BAs in this Evolution – AUTOMATION to AI
BAs in this Evolution – AUTOMATION to AI
Jan 09, 2018
The Evolution From Automation to AI
There isn’t a single company in the world that wouldn’t like to reduce its expenses, and one of the easiest ways to do that is by reducing the need for human staff. For many companies, bots — software programs that automate tasks — have made it possible to reduce staff costs while serving more customers with less waiting. Companies’ implementations of bots range from automation of repetitive tasks to full-blown artificial intelligence — and automation has permeated every industry including technology, healthcare, accounts, retail and more.
The paperless office is one of the most common examples of automation in business. Banks, post offices, accounts departments and more have all implemented measures to process data automatically rather than moving paperwork between departments. The smartphone mobile assistant is another prominent example of how machine learning and artificial intelligence have permeated our lives. Your smartphone’s virtual assistant can dial numbers, add appointments to your schedule, send text messages to your contacts and more without you using the keypad or even unlocking your phone. With automation and AI now exiting the world of technology and revolutionizing business as a whole, the possibilities for the future seem limitless.
The Revolution Began With Basic Automation
Basic automation allows a computer to perform basic tasks automatically without utilizing advanced cognitive abilities such as improvisation or problem recognition. The computer repeats the same pre-programmed steps every time, and the quality of the result depends upon the quality of the initial data. Utilities even allow users with no programming knowledge to automate repetitive tasks by recording their own actions. With a single click, the computer plays back the recording and replicates the user’s actions. One situation in which macros are useful is in website testing; a single click can cause the computer to complete a suite of tests in minutes.
Automation In Practice
For a deeper understanding of how automation can work in practice, consider the example of a team member who wants to request vacation time. Before automation, the employee would submit an application to his or her manager. The manager would review the application and approve or deny it. Simple automation makes it possible to create a system such as a web portal that allows employees to request vacation time. The system could forward requests to management for approval and update employees about the status of their requests.
Next, let’s examine how companies can enhance automation by adding workflows and data analysis. Systems like Google Assistant already utilize advanced data processing skills to great effect by scanning emails, notifications and attachments, inferring meaning and taking action based on the user’s anticipated intent. Companies that add advanced data processing features to their automated workflows will benefit from massive cost savings and greatly reduced manual effort.
Referring to our previous example of an employee requesting vacation time, a system with advanced automation could read and process the employee’s reason for requesting leave. The system could also differentiate between a casual leave request and earned vacation time. Giving the system access to information about the company’s scheduling needs would allow the system to approve or deny vacation time automatically based on whether the leave would create a manpower shortage. Upon approving a leave request, the system can automatically update the schedule and send notifications to the employee, his or her supervisor and the HR department.
Artificial intelligence is the most advanced form of automation. Companies have embraced AI by implementing decision trees, complex algorithms and live monitoring to create reactive cognitive applications. Since AI allows bots to handle incoming requests and send responses automatically, decision makers can focus on high-level results rather than manual handling of low-level tasks.
Machine learning takes AI even further by giving bots the ability to analyze language for sentiment and intent, learn synonyms and respond to whole phrases rather than one-word queries. Machine learning helps to create bots that anticipate users’ needs, recommend likely solutions and consider the context of previous queries when replying to input. AI and machine learning have enhanced search engines, online banking, website content delivery and more.
Let’s examine the enhancements that AI and machine learning can bring to our previous example of an employee requesting vacation time. The employee begins by launching a work-related application or website. The application greets the employee and awaits input. The employee types the word “Leave.” Based on the employee’s previous interactions — and the interactions of other employees who have typed the same word — the system correctly guesses that the employee wishes to request vacation time. Using natural language, the employee converses with the application to enter the desired date and reason for requesting leave. The application can either forward the request to a supervisor for manual approval or check the requested vacation date against the company’s scheduling requirements for automatic approval. If the application has permission to approve requests automatically, the employee receives a real-time notification. He can then continue the conversation or log out.
Putting It All Together: Automation Can Transform Business Processes
On the surface, processing an employee’s request for vacation time may seem like a trivial task. In reality, though, processing a request for leave may require more than one man-hour of work and input from multiple people. In a company that processes leave requests manually, the employee’s supervisor would need to check each request against a schedule to confirm adequate staffing. If the company is legally required to grant the leave request because of the circumstances, the supervisor might need to ask another employee to come in on his or her day off to keep the department running smoothly. In the case of a paid leave request, the supervisor may need to forward the request to the HR department to process payment and deduct the vacation time from the employee’s account. By automating the process and removing the need for human input, an automated system for processing leave requests could save a large corporation hundreds of man-hours per year — and that’s just one business process. Using AI also improves the experience for the employee. The next time the employee types “Leave,” the application will know what he wants and can respond with the correct tone depending on the circumstances for requesting the leave.
What does the future hold for automation and AI? Speech recognition and natural language processing are two of the most exciting areas of development in AI today. As AI systems improve at recognizing what users want and performing those functions with little effort, those systems will do a better job of improving our lives at home and work. For most people, AI won’t threaten to make jobs obsolete; it’ll simply change the nature of those jobs and allow people to concentrate on more important activities while the AI systems handle the repetitive tasks. AI also won’t remove humans from the business equation because humans will be the ones creating, applying and maintaining the AI systems.
In particular, AI and automation will transform the careers of many business analysts. The analysts will bridge the gap between the creators and users of AI services. They will build the workflows, define the parameters and optimize the AI services to achieve the ideal results. Ultimately, AI services will deeply ingrain themselves within the fabric of many businesses around the world. Those businesses will come to depend on automation to make employees’ time more productive, increase employee satisfaction and keep ongoing expenses as low as possible.
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