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Identifying Business Processes for AI Implementation: A Guide

According to the Global AI Adoption Index survey conducted by IBM, in 2022, at least 35% of businesses were implementing AI in one or more ways in their operational processes. Many businesses, including private and public enterprises, are considering or implementing AI to drive digital transformation. This is because of the manifold uses of AI, which vary from improving customer experience to ensuring robust cybersecurity to even enhancing functions such as sales and marketing via analytics.

But most importantly, businesses are resorting to using AI because it improves overall operational efficiency. But how do you identify which businesses or business processes can actually be viable for AI implementation? In other words, where should AI be implemented to strengthen the overall business administration? That’s precisely what this article answers.

How To Identify Business Processes for AI Implementation

Identify the Data-Driven Processes

To improve decision-making in your business, identify the processes that rely heavily on data. These data-driven processes can benefit greatly from AI implementation, which offers real-time data analysis. With AI, you can receive business insights throughout the day instead of waiting for monthly or weekly reports. This can speed up other processes, helping you resolve minor issues quickly and seize new opportunities faster. By utilizing AI to enhance data-driven processes, you can also make them more flexible and customizable, ensuring they remain effective in the future.

Find Out Recurring/ Repetitive Business Processes

Once a business has identified its data-driven processes, it is essential to determine which of these processes require the expertise of highly skilled employees. This knowledge is crucial as it can help pinpoint where the unnecessary cognitive load is being placed, making it easier to implement AI in repetitive processes that otherwise consume a significant amount of time.

AI implementation in these areas ensures that recurring tasks that do not require the extensive application of specialized knowledge can be automated, making things easier for employees. This also saves their time, thus helping them focus on more meaningful and value-adding tasks. 

Separate Business-Critical Decisions

It is crucial to distinguish between critical and non-critical business processes when implementing AI. But how do you determine which processes are non-critical?

In essence, non-critical processes are those that do not have a significant impact on important business aspects such as cost, revenue model, schedule, or growth. Therefore, using AI in non-critical operations is not recommended to ensure the sustainability of AI usage in business. Or perhaps the implementation of AI for such operations must be low on priority.

At the end of the day, it is essential to be selective in implementing AI to ensure that infrastructural costs don’t surpass the determined budget, the benefits accrued remain true to your business model and industry, the processes are aligned with your overall corporate goals, and AI itself remains adaptable and agile to support future growth.

Analyze Whether a Workflow Can Be Placed in a Structure of Instructions

This is another crucial step to consider before going for the automation of business processes using AI. If any business processes take up significant human effort for execution but can function without specialized human knowledge and attention, they should be considered. Such workflows can be automated with the help of fixed rules, approaches, models, and strategies that are itself repetitive in nature.

A formulaic, templatized, regular, and predictable format can be created with these rules and models. This will allow AI to seamlessly and predictably take over the human cognitive load for processing and execution. 

Identify Process Subsets That Can Be ‘Proof of Concept’

Not all parts of a business process will work best with AI automation. It could be that an underlying subset of a business process just cannot function when put through AI. To that end, automating the entire business process in one instance would not be ideal. Instead, start with smaller parts. Analyze which sub-process might work better with AI and will help make the business process as a whole more efficient.

This is, in fact, an approach that McKinsey’s consultants recommend. They outline how businesses usually approach AI implementation in two ways:

  • Either they look for incremental evolution, i.e., using AI to address discrete problems
  • Or they look for all-encompassing overhauls of the business functions

While the former might never become scalable, the latter would be challenging to realize with a host of moving parts. 

Instead, the best approach is to identify which sub-processes are broad enough to accommodate changes when AI is implemented and are capable of delivering outcomes within 18 months of implementation.

Wrapping Up

By now, we’ve understood how crucial it is to consider the enterprise’s objectives, mission, and scalability needs when determining which business processes require AI implementation. When these requirements are documented and a robust implementation strategy is put in place, businesses can expect AI to significantly improve functions like revenue generation, customer base expansion, and fraud detection.
Ascentt is here to assist in identifying your business’s AI needs. Contact us today for our expert guidance.

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