Top 25 Use Cases / Examples of Intelligent Automation in 2024

Traditional automation approaches can be effective in simple tasks but they often rely on rigid, pre-defined rules and are limited in their ability to adapt to changing circumstances. This can lead to inefficiencies and errors, especially when dealing with complex tasks or data.

Intelligent automation combines the speed and efficiency of traditional robotic process automation (RPA) with the adaptability and decision-making capabilities of artificial intelligence (AI). By using AI algorithms to analyze data and make decisions, intelligent automation systems can learn and adapt to changing circumstances, resulting in more accurate and efficient processes.

In this article, we’ll explore 25 use cases, examples, and applications of intelligent automation in different business functions and industries.

Use cases in common business activities and functions

1. Data extraction

By leveraging AI techniques such as machine learning and NLP, intelligent bots can go beyond traditional OCR technology and extract unstructured data from PDFs, images, or handwritten documents. Intelligent bots leverage AI to understand the context of the document, reduce the noise in documents, and improve their accuracy as they extract data.

Feel free to check our article on intelligent document processing for a more detailed account.

2. Data entry and update

Bots can integrate company systems and can be programmed to update databases in different business functions such as HR, customer services, or sales. Bots can extract data from customer service interactions, emails, reports, enterprise applications, etc. to update information such as:

• Employee personal information, payments, PTOs,
• CRM data such as customer information, purchases,
• Logistics data, including shipments, inventory, and delivery.

Customer services

3. Interacting with customers

Intelligent bots with conversational AI capabilities can interact with customers throughout the process, answer FAQs, make recommendations, provide self-service tools such as appointment scheduling or order processing, collect customer feedback, and report customer complaints.

4. Customer onboarding

AI-powered bots can streamline the customer onboarding process by:

• Guiding customers throughout the process,
• Collecting documents from customers,
• Extracting data from documents and entering it into company systems,
• Verifying provided information.

HR

5. Recruitment

NLP-powered bots can increase the efficiency of the recruitment process by:

• Scraping data from recruitment websites to identify potential candidates,
• Gathering candidate resumes,
• Screening resumes by comparing candidate information with job requirements,
• Sending emails to candidates according to their results.

6. Employee onboarding

Employee onboarding can be repetitive and time-consuming, but it is a critical process for employee experience. Intelligent bots can coordinate onboarding tasks across different departments, provide a more personalized onboarding experience, and streamline the onboarding process by:

• Creating user accounts for the tools used within the company and delivering the credentials to new hires,
• Granting access to files and applications according to new employees’ roles,
• Sending relevant onboarding documents to employees and answering FAQs.

7. Payroll processing

AI-powered bots can automate repetitive and error-prone payroll processing tasks such as recording overtime, keeping track of clock-in and clock-out information, and calculating commissions. You can also check our article on payroll automation.

For more examples, feel free to check our article on the use cases of intelligent automation in HR.

Sales & marketing

8. Price optimization

Intelligent bots can help you set optimal prices for your products and services by analyzing:

• Supply and demand changes,
• Customer data such as demographics or spending habits,
• Historical data and market trends,
• Your competition’s prices.

9. Bid adjustment

Marketing teams adjust bids on digital advertising platforms to show ads more or less frequently depending on factors such as time or audience’s location, age, or device. AI-powered bots can significantly improve the bid adjustment process by analyzing numerous other factors affecting sales and automatically adjusting bids.

10. Lead nurturing

The lead nurturing process includes tasks such as lead identification, lead scoring, and sending customized proposals to qualified leads. Intelligent bots can collect additional information about identified leads from public sources, assess them and assign them a score according to an algorithm, and automatically send customized proposals to qualified leads.

11. Order-to-cash (O2C)

Order-to-cash, or order management, is a multistep process that affects customer satisfaction. Intelligent bots can help businesses automate O2C processes by:

• Capturing order and customer data and issuing invoices,
• Sending automatic emails that contain payment links,
• Recording sales on the company’s books.

Feel free to check our article on O2C automation.

Finance & accounting

12. Accounts receivable (AR) / Accounts payable (AP) automation

Intelligent automation can help businesses reduce errors during AR and AP processes and prevent miscalculations and delayed payments.

For accounts receivable processes, AI-powered bots can keep track of vendor data and transactions, extract data from invoices, and cross-check invoices against purchase orders. By using fraud detection algorithms, they can also check for fraudulent documents.

