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Use cases of how generative AI can be used in RPA Bots

Based on: Cem Dilmegani Article on Jan10 2024

1. Customer service

RPA bots can create automated workflows in customer service for:

  • Collecting customer information
  • Updating databases
  • Scheduling follow-ups

Simultaneously, customer service centers can use Generative AI models in their workflows to create personalized responses to customer queries, based on each customer’s history and situational context.

The combination will allow a highly personalized, efficient, and scalable customer service operation.

2. Marketing & advertising

RPA can automate some of the marketing operations, like collecting customer data or scheduling marketing campaigns.

Concurrently, generative artificial intelligence tools can create personalized content, like custom-tailored ads or personalized product recommendations based on the collected data.

3. Data analytics & management

RPA can gather and pre-process data, while generative AI could generate synthetic data to augment existing datasets, fill in the missing values, or create data for testing purposes.

This conjunction can streamline the entire process of data analytics and data management, leading to more robust and reliable data analytics outcomes.

4. Healthcare

RPA in healthcare can automate administrative tasks, like scheduling appointments, maintaining patient records, or processing insurance claims.

And intelligent automation technology like generative AI can create synthetic patient data for research without violating privacy laws, as well as generating possible patient outcomes based on their health data.

A health clinic, for example, used RPA and generative AI for complex tasks like predicting patient malnutrition, reducing appointment no-shows, and projecting emergency room visits based on seasonal data.

5. Financial services

RPA in banking and finance can automate data entry, compliance reporting, due diligence, or loan processing.

Generative AI, meanwhile, can generate potential financial scenarios for asset management and risk modeling, improve fraud detection, or provide personalized financial advice to customers.

For example, a bank used AI and RPA to automate its Adverse Media Screening, lowering the number of false positives and improving compliance.

6. Human resources

RPA can automate HR tasks like granting PTOs, scheduling interviews, gathering employee data, or administrating the onboarding process.

Generative AI can assist HR staff by:

  • Creating personalized training material
  • Predicting employee performance based on historical data
  • Simulating responses to various HR policies

7. Retail & ecommerce

RPA can automate tasks related to inventory management, order processing, or CRM management.

In parallel, generative AI can be used to create:

  • Personalized product recommendations
  • Virtual shopping experiences
  • Dynamic pricing models based on real-time market conditions

For example, Chinese researchers used a PPGAN (Personalized Pointer Generative Adversarial Network) model to create short product titles. Their model outperformed conventional models by a click through rate of 5.18% compared to 3.53%.

8. Supply chain management

RPA can create an automation platform where users can track shipments, update inventory data, monitor freight conditions, and generate invoices.

Incorporating generative AI in supply chain management can help create predictive models for demand forecasting, optimize routes for logistics, or provide valuable insights about disruptions by simulating scenarios.

RPA and generative AI in supply chain management can minimize supply delays and optimize responses to unforeseen circumstances.

9. Legal services

Robotic process automation can automate document review, contract analysis, or legal billing.

Generative AI can create legal briefs, simulate different legal scenarios and mock trials for training, or even provide legal advice based on similar previous cases.

10. Manufacturing

RPA in manufacturing could include inventory tracking, quality control, or order processing. Generative AI, on the other hand, can design product prototypes, optimize production processes, or create stress testing scenarios.

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