AI Fundamentals 2026: Safe AI Skills for Work

Explore how multimodal ai processes images, videos, and text, generate art and code, and empower nontechnical users to automate tasks with vibe coding.

Understand four AI integration patterns in business: enhance existing products, create AI native offerings, automate formerly manual tasks, and gain insights for smarter decisions.

Discover how AI-assisted workflows boost productivity by accelerating research, analysis, drafting, and presentation tasks; save time, reduce costs, and enable teams to scale and stay competitive.

Use company-approved ai tools and follow your team's ai guidelines to ensure responsible handling of data. Avoid shadow ai by never using personal or free ai accounts for work tasks.

Learn how large language models are probability-based pattern recognizers, why they hallucinate, and how generative ai raises copyright and plagiarism concerns while producing text, images, or code.

Explore how ai uses pattern recognition and probabilities to predict the next word and generate text or images, then compare it with human learning through touch, senses, and feedback.

Test ideas by running a simple prompt three times through ChachiPT to explore why a generative ai doesn't always give the same answer and compare results.

Uncover common ai misconceptions and fears by clarifying that ai recognizes patterns, not human understanding, and emphasize that modern tools are accessible to everyone, not just technicians.

Explore how AI agents differ from large language models, with agents planning and acting to complete tasks—like querying data and sending email—while LLMs generate text and answers.

The lecture demonstrates using Claude’s Chrome plugin to act as an agent that searches London hotels for June dates, presents a plan, and guides booking up to checkout.

Showcase ChatGPT agent mode to book a hotel in London on June 3–6 via booking.com, with integrations to Google Drive, Gmail, and calendar.

Explore how an AI agent in Google AI Studio creates a plan to execute tasks with tools, builds code, outputs a web app, and contrasts with live language models.

Explore responsible AI use in the workplace by examining risks of AI misuse, ethics, bias, accountability, and human oversight, while understanding copyright, intellectual property, and the EU AI Safety Act.

Explore real-world ai missteps and their consequences, from data leaks and misgoverned chatbots to bias and privacy concerns. Learn strategies for safe, governed ai use at work.

Explore a three-tier security framework for AI assistants: public tier for general use, enterprise tier with encryption and RAG for internal data, and on-premise tier for fully private, controlled environments.

Explore tier 2 enterprise-grade AI tools with zero data retention, encrypted communication, and GDPR compliance, designed to keep work data within a company-controlled ecosystem.

Practice spotting sensitive work data in prompts and selecting the right AI tool. Review ten workplace scenarios to decide between work, personal, or no AI tool, pausing to check context.

Audit a black box resume screening tool to reveal how training data and features like education, experience, hobbies, and zip code embed bias in hiring.

Explore risks of over-relying on AI, including loss of human skills and decision visibility, and assess continuity, explainability, and regulatory considerations like GDPR and the EU AI Safety Act.

Explore eu ai act and the four risk levels, prohibited, high, limited, and minimal, along with examples and the role of transparency for ai systems under ai safety act.

Regulators require high-risk AI to conduct risk management and keep a risk register. Maintain technical documentation, ensure meaningful human oversight, and test for accuracy and bias with evidence.

Learn to tailor prompts by task complexity, provide clear outputs, and break complex requests into stages with company context, guiding the AI like a new hire.

Explore a practical template for effective prompting, including role, task, limits, templates, and examples, and learn how these elements improve output through studies and practical tips.

Context provides AI with the environment, background information about your company, industry, and system to avoid generic results; craft prompts for an internal policy in a regulated financial services company.

Use good and bad examples to guide tone, format, and writing style through few-shot prompting, and place important information at the start and end of prompts to boost accuracy.

Explain pseudonymization as a data security technique that scrambles sensitive information using a secure key table and cryptography, enabling masking with controlled access and later retrieval.

Explore how chat history builds user context in memory for large language models, and how to manage memory in personalization and data controls to protect your information.

Review key prompt elements in action, from meta-prompting to memory settings, and see how they shape outputs, then explore personalized large language models, custom GBTs, and co-pilot agents for automation.

Learn to personalize large language models by creating custom GPTs and copilot agents, understanding prompts from tokens to output, and tailoring tools like Google Gemini Gems to your needs.

Understand how prompts, instructions, and guardrails form a mega prompt. Learn how memory, knowledge bases, and retrieval augmented generation enrich outputs within the context window for safe, relevant results.

Demonstrates building apps with Google AI Studio, contrasts AI agents with large language models through planning and tool use, and showcases a bedtime story app with Gemini-powered outputs.

Automate document analysis across folders with a prompt in n8n, producing a catalog of title, summary, key information, risks, and sensitivity, populated into a Google Sheet.

Create an automation chain for a repetitive, multi-step workflow using AI tools, then map steps, choose a task, test the workflow, and document what it does and the time saved.

Explore how Google Gemini integrates across Google Workspace, including Docs, Sheets, Drive, Calendar, and Gmail, to act as a virtual assistant while understanding its work context limitations.

Read Google Drive, list files, and generate a content summary with risks and sensitivity; export to sheets is possible, but editing is not.

Learn how Gemini reads Gmail, summarizes emails and Google Drive attachments, and assists with drafting replies, while keeping you in the loop and noting update limitations.