Top 10 Ways for Inbox and Document Automation with Generative AI
In today’s fast-paced world, managing an email inbox or a help desk inbox can be an overwhelming task even for most organized teams, especially for businesses that receive a high volume of customer correspondence and document attachments. The need for efficient inbox task automation has become more critical than ever. Fortunately, advancements in artificial intelligence (AI) and generative AI can be used to revolutionize the way we handle emails, tickets, attachments and inbox as a whole. In this article, we will explore the top 10 ways in which generative AI can be used for inbox task automation and document-centric workflow automation.
1. Email and Message Classification and Routing
Generative AI-based solution can classify emails and messages based on content, sender, keywords, and other criteria. This automated classification allows for the creation of rules that route messages to specific folders or team members. For example, important client emails can be automatically sent to the sales team, while general inquiries can be directed to customer support.
In addition, generative AI-based solutions can provide an extra layer of intelligence. For instance, they can analyze historical ticket and inbox data to determine which team or department is best equipped to handle certain types of inquiries. Let’s say a distributor company receives customer emails with subjects like “Product Inquiry” or “Order Status.” Generative AI can learn from past interactions and route such messages to the appropriate department, ensuring faster responses and higher customer satisfaction.
2. Contextualized Message Response Generation
Generative AI can assist in crafting contextually relevant responses to emails and messages. By analyzing the content of incoming messages, AI can suggest or generate replies that are tailored to the sender’s query, thereby saving time and ensuring more accurate communication.
Generative AI can go beyond basic suggestions and provide highly contextual responses. For example, if an email contains specific questions about a product’s features or pricing, the AI can generate accurate responses by drawing information from your knowledge bases, product information system or ordering systems. Moreover, it can consider the sender’s history, such as previous purchases or inquiries, to craft responses that are personalized and tailored to the recipient’s needs.
3. Sentiment Analysis
Understanding the sentiment of incoming emails and messages is crucial for providing appropriate responses. Generative AI can analyze the sentiment behind the content, allowing for prioritization of responses based on the emotional tone of the message. This can improve customer service by addressing negative sentiments promptly.
Sentiment analysis can be further used in generating personalized responses. Because it identifies positive or negative sentiments, it can suggests appropriate responses based on the sentiment detected. For example, if a customer sends an email expressing frustration about a service issue or delayed order, the AI can recommend responses that acknowledge the problem, apologize, and provide potential solutions, considering previous conversations and system data, thus demonstrating empathy and improving customer relations.
4. Conversation and Ticket Summarization
For businesses dealing with a large number of customer inquiries and support tickets, generative AI can summarize the content of ongoing conversations or ticket threads. This summarization provides a quick overview of the issue, making it easier for support agents to respond effectively.
In customer support scenarios, AI-generated summaries of ticket threads can include key details, timestamps, and any actions taken. This condensed overview allows support agents to quickly grasp the history of a conversation, enabling them to provide efficient and informed responses. Furthermore, summaries can be generated for internal team discussions, making meetings and decision-making more effective.
5. Information Extraction from Messages (Ticket Parsing)
For businesses using ticketing systems, AI can extract key information from messages and populate ticket fields automatically. This streamlines the ticket creation process, reducing manual data entry and human error.
AI-powered ticket parsing can go beyond basic data extraction. For example, in an IT support context, it can not only extract information like the user’s name, issue description, and priority level but also identify trends and common problems from historical tickets, helping IT teams proactively address recurring issues.
6. Action Item Extraction
AI can scan emails and messages to identify action items and tasks. This feature helps users prioritize their to-do lists and ensures that important tasks are not overlooked, reducing the risk of missed deadlines and opportunities.
Generative AI can identify action items in emails and messages and create tasks or to-do list entries automatically. For instance, if an email from a client mentions a deadline for a project, the AI can extract this information and add it to a shared project management tool, ensuring that team members are aware of and can act on upcoming tasks.
7. Attachment Classification
Generative AI can analyze and classify email attachments, making it easier to organize and retrieve documents. This is particularly valuable for businesses that deal with various types of attachments, such as invoices, bills, and sales orders in their inbox.
AI can classify attachments based on their content and file types. For instance, it can categorize invoices, receipts, contracts, and resumes. This automated sorting makes it easier to locate specific documents quickly. For example, in a legal IP (Intellectual Property) firm, generative AI can classify and organize patent related receipt and documents, usually handled by IP Paralegal team, ensuring that case-related materials are properly handled and are easily accessible.
8. Attachment Content Reading (Data Extraction) with AI
AI-powered systems can read and interpret the content of attachments, extracting meaningful data. For instance, AI can extract invoice details, amounts, and due dates, allowing for automated payment processing and invoice tracking.
Generative AI can read and understand the content within attachments, providing valuable insights. The information in the message body and attachments can be used jointly to make the right decision or take the desired next step automatically. In the example of an email with an invoice attachment, this information can be used to automate invoice processing, reconciliation, and payment, saving businesses time and reducing errors.
9. PDF and Image OCR (Optical Character Recognition)
OCR technology can be integrated into email and inbox automation systems, enabling the extraction of text from PDFs, scanned documents and images. This is invaluable for digitizing paper documents and making their content searchable and editable.
OCR technology, combined with generative AI, can not only extract text but also interpret it. For instance, it can convert scanned handwritten notes into editable digital text. In an educational setting, this capability can be used to digitize and analyze handwritten student feedback, making it easier for educators to provide personalized guidance.
10. Trigger-based Inbox Workflow Automation
Generative AI can be used along with workflow automation technology to automate inbox workflows based on predefined triggers. These triggers can include actions like the arrival of a new message, the addition of a specific label to a message, or changes in sentiment. By automating workflows, businesses can ensure that responses and actions are initiated promptly.
Generative AI can execute complex workflows based on triggers. For instance, if an email contains a specific keyword or phrase, it can initiate a series of predefined actions, such as sending automated follow-up emails, updating CRM records, or triggering notifications to team members. This level of automation ensures that critical processes are consistently executed and reduces the need for manual intervention.
In summary, incorporating generative AI into these ten aspects of email and inbox automation can significantly enhance productivity, efficiency, and accuracy in managing communications and automating repetitive and daunting work and save valuable times of employees, agents and staff for more customer-focused activities. It’s an exciting time for businesses and teams looking to streamline their email and inbox handling processes.
UpBrains AI: Your Partner in Inbox and Document Workflow Automation
UpBrains AI Copilot is an intelligent full-service inbox automation tool, which is built based on an innovation foundational Gen AI technology. It offers a wide range of AI skills for inbox task automation ranging from intelligent response assistance skills, scanned document and PDF attachment readers for variety of document types such as invoices, bills, receipts, ID documents and more, and an AI-based workflow automation technology which seamlessly integrates with popular email platforms like Front App, Zendesk, and Microsoft Office 365 and Mail. Additionally, it can be easily integrated with external systems and APIs to pull information out of them , send information to them and further enhance automation capabilities. With generative AI at its core, UpBrains AI Copilot is poised to transform the way we manage our inbox and email communications, and document -cetric workflow automation, making it a valuable asset for businesses and teams alike.
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