help you use AI to the benefit of your business.

1. AI Can Only Automate What You Can Articulate

Think about the last time you trained a new team member. You likely fumbled over jargon and could not capture all the nuances of what needed to be done, evaluated and decided on, or couldn’t list out all the different exceptions that would present themselves. If you used the same conversation with AI in hopes of replicating the process, it is even less capable of making sense of what you do and where it can help.

For example, automating your invoice creation process requires more than simply what to put on an invoice. There are the unique nuances of invoices for specific clients or the different rates that go into effect at different times. Identifying every step in your invoice process, including the one-off situations, eliminates the invisible, “it just happens” steps. Then AI can create invoices that do not always need editing because you failed to train it that your one client requires each session to have the title in red font.

2. Documentation Reveals the Perfect Starting Points for AI Integration

As of this writing, not all processes are equally suited for AI assistance. Without documentation, you are throwing spaghetti against the wall and hoping what sticks is valuable. Guessing where AI might help, versus leveraging existing processes, leads to frustration and wasted resources.

When you document your workflows, you can identify which tasks are repetitive versus creative and which require human judgment versus rule-based decisions. Tasks that are perfect for automation are data entry, categorization, and repetitive formatting. Knowing exactly where that happens within your organization eliminates the need to throw spaghetti.

3. Your Team Will Use the AI Tools You Implement

A big challenge organizations are facing is employees unwilling to implement AI tools for fear of losing their job to the automation. As excited as you may be about the opportunities for AI, if your team sees it as a replacement versus an enhancement, they will resist.

If you document all the workflows, your team will be engaged in the process, as they are the ones that know the workflows. They will then be able to identify what steps are easiest to automate and can focus on those tasks they prefer not to do. In addition, they can find areas in the workflows that are not best suited for AI where they can add more value or are excited to learn more about.

The Bottom Line

Artificial Intelligence is not a fad. Using it for your back-office operations is key for growth. Process documentation is not a requirement for artificial Intelligence. It is essential because it forces you to understand your own business with the clarity needed to make strategic decisions about AI technology adoption.