Robotic Process Automation

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Generative AI and RPA: A Powerful Combination for Automation

Ed Garabedian

Like many of you, I am fascinated by the explosion of AI, specifically generative AI. It is overwhelming. The amount of new products, services, and releases feels like a tidal wave and challenging to digest. A recent example is right here on the linkedin platform: https://techcrunch.com/2023/10/03/linkedin-goes-big-on-new-ai-tools-for-learning-recruitment-marketing-and-sales-powered-by-opena

In this vein, I have been curious about real, concrete use cases that can help connect all this whirlwind of AI news and hype to actual automation ROI and practical use cases.

Generative AI and robotic process automation (RPA) are two of the most transformative technologies in business today. Generative AI can create new content and data, while RPA can automate repetitive tasks. Combined, these two technologies can create a powerful force for automation, efficiency, and innovation.

Here are some realistic and impactful examples of how generative AI can be combined with RPA right now:

  • Automated customer service: Generative AI can be used to create chatbots that can understand and respond to customer queries in a natural and engaging way. RPA can automate tasks such as routing customer tickets, sending follow-up emails, and updating customer records. Together, these two technologies can provide 24/7 customer support at a fraction of the cost of traditional methods.

  • Automated sales and marketing: Generative AI can create personalized sales and marketing materials, such as email campaigns, social media posts, and website landing pages. RPA can automate tasks such as sending emails, scheduling meetings, and updating CRM systems. Together, these two technologies can help businesses to generate more leads, close more deals, and increase revenue.

  • Automated product development: Generative AI can generate new product ideas, design concepts, and marketing materials. RPA can automate market research, competitive analysis, and product testing tasks. Together, these two technologies can help businesses to develop new products more quickly and efficiently.

  • Automated financial management: Generative AI can create financial reports, forecasts, and budgets. RPA can automate data entry, account reconciliation, and invoicing tasks. Together, these two technologies can help businesses to improve their financial accuracy and efficiency.

  • Automated IT support: Generative AI can create chatbots to answer IT support questions and resolve common issues. RPA can automate tasks such as password resets, software updates, and hardware troubleshooting. Together, these two technologies can help businesses to reduce IT costs and improve employee productivity.

Here are some links to publicly published use cases from real businesses using RPA and generative AI today:

  • Autodesk: Autodesk uses generative AI to help customers design and manufacture products more efficiently. For example, Autodesk's Generative Design platform can automatically generate thousands of design options based on customer input and constraints.

  • Capital One: Capital One uses generative AI to improve its fraud detection and customer service capabilities. For example, Capital One's AI-powered chatbot can answer customer questions and resolve issues quickly and efficiently.

  • JPMorgan Chase: JPMorgan Chase is using generative AI to automate trading and risk management tasks. For example, JPMorgan Chase's AI-powered system can automatically generate trading signals and monitor risk exposure.

These are just a few examples of how generative AI and RPA can be combined to automate tasks and processes in various industries. As these technologies continue to develop, we can expect to see even more innovative and transformative use cases emerge in the years to come.

Here is a more detailed example of how generative AI and RPA could be used together to automate a customer service process:

  1. A customer visits a company's website and clicks the "Live Chat" button.

  2. A chatbot powered by generative AI greets the customer and asks them how they can help.

  3. The customer describes their issue to the chatbot. The chatbot uses generative AI to understand the customer's issue and generate a response.

  4. If the chatbot can resolve the customer's issue, it does so. Otherwise, the chatbot routes the customer to a human customer service representative.

  5. The human customer service representative uses RPA to access the customer's account information and view their previous interactions with the company.

  6. The human customer service representative uses this information to provide the customer with a personalized and efficient solution to their issue.

In this example, generative AI is used to understand the customer's issue and generate a response. RPA is used to access the customer's account information and view their previous interactions with the company. This combination of technologies allows the human customer service representative to provide the customer with a more personalized and efficient experience.

Check out these RPA vendor links to learn how they are rapidly adding to their tools and services to help their RPA customers tap into this powerful combination:

Generative AI and RPA are two powerful technologies that can automate a wide range of tasks and processes. Combining these two technologies can improve efficiency, productivity, and customer service.

Stay curious, share what you learn, and we can help each other survive and thrive through this tsunami of a paradigm shift. ;)