The following are the top 8 most important areas of difference in the RPA vs. AI debate.
1. Function
The primary function of RPA tools involves mimicking human tasks. AI, on the other hand, focuses on mimicking human thoughts. Therefore, RPA software can’t make its own decisions, whereas AI tools can make independent decisions. In other words, RPA is the muscle, and AI is the intellect.
2. Configuration
Since RPA solutions can’t make autonomous decisions, RPA developers and human workers must configure rules to ensure certain ingrained capabilities. While AI solutions require intricate programming, they can analyze vast amounts of data and independently establish configurations.
3. Execution
RPA software is relatively simple to execute, whereas the implementation of AI automation can be a painstaking and intricate process. RPA has numerous no-code and low-code options that require no advanced technical skills or insight.
4. Flexibility
Both RPA software and AI tools feature high degrees of flexibility. The difference is that RPA software requires human intervention to alter or enhance its use case. In contrast, AI can learn from diverse data sources to change its behaviors depending on complex variables.
5. Optimization
Businesses must proactively optimize and enhance their tools and technologies. This is easy with AI solutions because AI self-regulates and self-optimizes based on feedback and related data. Conversely, getting under the hood of RPA tools requires manual work.
6. Disruption
RPA tools and AI solutions fundamentally change processes within an organization. However, introducing RPA tools is a less dramatic shift because it doesn’t entirely replace human workers. AI solutions, in a lot of cases, make human workers redundant. While there are benefits to replacing workforces, businesses must acknowledge the long-term implications of AI.
7. Strengths
There are unique strengths and capabilities associated with RPA tools and AI solutions. For example, RPA tools are perfect for conducting back-office administrative tasks. Among many other capabilities, AI automation can provide a human touch to front-end interactions and greatly enhance customer service and experience.
8. Accuracy
While AI automation might seem like the ultimate solution for industries, businesses must remember that probability plays a significant role. Therefore, the accuracy of outputs depends on the quality of training data. RPA software boasts higher accuracy rates, but businesses should remember that this depends on the quality of the predefined software rules.