The AI Basics and Applications in BPO & Finance Tasks Training Course is a practical, beginner-friendly program designed to introduce participants to Artificial Intelligence (AI), Generative AI, and their applications in business process outsourcing (BPO), shared services, accounting, and finance-related operations.
The course focuses on how AI tools can support everyday workplace tasks such as drafting and improving business communications, summarizing documents, processing and organizing information, analyzing financial and operational data, preparing reports, assisting with customer interactions, documenting processes, and automating repetitive tasks.
Participants will also develop practical prompting skills for working effectively with Generative AI tools while learning the importance of data privacy, information security, accuracy, human review, and responsible AI use. BPO and finance-oriented exercises are incorporated throughout the course to help participants translate AI concepts into practical workplace applications.
Duration 3 Days – 21 hrs.
Objectives
- Explain the basic concepts of Artificial Intelligence, Machine Learning, and Generative AI.
- Identify appropriate AI applications within BPO, shared services, accounting, and finance operations.
- Understand the capabilities and limitations of commonly available AI tools.
- Write clear and effective prompts for common workplace tasks.
- Use AI to draft, rewrite, summarize, classify, and organize business information.
- Apply AI to customer service and back-office BPO activities.
- Use AI to assist with finance, accounting, reconciliation, reporting, and analytical tasks.
- Use AI to analyze structured and unstructured business information.
- Apply AI to improve reports, presentations, emails, and business communications.
- Identify repetitive processes that may benefit from AI-assisted automation.
- Verify and validate AI-generated information before using it for business decisions.
- Recognize privacy, confidentiality, security, compliance, and ethical considerations when using AI.
- Develop practical AI-assisted workflows that improve productivity while maintaining appropriate human oversight.
Target Audience
- BPO and shared services employees
- Customer service and contact center personnel
- Back-office operations staff
- Finance and accounting personnel
- Accounts Payable and Accounts Receivable teams
- Billing and collection personnel
- Financial reporting staff
- Finance operations and transaction processing teams
- Business process associates and analysts
- Operations supervisors and team leaders
- Quality assurance personnel
- Administrative and support staff
- Business analysts
- Process improvement teams
- Managers responsible for BPO or finance operations
- Employees interested in applying AI to their daily workplace tasks
Prerequisites
- Basic computer literacy
- Familiarity with common office productivity applications
- Basic understanding of business processes and workplace documentation
- Familiarity with BPO, accounting, finance, or administrative processes is helpful but not mandatory
- Access to an approved Generative AI platform for practical exercises, where available
Course Outline
Day 1 – AI Fundamentals and Practical Generative AI Skills
Module 1: Introduction to Artificial Intelligence
- What is Artificial Intelligence?
- AI, Machine Learning, Deep Learning, and Generative AI
- Traditional automation versus AI-powered automation
- Understanding Large Language Models (LLMs)
- How Generative AI produces responses
- Common types of AI tools used in business
- Current capabilities and practical limitations of AI
- Understanding AI hallucinations and inaccurate outputs
- AI as a workplace assistant versus human decision-making
Module 2: AI Applications in BPO and Finance
- AI trends in BPO and shared services
- AI applications in customer service
- AI-assisted back-office processing
- Document and information processing
- AI applications in accounting and finance
- AI-assisted reporting and analysis
- Intelligent automation of repetitive processes
- Identifying suitable AI use cases
- Tasks that should remain under human control
Module 3: Fundamentals of Prompt Engineering
- Understanding prompts and AI instructions
- Anatomy of an effective prompt
- Providing clear context and objectives
- Defining roles, tasks, and expected outputs
- Providing constraints and business requirements
- Specifying output formats
- Using examples to guide AI
- Prompt refinement and iterative prompting
- Asking follow-up questions
- Common prompting mistakes
Module 4: AI for Everyday Workplace Productivity
- Drafting professional emails
- Rewriting and improving communications
- Adjusting tone and writing style
- Summarizing long documents
