1.4 Business Automation
Another way to view the IS discipline is as a means of business automation. Business automation refers to the use of technology to execute recurring tasks or processes in a business where manual effort can be replaced. It is designed to streamline processes, increase efficiency, and reduce costs by minimizing human intervention. Business automation is created for every function including marketing, sales, customer service, finance, and operations.
Generally speaking, automation is the process of moving tasks from the human side to the machine side of an IS. In accounting, ledgers must be balanced (equal zero). You could manually record every transaction in a debit or credit column of a spreadsheet. Or, you could set up an IS that automatically balances a virtual ledger every time a transaction occurs. In retail, you could manually update inventory levels every time a product sells. Or, you could set up an IS that automatically updates inventory levels the moment it is scanned in a store. Furthermore, it could automatically reorder inventory when levels get too low and dynamically choose the cheapest supplier from a database of potential options.
Types of Business Automation
We build IS to automate every type of task. Below are the most common types with examples:
Process automation: Automates routine, repetitive tasks.
Automated Invoicing: When a sale is made, the system automatically generates an invoice, sends it to the customer, and records the transaction in the accounting system. The system can also send reminders for overdue payments.
Example tools: QuickBooks, FreshBooks, Zoho Invoice
Workflow automation: Manages the flow of tasks across different departments.
Employee Onboarding Workflow: When a new employee is hired, the HR software automatically sends welcome emails, sets up necessary accounts (email, software access), schedules training sessions, and notifies relevant departments (IT, payroll) to complete their tasks.
Example tools: BambooHR, Workday, Monday.com
Robotic process automation (RPA): Uses software robots to perform high-volume, repeatable tasks.
Data Entry and Migration: An RPA bot extracts data from a legacy system and inputs it into a new application. This process is automated without human intervention, ensuring data accuracy and saving time.
Example tools: UiPath, Automation Anywhere, Blue Prism
Artificial intelligence (AI) automation: Uses AI to automate complex decision-making processes.
Customer Service Chatbots: AI chatbots can handle customer inquiries, provide product information, troubleshoot issues, and even complete transactions. The chatbot uses natural language processing (NLP) to understand and respond to customer queries.
Example tools: IBM Watson Assistant, Chatfuel, Drift
Machine learning (ML) automation: Applies ML algorithms to automate predictive and prescriptive analytics.
Predictive Maintenance: Sensors collect data from machinery, which is then analyzed by ML algorithms to predict when a machine is likely to fail. Maintenance is scheduled proactively, reducing downtime and repair costs.
Example tools: Azure Machine Learning, TensorFlow, IBM Predictive Maintenance and Quality
Generative AI automation: These tools automate the creation of text, audio, and video.
Report Writing: At the completion of a long project, the manager is required to write a report documenting the details of how well the plan was executed, how effective the results were at meeting the requirements, and how closely the budget met projections. The manager can provide the generative AI with various documentation and produce a well-written summary of the project which then only needs to be reviewed for accuracy. This is similar to AI automation, but different in that the end result is generated content rather than a transaction or decision.
Example tools: ChatGPT, Copilot
Implications for Workforce and Upskilling
Does this mean that IS will put people out of jobs? Yes and no. Yes, because automation has displaced jobs for centuries. No, because the added efficiency that automation enables creates new value for the organization that is put right back into the business in the form of new jobs. This has also been true for centuries and will not change. However, it does force many workers to upskill if they don’t want to end up useless in the job market.
This is a critically important fact that you should consider and accept right now—you must continue learning throughout your life. You are the master of your own value to any employer. You must assume that your employer is focused on the company’s future—not yours. You must take complete responsibility for your own upskilling. Do not avoid difficult tasks or projects simply because you want an easy career or you will eventually become displaced. Do not avoid learning new technologies because those you know now may one day become obsolete.
If becoming outdated is such a concern, then wouldn’t it be better to choose an entirely different career route? That is your choice to make. But where there is higher risk, there is higher reward. IS-related careers are some of the most profitable and rewarding. Ask a generative AI (e.g., Copilot or ChatGPT) to tell you all about the most common job roles of recent IS graduates (e.g., systems analyist, business analyst, data analyst, database administrator, IT consultant, cybersecurity analyst, project manager, software developer, web developer, cloud architect, digital marketing analyst, etc.). Ask what the current average salaries are for those roles, what the work life balance is like, and which technology skills are most relevant in each role. This will give you an idea of what you would study in an IS program and which skills to focus on.
The good news for IS professionals is that there may be more online help and resources for technology upskilling than any other type of skill. If you can learn how to learn during your university degree(s), then you’ll be able to continue learning, upskilling, and future-proofing yourself throughout your career.