Five issues with implementing AI too fast!
Digital transformation has been on the horizon for many different size businesses and corporations. Digital Transformation has many different meanings, but AI (Artificial Intelligence) and RPA (Robotic Process Automation) have been on the radar for quite some time. Initially, digital transformation was a part of business plans to find a way to stay up with customer behavior, technology innovation, and finding faster ways to do things. With Covid-19 and shortages (supply chain and employees), digital transformation plans have been accelerated. The fundamental factors are still a part of the transformation plans. The acceleration is needed to find the right ways to support remote work plans, safety for employees, handle the shortages, and implement new processes due to new regulations.
What is wrong with implementing fast?
There are increasing demands to keep the customers and employees happy in this new world, but this comes with more costs that will cut into revenue profits. Many business owners and leaders think that implementing RPA or AI will solve many of their business problems and help with costs. These technologies do produce positive results in the form of cost savings, increasing ROI, better processing or cycle times, and increasing revenue. But if you do not take the time to plan correctly, implementing RPA and AI can become costly and time-consuming. Business owners and leaders find out quickly that they have more complications after the implementation than before they started.
During my past 13 years of experience with any technology transformation and Continuous Improvement, if a business does not take time to plan, issues come up with the implementation. These issues will cause the transformation to take longer than expected, which means it costs more money than expected.
What are the issues?
1. Wrong reasons
AI and RPA projects fail because there is a lack of clarity on the project from the start. When a business starts implementing these types of projects quickly, the wrong problem is being solved. The right kind of questions is not asked, which leads to the wrong reasons and project goals. Without honestly knowing what you are solving for, the project will fail right from the start.
2. Process issues are seen faster
There are different arguments on whether you should fix a process first or throw technology at the problem. I see too many businesses throw technology at the issues, only to watch the process completely break down. AI and RPA will reveal how bad a process is faster and at more cost. After these failures, the technology is removed, and the projects become failures. When these failures start to happen, businesses lose momentum, and business leaders lose faith in the technology.
3. Culture and workforce issues
Employees often fear AI and RPA because they are afraid they are going to lose their jobs. People fear what technology will do to do their jobs. When you combine this with the technology broken by the technology, the culture becomes an issue. When your employees are unhappy, this will affect them.
- Quality with the services and products
- Production and cycle times begin to be elongate.
Employees will not be on board with any future changes, and the workplace will become hostile. Business leaders need to remember that when their employees are unhappy, their customers are usually going to be dissatisfied as well. Businesses cannot lose the people side of things if they wish to implement AI and RPA successfully.
4. Dissatisfied customers
Process issues and unhappy employees contribute to dissatisfied customers. It is vital to ensure customers are as happy as possible during these ever-changing times and do not feel alienated. If customers are not satisfied, they start to lose faith, taking their business somewhere else. Without customers, a business cannot survive.
6. ROI (Return on Investment) will not be delivered
In 2018, Gartner stated that about ~85% of AI projects would not deliver CIOs’ impact. One of my clients lost $2 M in costs, rework, and revenue by implementing RPA too fast. One of my prospective clients lost ~$5 M in costs and had cultural issues due to implementing RPA too quickly. It is important to note these types of cases because it helps to bring the hard reality when AI and RPA should not be applied too fast without planning.
Everything is changing so fast during these times, but while it may seem moving fast is right the right thing to do. But the right move is to move slowly to move fast. But how do you plan to use AI or RPA right the first time? Each time I work with a client who wants to use AI or RPA, I apply Continuous Implement. We start with setting goals, planning, leveraging Lean Six Sigma, and applying AI or RPA. After everything is in place, we set up a Continuous Improvement Plan. The plan ensures that the company is always improving and can pivot as needed for growth, market demands, and customer changes.
What are your thoughts?
Have you experienced this in your business or organization?
If you would like to help solve these issues, let’s set up some time to talk.
“if you do not take the time to plan correctly, implementing RPA and AI can become costly and time-consuming” – Lauren Hisey