Course Overview for AI Digital Literacy and Workplace Automation Skills

This intensive, pragmatically focused program is engineered to elevate the baseline digital competencies of the modern workforce. “AI Digital Literacy” transcends basic software operation; it demands the ability to critically evaluate AI outputs, interact securely with machine learning models, and identify opportunities to automate routine digital labour. This course demystifies the convergence of Generative AI and everyday workflow automation concepts. Participants will transition from manual task executors to digital orchestrators, learning how to conceptually map repetitive administrative burdens and understand how automated, AI-enhanced systems can resolve them.

Who Should Attend

Cross-Functional Knowledge Workers, Operations Staff, and Administrative Professionals

Training Outcomes

Upon successful conclusion of this program, participants will possess the competency to:

• Critically analyse and verify the outputs of artificial intelligence to ensure operational accuracy.
• Identify routine, repetitive tasks within their daily workflows that are prime candidates for digital automation.
• Understand the mechanical logic of “No-Code” platforms (Triggers, Conditions, Actions).
• Construct, test, and deploy basic automated workflows to eliminate manual data entry and routine communications.
• Safely integrate generative AI capabilities into automated sequences to handle complex, unstructured data.
• Maintain rigorous adherence to corporate cybersecurity, data privacy, and ethical AI usage standards.

Methodology

The training is delivered as a highly interactive, physical workshop utilizing a “concept-to-application” pedagogical model. Theoretical frameworks regarding digital literacy and algorithmic bias are reinforced through practical, guided exercises. To maximize the efficiency of a 1-day session, complex automation building is replaced with high-impact live demonstrations and conceptual process-mapping exercises. This ensures participants understand the logic and potential of automation without being overwhelmed by software mechanics. The environment prioritizes safe, compliant experimentation and strategic group discussion.

Course Content

Module 1: The New Digital Baseline: AI Literacy

• Deconstructing the modern digital ecosystem: The shift from static software to dynamic, intelligent systems
• Defining AI Digital Literacy: Comprehension, critical analysis, and ethical application
• The anatomy of AI: Differentiating between search engines, predictive algorithms, and generative models
• Cultivating an “Automation Mindset”: Learning to identify systemic friction and repetitive digital labour

Module 2: Critical Evaluation and AI Interaction

• Best practices for querying and interacting with Large Language Models
• The imperative of critical thinking: Identifying AI hallucinations, logical fallacies, and algorithmic bias
• Fact-checking and verification strategies for AI-generated outputs
• Guided Exercise: Evaluating and correcting flawed AI analyses against raw data sets

Module 3: Foundations of Workplace Automation

• Introduction to “No-Code” and “Low-Code” automation paradigms
• The core architecture of an automated workflow: Triggers, Conditions, and Actions
• Overview of accessible automation platforms (e.g., Microsoft Power Automate, Google Workspace automations)
• Translating manual effort into digital logic

Module 4: Synergising AI with Digital Automation

• Moving beyond chatbots: The concept of integrating AI logic directly into automated pipelines
• Conceptual Use Case 1: Intelligent Routing: How AI sentiment analysis categorises and routes communications
• Conceptual Use Case 2: Data Extraction: Pulling structured action items from unstructured meeting transcripts
• Conceptual Use Case 3: Automated Drafting: Triggering AI to draft preliminary responses based on dynamic data

Module 5: Digital Governance, Security, and Ethics

• Understanding the boundaries of corporate data privacy and intellectual property
• Identifying and protecting Personally Identifiable Information (PII) and sensitive corporate metrics from public AI models
• Establishing individual accountability in an automated workplace (The “Human in the Loop” imperative)
• Adhering to organisational IT security protocols when building custom automations

Module 6: Practical Demonstration: Anatomy of a Simple Workflow

• Live Instructor Demonstration: Walking through the execution of a foundational automation (e.g., automatically routing specific email attachments to a secure cloud drive and generating an AI summary in a team chat channel
• Deconstructing the logic: Visualizing the flow of data from the initial trigger to the final automated action
• Interactive Group Exercise: “Whiteboarding the Workflow.” Participants map out a repetitive daily task using the Trigger/Condition/Action framework without writing any code or utilizing software
• Strategic discussion on defining requirements to hand off to IT or operations teams for actual building