Agentic automation & RPA in the automotive
industry: use cases & best practices

As automotive companies need to vet and register dozens of suppliers, which is time-consuming and labor-intensive, they can employ agentic automation and RPA software to perform repetitive administrative tasks:

• Extracting and classifying submitted supplier data, such as tax IDs, banking details, and compliance information, from document scans, emails, and public databases, populating corporate supply chain management, supplier lifecycle management, and ERP software with it, and updating supplier profiles when required
• Detecting missing, inconsistent, or incomplete information for supplier onboarding and sending notifications to procurement managers about the missing data
• Scanning governmental and publicly available databases to perform background checks of potential suppliers
• Generating standard supplier contracts using supplier and company data and ready-made templates

Implementing RPA bots and AI-driven agents to facilitate transportation and logistics workflows can ensure accurate handling of relevant documentation and significantly streamline shipment management:

• Extracting relevant product shipment details, such as the destination and number of SKUs, from a purchase order and entering this data into the transportation management system
• Generating quotes, standardized bills of lading, and customs documents based on order data
• Processing carrier invoices, classifying them, matching them with contract information, and sending them to the appropriate specialist for approval and payment

Auto manufacturers can implement RPA bots and AI agents to facilitate and speed up the vehicle recall process, mitigating safety concerns and preventing legal consequences and litigation:

• Capturing vehicle identification numbers (VINs) from incoming documents and images, identifying the affected cars by scanning manufacturing databases and systems, and distributing recall messages among owners and dealerships
• Scheduling repair or replacement procedures and monitoring their completion statuses across MES, ERP, and work order management (WOM) systems, identifying approaching or missed task deadlines, sending reminders to assigned technicians, and delivering repair notifications to QA managers
• Generating recall reports by consolidating repairs and product data from spreadsheets and internal systems, as well as sending them to regulatory authorities like NHTSA

To help car manufacturers successfully manage an extensive, geographically distributed dealership network, RPA bots and AI-powered agents can automate repetitive tasks across sales, customer support, and financial operations:

• Updating data related to particular dealers across dealer management, ERP, and CRM platforms by processing incoming emails and signed contracts
• Matching dealers’ contact information, dealership licences, certificates of insurance, and financial statements with company policies to determine its completeness and relevance during onboarding
• Tracking dealers’ contract expiration dates and triggering renewal notifications to dealer management specialists
• Processing warranty reimbursement requests from dealers, validating them against company policies and contracts, and sending them to relevant technicians
• Verifying outgoing invoices and payments against purchase orders
• Delivering vehicle repair updates and reports to dealerships

In auto insurance companies, agentic automation and RPA solutions can streamline diverse labor-intensive and error-prone tasks, freeing insurance specialists from manual data handling:

• Collecting policyholder data, such as vehicle accident reports, photos of car damage, and other relevant details, from online portals, apps, and emails, formatting the data, and creating the first notice of loss record in the claims management system
• Browsing public databases to check applicants’ criminal records and creating a report based on the findings for an authorized agent
• Processing claims, detecting inconsistencies in the submitted documents, e.g., mismatched vehicle info or duplicate claims, and triggering a closer investigation if needed
• Verifying compensation eligibility by matching claims data with policy information from the insurance policy management system
• Processing claims payments, sending notifications and emails to clients about the claims processing status, and updating a policyholder’s records across insurance systems

Lenders can optimize the end-to-end loan approval workflow while avoiding financial losses, applying RPA bots and AI agents to the following tasks:

• Collecting and processing large volumes of customer data from loan and lease applications and supporting documents, populating loan forms, and forwarding the information to the loan management system
• Detecting inconsistencies in borrower forms, service contracts, and warranties and triggering alerts to finance teams to rectify the issues
• Sending automated loan status updates to borrowers or dealers via emails or dedicated portals
• Creating customer profiles within automotive CRM software or the customer data platform and updating them with loan approval or denial information

The quality and availability of customer information affect sales operations, marketing campaign effectiveness, and customer service, so applying process automation solutions can prove useful for any business, including automotive companies, in the following tasks:

• Gathering customer data from web forms, dealer systems, and emails, validating and deduplicating customer records, and updating customer-related data within disjointed systems
• Processing customer contracts, records, support tickets, and other documents to extract data necessary for compliance reporting or customer issue resolution
• Tracking expiration dates of diverse customer-related documents, such as purchase and warranty service agreements, NDAs, and liability waivers, and sending timely notifications to relevant specialists and customers about the need to update the contracts