Artificial intelligence and machine learning-driven automation are rapidly changing business productivity and how organizational teams work. As these technologies become more sophisticated, they are helping employees to perform their roles more efficiently and businesses to reap the rewards of enterprise automation like reduced costs and better service delivery and customer service.
Automation technologies are ushering in a new world of possibilities and opportunities. But all enterprise automation deployments depend on the quality of human data to deliver the desired outcomes and the most realistic insights. Human intelligence is, therefore, extremely crucial for automation to be effective, instead of the belief that automation can work without people.
Artificial Intelligence can only go so far in decision-making
AI can work with data and perform tasks but when it comes to decision-making, there will always be a need for human intelligence to make the final call. For instance, if you have an image recognition application that identifies images correctly most times, but occasionally mistakes a tree for a lamp post or vice versa, then this is where your decision-making process comes into play to prevent errors.
Here, human intelligence supports the AI’s ability to run better when it takes decisions based on past experience or innate knowledge of how things work; however, it also needs to be able to deal with unforeseen circumstances. A partnership between AI and humans is, therefore, essential for enterprises who want to adopt automation effectively in a 360-degree manner to reap its benefits like improved business efficiency and productivity.
Human intelligence is crucial for successful automation
The most successful enterprise automation projects depend on the quality of human data to provide the most realistic insights. Current AI technology is very good at some things and not so good at others. By pairing AI with human intelligence, businesses can overcome the limitations of AI and achieve true enterprise automation.
There are two primary ways to do this. The first is through what’s known as “collaborative automation.” This is where humans and AI work together to complete tasks, with each taking on the part of the task they’re best suited for. For instance, a bank teller might use an AI-powered chatbot to handle customer inquiries outside of normal banking hours. During regular business hours, however, a human teller would take over. This approach allows businesses to take advantage of the strengths of both humans and AI while minimizing their weaknesses.
The second way to combine human intelligence and AI is through what’s called “augmented automation.” This is where humans provide direction to AI systems, which then automate the task at hand. An example of this would be using an AI-powered software package to create a custom marketing campaign for a new product launch. The software would design the campaign based on input from the marketing team, which would then be fine-tuned by human marketers before being implemented. This approach allows businesses to get the benefits of automation while still maintaining control over the process.
In all of this, human data is more valuable and revelatory than machine data. If you don’t provide good quality and diverse human data then your AI will suffer. And unlike traditional software development, in which one can usually assume that a bug will never occur, automation is constantly being updated with new features and functionality. That means there could be hundreds or thousands of ways for a machine learning model to fail without even realizing it until months later. It’s much better to catch these bugs early on before rolling out updates worldwide than waiting for them to happen after everything’s been deployed on every user’s device/systems/etc.
Additionally, automated systems can sometimes struggle with tasks that require a high degree of situational awareness, such as managing an incident response or detecting and responding to security threats. For these reasons, it is essential to have a clear understanding of the strengths and limitations of AI and automation before implementing these technologies in enterprise IT operations.
Successful automation deployments need both human intelligence and artificial intelligence
When deployed effectively, AI and automation can offer a number of benefits for enterprise IT operations. These benefits include increased efficiency, improved quality of service, and reduced costs. Additionally, AI and automation can free up human beings from routine tasks so that they can focus on more strategic initiatives.
However, it is important to remember that human input remains key to successful enterprise automation. Automated systems cannot yet replicate all of the capabilities of human beings. As a result, it is critical to have a clear understanding of the strengths and limitations of AI and automation before implementing these technologies in your organization. Additionally, it is important to ensure that there is close alignment between the goals of your business and the capabilities of the technology. Only by taking these factors into account will you be able to realize the full benefits of AI and automation in your organization’s IT operations.
Conclusion
Machines are great at performing tasks automatically with precision, but they lack the creativity needed to make decisions based on context-specific knowledge and experience—and that’s why humans have an important role to play in any automated process. Proper alignment of business goals and technology requirements can help organizations ensure they realize the full benefits of automation by building systems that are efficient and easily scalable.
