How to implement AI in business process design

Artificial intelligence has a mixed record of success and failure in business processes. What should you do for successful AI implementation?

On the very first business process design project, my team was told to redesign an internal invoice process in accounts receivable. Problems involved duplicate systems and duplicate BPs that prolonged invoice processing for days. Working hand in hand with finance, we reviewed each step of the process, identifying duplicates in data and processes and eliminating them. The result was a more streamlined invoicing process that went from three days to one.

I often think of that first BP redesign assignment and how straightforward it was when compared to redesigning BPs with artificial intelligence.

SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium)

The difference in BP design with AI is that you’re doing more than streamlining business processes. You’re radically changing how employees do work. This makes the BP change project a human issue as well as a process and system change.

IT and business leaders need to be sensitive to this, or a new and redesigned business process could fail when employees resist it.

Four best practices for business process design with AI

Never initiate without a strong business use case

This use case should be defined and bought into by the end user department that uses the business process. Is there a user pain point or a productivity improvement goal that a BP redesign with AI can solve? And if AI and automation are inserted into the business process, do the end users support this?

Provide the AI with enough information so it can do its job

The rules and data provided to an AI decision-making engine originate from subject matter experts and those on the end user staff who understand the intricacies of an existing BP and the decisions and operations that BP makes and executes. You can’t inject AI decision making and execution into a business process if you don’t have the requisite expertise to define the AI’s rules of operation and decision making.

Determine the AI’s systems impact

Every system that interacts with the AI in a revised business process must be modified to receive and to send data to the AI. One of the most common errors in AI BP design and implementation is forgetting about a downstream system from the AI that is adversely impacted because someone forgot to build the necessary interface between the AI and that system.

Determine the AI’s human impact

There is probably no step more important than this one.

Users may initially be excited about AI and automation taking rote tasks off their desks, but they won’t be excited for long if they think that the new AI is going to eliminate their jobs.

If job loss is expected, the best thing to do is to level with employees upfront. Try to reassign them to other jobs in the company.

If there is no job loss impact, but instead a new AI-infused BP that employees must be retrained for, the retraining should be aggressively undertaken and enthusiastically supported.

Employee wellbeing is an essential outcome for any AI infusion into a business process.