- Extracting important information
- Creating meeting summaries
- Generating action items
- Creating templates and checklists
- Organizing unstructured information
- Preparing reports and presentation content
Day 2 – AI Applications for BPO and Finance Tasks
Module 5: AI for BPO and Customer Service Operations
- AI-assisted customer communication
- Drafting customer responses
- Creating response templates
- Summarizing customer interactions
- Classifying customer concerns
- Identifying customer intent
- Creating FAQ and knowledge-base content
- AI-assisted ticket and case summarization
- Sentiment and feedback analysis
- Escalation summary preparation
- Quality assurance support
- Creating call or interaction summaries
Module 6: AI for Back-Office and Shared Services Tasks
- Document summarization and classification
- Extracting information from business documents
- Converting unstructured information into structured formats
- Creating standard operating procedure drafts
- Preparing process documentation
- Generating checklists and work instructions
- Comparing documents and identifying differences
- Organizing transaction-related information
- AI-assisted data validation
- Supporting repetitive administrative processes
Module 7: AI Applications in Accounting and Finance
- Practical AI use cases in finance
- AI-assisted Accounts Payable tasks
- AI-assisted Accounts Receivable tasks
- Invoice and transaction information extraction
- Supporting reconciliation activities
- Expense categorization
- Variance explanation assistance
- Budget versus actual analysis
- Financial report summarization
- Management reporting assistance
- Drafting financial commentary
- Identifying unusual transactions for further review
- AI-assisted financial research and information organization
- Human validation of financial outputs
Module 8: AI-Assisted Data Analysis and Reporting
- Preparing data for AI-assisted analysis
- Asking AI questions about business data
- Identifying trends and patterns
- Categorizing and grouping information
- Creating summary tables
- Generating business insights
- Explaining numerical results in business language
- Developing executive summaries
- Creating management report narratives
- Turning analysis into recommendations
- Verifying calculations and AI-generated interpretations
Day 3 – Automation, Responsible AI, and Workplace Application
Module 9: AI and Process Automation
- Understanding AI-assisted automation
- AI versus traditional workflow automation
- Identifying repetitive and rule-based tasks
- Mapping current business processes
- Identifying AI intervention points
- Combining AI with workflow and RPA concepts
- Document processing workflows
- Email and communication workflows
- Reporting and information-processing workflows
- Human-in-the-loop processes
- Selecting appropriate tasks for automation
Module 10: Responsible AI, Data Privacy, and Information Security
- Responsible use of AI in the workplace
- Data privacy considerations
- Confidential and sensitive business information
- Customer and employee information
- Financial data confidentiality
- Personally identifiable information
- Risks of entering corporate data into public AI platforms
- Organizational AI policies
- Bias and fairness
- Intellectual property considerations
- AI hallucinations and misinformation
- Maintaining human accountability
Module 11: Validating AI-Generated Outputs
- Why AI output requires verification
- Fact-checking AI responses
- Validating numerical and financial information
- Identifying unsupported assumptions
- Reviewing calculations
- Detecting incomplete or misleading answers
- Cross-checking against source documents
- Maintaining auditability
- Human review and approval
- Establishing quality-control checkpoints
Module 12: Building Practical AI Workflows for BPO and Finance
- Selecting a real-world task
- Defining the business objective
- Breaking the task into workflow steps
- Identifying appropriate AI assistance
- Designing reusable prompts
- Defining required input information
- Establishing output requirements
- Adding validation checkpoints
- Incorporating human review
- Measuring productivity improvements
- Developing reusable AI-assisted workflows
Module 13: Practical BPO and Finance Use Cases
- Customer inquiry response and summarization
- Customer feedback classification
- Business email drafting
- Document summarization and information extraction
- Invoice information organization
- Transaction categorization
- Reconciliation support
- Variance explanation
- Financial report summarization
- Management report preparation
- Process documentation
- SOP and checklist generation
- Operational data analysis
- Creating actionable recommendations from business information
