How to Identify the Best Workflows for AI

Tasks that are well-suited for AI automation are often those that people find tedious and won’t miss once they’re automated.

Generative AI has rapidly advanced to a level where it can deliver significant, strategic improvements to business offerings and operations. Yet, its adoption in everyday business processes remains limited. Many organizations struggle with an abundance of possibilities: Where should we focus development efforts when new ideas and opportunities keep emerging?

My recommendation is to start by identifying the repetitive workflows in your organization that are best suited for automation with AI. By streamlining these, you can achieve tangible, measurable improvements quickly and cost-effectively.

How do you know which workflow is best for AI automation?

Tasks that are well-suited for AI automation are often those that people find tedious and won’t miss once they’re automated.

These tasks repeat day after day, consume time, require concentration, but offer little sense of purpose. As a result, they are prone to errors. Traditional RPA (Robotic Process Automation) has not been enough to automate these tasks because they require flexible reasoning and contextual understanding.

I evaluate potential AI-automated workflows from three perspectives:

1. Speed and Quality Impact Customer Experience

When the speed or quality of a workflow directly affects customer experience, for example resulting in faster response times, improved delivery reliability, or clearer communication, AI can add significant value.

Generative AI can interpret and produce customer messages, analyze large volumes of content, and suggest solutions in seconds. This improves customer satisfaction and frees experts to focus on more demanding tasks.

2. Repetition and Routine

AI excels at tasks that repeat in similar form dozens or hundreds of times each month. When a workflow is standardized and consists of clear steps, generative AI can be instructed to deliver consistent, high-quality results.

Examples include interpreting and categorizing customer messages, using product and production data, creating pricing or customer-specific action proposals, and updating structured information into operative systems. These are areas where AI can replace repetitive manual work almost entirely.

3. Multi-Step Processes and Cross-System Data Retrieval

Workflows that require multiple people, involve different systems, and demand searching for information from scattered sources are prime candidates for automation due to their high optimization potential.

AI can combine data from various sources, suggest next steps, and even handle parts of communication automatically. This reduces errors, speeds up processes, and improves overall control.

AI excels at tasks that repeat in similar form dozens or hundreds of times each month.

 

Steps toward AI-assisted efficiency

Identifying a workflow suitable for AI doesn’t require technical expertise. It requires understanding where work is boring, repetitive, and error-prone. When you find a workflow where automation improves customer experience, reduces manual effort, and enhances quality, you’ve already taken the first steps toward AI-assisted efficiency.

For practical examples of workflows that fit AI perfectly, check out our article AI Assistants in Practice: Three Common Workflows. It explains how AI can be applied effectively and successfully in different business processes.

At Aines, we run workshops for our clients where, through carefully designed facilitation, we identify and prioritize the most promising repetitive workflows for automation in just a couple of hours. Don’t hesitate to reach out if you’re interested!

—Markus