A Peek Into the Future of BPM and AI

In a digital age, more and more tasks are being eaten up by software. Many tools have gone from nice-to-have status to absolutely essential.

Business processes are the next item on the menu for digital transformation efforts and there are already many options to choose from. Business process management (BPM) has been a recognized discipline for a few decades, but it’s only been recently that many of the tools have been made available to any sized business.

But at the forefront of BPM are new and developing innovations including adding Artificial Intelligence to how processes function. This new breed of business intelligence will not only automate repetitive items but also improve them and adapt to changing circumstances with little human involvement.

The Shifting Motivation for Introducing AI to BPM

According to Forrester Analyst Rob Koplowitz, the main reason companies have historically invested in BPM was for cost reduction. Improvements in efficiency allowed organizations to reduce their spend across multiple areas.

However, that trend has changed. Now, according to the Forrester report, the primary driver is customer experience. While cost savings are still important, businesses will begin to look to BPM for a wide variety of improvements. BPM not only drives down costs but can also optimize the experience of the end customer.

Introducing AI is an important part of achieving these varied goals. While cost reduction is easy to focus on, business process analysts must weigh a large number of factors when trying to also optimize customer experience, digital transformation, regulatory compliance, and many other elements. AI makes computing and evaluating these changes much more manageable.

4 Early Ways AI Will Improve BPM

While some of the advancements in BPM from AI are several years away, here are four areas where AI will have an impact very soon in how processes are better optimized.

Adding Natural Language Processing

One key part of the AI burst is how it processes language. Natural language processing is a key step in getting to the next level of BPM.

For example, rather than opening up a form, team members can just say, “Start a new expense report for my trip to New York.” The AI functionality will be able to not only initiate the form but also parse through emails and receipts to find relevant expenses to include.

In addition to initiating forms, natural language processing should also allow for changes in the process from administrators on low-code platforms. For example, while in a meeting, an administrator should be able to say, “Add an approval step for Brandi after the P&L reports are generated.”

This kind of functionality will continue to make BPM more and more accessible and top-of-mind for business leaders.

Automatic Optimizations

Another quick area to see improvements from AI with BPM is in how processes are improved and optimized. Many times, delays and inefficiencies aren’t seen by humans until well after problems arise and show a pattern. A well-equipped AI tool should be constantly monitoring regular business processes to note where potential trouble spots will develop. This might involve a smart assign feature where the system can decide who should act on a request based on past performance and current availability in order to avoid bottlenecks.

In addition, AI can analyze business processes to make recommendations on changes in order to optimize a process. When a process is continually sent back or rejected, the system can find a way to prevent these inefficiencies and find a better way forward.

While recommendations are the first step, eventually AI will develop to make real-time implementations of process modifications.

Focusing Humans on High-Value Tasks

As AI continues into BPM, it can also analyze the amount of time that humans take to perform certain tasks. Through a process of machine learning, a smart BPM system can identify situations and forms and data that cause humans to spend extra time on a task where it is unneeded.

AI will also be able to analyze decisions that humans make over time. It can make suggestions such as “You normally approve items like this. Do you want to auto-approve similar requests?” This teaches the system the exact situations where different decisions are made. The system will also identify where there are complexities that humans must spend time with to find the best solution.

Aligning Disparate But Similar Processes

In large global organizations, there are often multiple processes created for the same function, such as a purchase order. Different regions may require different documentation or approval steps. However, when all the processes are automated on the same platform, AI can compare the processes and find areas where they can be more in line and standardized while still maintaining autonomy when required.

An Automated, Intelligent Future

As digital transformation and AI continue to make an impact in every area of business, there are many clear outcomes. When it comes to business processes, organizations realize that it is not only cost reduction but many other areas like customer experience that can be impacted by better processes.

AI will have a drastic long-term impact on business processes, but even the short-term outlook is quite impressive. As AI moves forward, business leaders can expect to partner closer with machines to make better decisions in a changing world.