For accounts payable processes, bots can auto-generate invoices, keep track of days-sales-outstanding (DSO), process payments, and reconcile balance sheets after the payments.

Feel free to check our articles on accounts payable (AP) automation and accounts receivable (AR) automation.

13. Financial reporting

AI-powered bots can automate the financial report generation process by extracting data from business systems and relevant documents, performing necessary data manipulations, assembling reports in designated formats, and sending them to relevant stakeholders based on the content.

You can check our article on intelligent automation in finance & accounting for more examples.

Industry-specific use cases

Healthcare

14. Appointment scheduling

Bots with conversational AI capabilities can enable self-service patient appointment scheduling by interacting with patients about their health problems, providing available time slots for different physicians, and letting patients set, reschedule, and cancel appointments. Bots can also reduce no-shows by sending reminders to patients.

15. Health insurance processing

Intelligent bots can undertake time-consuming and error-prone health insurance processing tasks such as preauthorization and claims processing, reducing healthcare insurance fraud and improving customer satisfaction with faster claims processing.

You can check our article on intelligent automation in healthcare for more.

Financial services & banking

16. Know your customer (KYC)

Financial institutions can reduce the manual work involved in KYC processes using intelligent automation. Intelligent bots can extract data from customer documents, validate the information, identify risk areas, and send the cases to relevant staff in which human decision-making is necessary. Using intelligent automation, banks can speed up KYC processing times, reduce error rates, and improve regulatory compliance.

17. Loan processing

Intelligent bots can extract data from customers’ documents, prepare due diligence by combining this information with other documents, and assign a credit score for each loan application. Leveraging AI-powered automation can improve loan decisions and reduce the manual paperwork during loan application processing.

18. Anti-money laundering (AML)

AI-powered bots can conduct name screening by comparing customers’ information with watchlists, monitor transactions to detect suspicious activities, and reduce the manual work during customer offboarding.

Feel free to check our article on intelligent automation in the financial services and banking industry.

Insurance

19. Underwriting

Intelligent automation can help insurers better price the risk and improve underwriting processes by:

• Extracting data from application documents,
• Consolidating relevant data from external and internal sources,
• Use ML models to offer a premium.

Claims processing

Claims processing is a labor-intensive process, and efficient claims processing is important both in terms of profitability and customer retention: 87% of customers say effective claims processing influences their decision to choose an insurer. AI-powered automation can accelerate the document processing with NLP-backed document extraction and improve other core claims processes such as:

20. First notice of loss (FNOL): Intelligent bots can guide policyholders after a loss to take pictures or videos, submit relevant information, etc., and enter this information into company systems.

21. Fraud detection: Bots can leverage AI algorithms to detect fraudulent claims.

For more, feel free to check our article on intelligent automation in insurance.

Retail

22. Inventory management

Retailers can prevent stockouts and waste by leveraging intelligent automation. Intelligent bots can use AI/ML models and historical sales data to estimate the optimum inventory levels for different products, in different places and times.

23. Returns processing

Returns management is important for retailers as it affects customer retention: 96% of customers whose returns experience went well stated that they would shop from the retailer again. Intelligent bots can reduce manual work by collecting necessary information from customers, guiding them during their return process, sending status notifications, and updating inventory databases.

You can check our article on intelligent automation in retail for more use cases and examples.

Manufacturing

24. Predictive maintenance

Intelligent bots can be integrated with sensors and IoT devices connected to machinery. As a result,  manufacturers can keep track of the health of their equipment in real-time, predict machine failures, set and update maintenance schedules, and alert staff when maintenance is required.

We have a dedicated article on predictive maintenance, feel free to check it for a more comprehensive account.

25. Bill of materials (BOM) creation

Bots with intelligent document processing capabilities can standardize bill of materials creation, generate BOM by extracting data from documents, and alert staff in case of missing information. This can help manufacturers reduce human errors resulting in delayed production and product recalls.

You can also check our article on intelligent automation in manufacturing for more use cases.

For more on intelligent automation

Feel free to check our related articles on intelligent automation:

• RPA vs Intelligent Automation: Which is the Right Tool for You?
• Intelligent Automation & Hyperautomation: What’s the difference?
• Top 6 Intelligent Automation Tools & Solutions

You can also explore our data-driven list of intelligent automation solution providers. If you have other questions, we can help: