To flourish in the age of AI, we need to transform our business processes in the way we open them up to make the most of AI.
You can provide business AI tools so that you can lead a man to the water but not drink him, but in reality it cannot be an effective part of the business process.
In fact, in my experience helping organizations modernize their IT infrastructure and environment, the inability to successfully integrate AI into processes powered by everyday business operations is one of the key factors that lead to lack of returns on AI investments. If your organization wants to successfully leverage AI, it must use AI technology to speed up business processes.
The reason this type of change is so important is important along with practical tips on how organizations align their business processes with AI.
Why AI innovation requires business processes to change
The stories that many companies are unfolding are not new as they struggle to fit AI into existing business processes. With each emergence of disruptive new technologies, we encountered a similar trend. Cloud, mobile computing and big data have all spurred similar challenges over the past few decades.
At the heart of the issue is that creating real value through innovation requires commitment to transforming business processes, in addition to deploying new technologies. This means that workers will change the way they perform tasks, rethink the expectations surrounding those tasks, and invest in new safety measures to mitigate the new risks that emerge in the context of those tasks.
For example, let’s take a look at the example of mobile computing, which first began to become popular in businesses. To harness the value from this technology, companies have not only provided smartphones and tablets to their employees. Additionally, mobile technology gives us much more flexibility in this regard, and expectations surrounding the ability to perform tasks remotely had to be changed. They had to build new security controls in many processes to mitigate the new risks that arise when workers log in from remote devices using third-party networks. They needed to strengthen their data practice strategies to properly store and protect mobile data. and so on.
AI poses a similar set of challenges. For example, consider the process of finding information within a company’s knowledge base. When employees use AI-powered tools for this purpose (as opposed to traditional search engines), new risks arise, such as the possibility that AI tools may expose information that is not available to certain employees. To mitigate these risks, new types of security controls must be built into the process.
This is just one basic example, but when AI (or major new types of technology) enters business, if the process needs to evolve, the company needs to add little value.
See also: How to get the most out of Intelligent Process Automation
Procedures for adapting business processes in the AI ​​era
Transforming business processes to make the most of AI requires work, but it’s a viable exercise. We recommend approaching based on the following four steps:
1. Identify processes affected by AI
First, companies need to determine exactly what existing processes need to be altered as a result of their AI investments. This is important because you cannot make the correct conversion unless you know what to convert first.
In some organizations, AI can affect almost every process. However, those who deploy AI at a more limited scale or only in a specific use case can see that it can only affect a small number of processes. To determine what will be impacted by your company, stock current processes, evaluate them against a list of AI features adopted, and look for cases where AI technology changes how processes work.
2. Consult with the process owner
The people who know best what needs to be changed within a process to accommodate AI are those who run or oversee that process on a daily basis.
Therefore, organizations need to consult with the “owner” of processes affected by AI adoption, discuss how to perform the tasks currently, and identify how the workflow will change depending on the use of AI tools. Additionally, when adding AI to existing processes, you must determine the new types of risks or challenges your business needs to manage.
3. Identify opportunities for expanding AI adoption
The goal of a process transformation should not be limited to addressing current changes. Additionally, companies should consider ways to use AI tools further in the future and additional processes that need to be implemented to support those changes.
This exercise is especially valuable for identifying opportunities to eradicate manual tasks in the process. AI is great at making dynamic and automated decisions. This is the type that traditionally requires input from humans. Once you grasp that ability, companies can implement plans to continue evolving their business processes and take advantage of AI more over time.
4. Integrate AI directly into business processes
The approach many organizations take to leverage AI is to generate data through business processes and feed the data into external tools to make decisions. This works, but it does not make business processes as efficient as possible.
Ideally, organizations are taking it a step further by directly and fully integrating AI into the process. A good example to follow in this regard is that it is set up by SAP through the Business AI initiative. Unlike many other large platform vendors, SAP doesn’t expect customers to deploy standalone AI tools and find a way to connect them to the system. Instead, they embed AI capabilities directly into processes and capabilities built into the ERP platform.
Rather than solving processes supported by external AI tools, SAP is alternatively making AI inseparable from processes, making it maximizing both ease of use and efficiency. This happens when the conversion to an AI-friendly process is completely complete.
Conclusion: Adopt AI-centric business process transformation
The difference between companies thriving and struggling in the age of AI is not necessarily the specific AI tools each company uses, or even the use cases it targets. Instead, it depends on how effectively each company can transform its process in a way that opens up to make the most of its AI.
This type of transformation is something that all types of businesses should now prioritize as they navigate the new world created by modern AI technology.
