Automation is not a newcomer to the business world. Companies have been leveraging it for centuries to gain a competitive edge. From the early days of mechanized looms to the more recent appearance of smart technologies, the business world has welcomed wave after wave of automation.
The latest wave to arrive is AI-driven automation. Artificial intelligence takes automation to the next level, moving beyond the rule-based systems that have come before it and entering into an era of adaptability.
Whereas traditional automation required creating a path for machines to follow, AI-driven automation has the power to blaze its own trail. AI learns while working, empowering dynamic rather than static automation. AI-driven automation not only manages processes with speed and precision but also helps companies understand how to better streamline those processes and gain even more efficiency.
Using AI automation for repetitive tasks
Automation is typically used to handle repetitive tasks. Automated answering systems, for example, were designed to handle the hundreds of calls companies would receive on a daily basis, allowing a menu to guide and connect callers instead of a human receptionist. While the systems weren’t widely appreciated by callers, they helped companies by relieving them of the need to answer countless incoming calls.
AI allows a company to go beyond conditional automated systems — if the caller presses number 3, the caller will be connected to customer service — and use autonomous systems. Systems leveraging AI-driven automation make decisions independent of human interaction, broadening the variety of tasks they can accomplish.
Data entry is one repetitive task AI can automate with ease. All phases of the process can be managed by AI without manual intervention, including:
- Data extraction: AI can identify and extract data from invoices, applications, and other forms using optical character recognition to gather data from physical forms.
- Data categorization and labeling: AI can interpret what type of data is presented, even when hand-written, to ensure it is appropriately classified and prepared for entry.
- Data validation: To ensure data integrity, AI can identify errors in the data being processed and correct them before adding it to the database.
- Data formatting: AI can reformat data to ensure consistency in databases
- Data indexing: To make data retrieval more efficient, AI can index it to fit any parameters needed, even indexing on demand when new search needs arise.
Repetitive customer service processes can also be streamlined with AI automation. With AI, the annoying automated answering systems of the past have become AI-powered chatbots that can interpret the nuances of customer service requests, often answering them without the need to get a human representative on the line.
Additionally, AI-driven automation can streamline email requests by sorting and prioritizing messages. This allows companies to quickly determine what is urgent and needs to be bumped to the top of the queue. AI can also automatically respond to emails with customized information that specifically addresses concerns mentioned in messages.
In HR, AI automation can manage applicant screening, easing the burden on companies seeking to identify top candidates while letting applicants know more quickly if they need to continue their search. AI can also be used by HR teams to make onboarding processes more responsive and customized.
Using AI automation for advanced analysis
AI automation holds excellent potential for not just managing data but also mining it. AI excels at identifying patterns in data, which can benefit companies in any industry in a wide variety of ways. For example:
- E-commerce companies can automatically analyze browsing behavior to identify the type of upsells and cross-sells that would appeal to customers.
- Retail companies can automatically analyze sales data to determine if inventory is sufficient to support current sales trends.
- Manufacturing companies can automatically analyze sensor data to identify when equipment maintenance is needed.
- Transportation companies can automatically analyze vehicle data, such as miles traveled and fuel consumption, to determine which routes are most efficient.
Using AI to automatically analyze financial data is highly beneficial for companies in any industry. AI can identify patterns in customer payments that indicate the company should expect delays, giving it time to proactively address a potential issue. AI can also be used for fraud detection, automatically assessing transaction data to identify suspicious activity before it leads to losses.
The capacity for producing real-time analytics is the primary advantage companies gain when they unleash AI automation for financial processing and analysis. Business leaders who lean on AI can have up-to-date financial intel whenever they need it, streamlining the decision-making process. Reporting becomes more reliable and accessible, with AI-generated visualizations and interpretations making it more readily understandable.
Using AI automation to increase human potential
Companies that use AI automation to boost efficiency by removing human employees from the payroll miss out on its ultimate value. AI’s highest potential is found in increasing human potential, which it can do in several ways.
Firstly, AI automation gives employees more time to accomplish high-level tasks. As AI automation streamlines customer service operations by managing routine inquiries and sorting the rest, human agents can focus their time on reaching out to high-value customers and addressing legitimate issues that require more diplomacy than a chatbot can offer. And when AI automates the processes needed to keep machinery running optimally, it frees up equipment managers to explore innovations that can improve efficiency or sustainability.
Secondly, AI automation gives employees valuable intel for driving better decision-making. It can handle tedious bookkeeping duties, allowing finance teams to become true financial strategists using AI-driven analytics to fine-tune business plans. AI can even deliver predictive analytics that gives business leaders a glimpse of what the future will most likely hold. Armed with that information, they can more accurately assess what opportunities are most promising and the best way to pursue them.
Business leaders looking for a multiplier that will allow them to do more with less will find it in AI automation. It adds a component to your workforce that never tires, regardless of how tedious the task, and delivers accurate, real-time, relevant intel. AI automation removes the barriers that keep companies from reaching their full potential.
Snehal Shinde, Co-founder and Chief Product Officer of Zeni, is a Product Entrepreneur with more than 15 years of professional experience leading innovative products and technologies that have impacted millions globally. Zeni is a CFO-as-a-service platform that has raised $47.5 million to date. With Zeni, Snehal is building intelligent, human-like financial agents that seamlessly take over the roles of bookkeepers, accountants, controllers, and tax.