How Artificial Intelligence is changing the way businesses operate?

Till recently, computers were able to automate simple, rule-based processes at the workplace like billing and accounting. But, they were not able to deal with more complex processes, until Artificial Intelligence (AI) came into the picture.

Today, enterprise AI is capable of performing three activities that strictly fall in the human domain: learning, thinking, and directing human actions. Business users are now able to transfer repetitive tasks from human staff to AI automation tools, a powerful transformation. Regardless of the wide impact artificial intelligence can create, people are better at imagining, creating, and directing. They can spend more time on these high-level tasks while AI automation handles the rest.

Here, we will explain how AI is changing business through five real-world examples:

Automating customer interactions

Chatbots are a form of AI, which allows computers to understand human language in its raw form. They provide 24/7 service and are great at acquiring customer information. Eg: If you go to any website, you’re likely to see a chat window pop up. When you call a customer service line, you may be interacting with a voice agent, which is a voice chatbot that uses AI to get results through language. Now, you might have understood why AI is being widely adopted. Although it allows companies to automate and scale customer interactions, they’re not the only way AI helps to automate core business communications.

Intelligent Automation For Service Desk Processes

The IT department is involved in collecting IT requests from customers, employees, and partners. It generates tickets, assigns tasks to IT staff, tracks resolution, and communicates the status with stakeholders. In many industries, service desks receive hundreds of requests per day. AI automation can save a tremendous amount of staff time on these tasks. They can categorize, process, and respond to these requests. Also, they can generate tickets and assign them to the appropriate staff. This streamlining service desk operation leads to greater performance and cost efficiency.

Invoice Data Extraction and Processing

Accounts payable departments are flooded with invoices. Smart RPA bots that use AI identify key information on invoices, irrespective of layout or format. They extract key information and enter that into accounting software and ERPs. Thanks to integrated Business Process Management (BPM) capabilities, it orchestrates work between smart RPA bots and employees to achieve end-to-end process automation for invoicing tasks and more.

Insurance Claims Processing

Every insurance claim involves multiple document checks in all sorts of formats along with complex eligibility checks and data verifications. With AI, the software can check data across documents, automating verification and other tasks associated with claims processing. Intelligent automation also reduces data errors during all these processes and dramatically reduces staff time dedicated to claims processing.

Fraud Detection

AI is also crucial for data mining, or the discovery of useful patterns within extremely large datasets. Predictive analytics involves data mining in order to predict future outcomes, including potential fraud. Take credit card transactions as an example. A bank can train an AI model with datasets of all its normal and abnormal transactions. That AI system can then analyze the data to reveal patterns that suggest fraudulent activity. When similar conditions arise in future transactions, the fraud detection system can notify account holders, asking for verification before processing the charge.

Prepare for the Intelligent Future

AI is perhaps one of the most disruptive technologies for modernizing businesses in today’s digital landscape. Many organizations are trying to use AI in their business for better insights, cost-effectiveness, and deeper customer engagement. However, when it comes to fully implementing AI technologies, there are still many questions to which adopters are seeking answers, such as how to integrate AI into their existing systems, how to get access to data through AI and concerns around security and costs.