AI for Business Process Automation

Course Description

AI for Business Process Automation is a practical, application-driven workshop focused on leveraging AI to automate repetitive tasks, optimize workflows, and improve decision-making within modern enterprises. The course covers key concepts such as intelligent document processing, AI-powered chatbots, RPA with AI, NLP-based automation, workflow orchestration, and predictive analytics. Participants will gain hands-on experience using platforms like UiPath, Zapier, n8n, ChatGPT API, Microsoft Power Automate, and custom AI bots to automate essential business tasks like invoice processing, HR onboarding, customer service, and data reconciliation.

Aim

The goal of this course is to equip participants with the skills to streamline enterprise operations using artificial intelligence, enabling smarter decision-making and improving overall business efficiency through automation.

Course Objectives

By the end of the course, participants will be able to:

• Understand how to bridge AI technologies with operational strategy to improve efficiency.

• Gain hands-on experience in building real-time business process automation (BPA) workflows.

• Implement smarter decision-making systems and integrate human-in-the-loop automation.

• Enhance the scalability, speed, and accuracy of business operations through intelligent automation.

• Foster a culture of continuous improvement and innovation in their organizations via automation tools and AI.

Course Structure

Day 1: Introduction to AI-Powered Business Process Automation

Theme: From Manual to Intelligent — Fundamentals of Automation

• Key Concepts

  • What is Business Process Automation (BPA)?

  • Differences between BPA, RPA, and IPA (Intelligent Process Automation)

  • The role of AI in modern enterprise workflows

  • Introduction to tools: Python, OCR (Tesseract), APIs, Google Sheets

• Hands-On

  • Set up Python & Jupyter Notebook for automation tasks

  • Simple automation tasks: Extracting text from PDFs using Tesseract OCR

  • Automating email-to-Google Sheets data entry using Python

  • Using OpenAI or Hugging Face APIs to extract structured information from raw text

• Outcome: Participants will create a basic automation pipeline for document processing and data logging.

Day 2: ML and Predictive Automation for Process Intelligence

Theme: Adding Intelligence to Automation — Forecasting & Classification

• Key Concepts

  • Introduction to machine learning for business processes

  • Predictive analytics for decision-making workflows

  • Overview of ML tools: scikit-learn, pandas, matplotlib

  • Intro to process mining and its applications

• Hands-On

  • Train a simple ML model to predict task duration or order fulfillment times

  • Use decision trees to classify entries (e.g., approve vs. reject)

  • Visualize model performance using basic plots

  • Trigger follow-up actions (e.g., email or notification) based on model output

• Outcome: Participants will integrate ML models into business workflows to automate smarter decision-making processes.

Day 3: Intelligent Agents & Multi-Step Automation Pipelines

Theme: End-to-End Automation Using AI Agents

• Key Concepts

  • Understanding AI agents and their role in business workflows

  • NLP basics for extracting intent and meaning from text

  • Overview of no-code/low-code automation platforms like n8n, Zapier, and OpenAI

• Hands-On

  • Build a simple chatbot or prompt-based assistant using OpenAI

  • Extract and summarize content from email or text using AI

  • Use n8n or Zapier to create an automation chain: Email → Extract info → Store in Google Sheets → Send Slack notification

• Outcome: Participants will complete a guided end-to-end intelligent automation workflow.

Who Should Enrol

• Operations and process improvement professionals looking to enhance efficiency through automation

• Business analysts and automation engineers interested in streamlining workflows

• AI/ML engineers and IT consultants working in automation or digital transformation

• Product managers and digital transformation leads seeking automation solutions for enterprise environments

• Entrepreneurs and startup teams exploring AI-based automation for scalable operations