Prolific AI usage for business professionals: Need Instructor to record training

Hi - We are looking for a prolific AI user in daily office environment with MS365, data analysis, regular research etc. We need them to record training for a course which we are developing as listed below. The task involves fixing any issues and developing very engaging videos. ## AI for Business Professionals A 20-lesson course that teaches business professionals to use generative AI for everyday work — research, analysis, writing, meetings, data, presentations, communication, and workflow automation. It follows a common-skills / role-specific-application model: everyone learns the same capability, but every lab is applied to the learner's own role (Sales, Finance, HR, Marketing, Project Management, IT, or Manager/Executive). The course builds cumulatively toward a capstone, the **AI-Powered Business Decision & Productivity Assistant**, in which learners take a real problem from their job through research → analysis → options → recommendation → communication → action plan. **Structure:** Stage 1 Foundations (1–4) · Stage 2 Professional Work (5–8) · Stage 3 Business Intelligence & Productivity (9–13) · Stage 4 Responsible AI & Advanced Application (14–18) · Stage 5 Capstone (19–20). --- **Lesson 1 — AI for the Modern Business Professional** Establishes what today's generative AI can and can't do, and where the line sits between AI assistance, automation, and human judgment. Learners map 3–5 recurring tasks in their own role and choose their capstone problem. **Lesson 2 — Prompt Engineering for Business Professionals** Teaches structured prompting: context, role, objective, constraints, output format, and examples. Learners build a reusable prompt library for five role-specific tasks. **Lesson 3 — AI for Research** Covers framing research questions, building a research plan, finding sources, and synthesizing findings — plus verifying anything that matters. Produces the evidence base for the capstone. **Lesson 4 — AI for Business Writing** Drafting, restructuring, and adapting tone for different audiences, with a review pass for accuracy and quality. Learners write an internal message, an external message, and an analytical document. **Lesson 5 — AI for Meetings** Preparation, agendas, discussion questions, summaries, and extraction of decisions and action items. Learners run a full AI-supported meeting workflow from prep through follow-up. **Lesson 6 — AI for Document Analysis** Summarizing, comparing, and interrogating dense business documents, and spotting risks or inconsistencies across a set. Learners analyze a document set from their own function. **Lesson 7 — AI for Data Analysis** Preparing business data, asking analytical questions in plain language, finding trends and anomalies, and generating charts — then validating the output. Learners surface at least three decision-relevant insights. **Lesson 8 — AI for Decision Support** A framework for framing decisions: criteria, alternatives, risks, and trade-offs, with AI supporting rather than making the call. Learners produce a decision brief that becomes the capstone backbone. **Lesson 9 — AI for SWOT, Competitive and Strategic Analysis** SWOT, competitor scanning, and trend identification, converted into concrete recommendations rather than observations. Adds strategic evidence to the capstone. **Lesson 10 — AI for Presentations** Building presentation structure, executive narrative, slide content, and speaker notes from existing analysis. Learners create the executive presentation that serves as their final deliverable. **Lesson 11 — AI for Professional Communication** Tailoring tone and detail by stakeholder, and turning complexity into plain language. Learners produce an executive summary, a stakeholder email, a briefing, and talking points. **Lesson 12 — AI for Workflow Automation** Mapping a repetitive workflow, deciding where AI belongs and where it doesn't, and designing human approval points. Learners automate one real role-specific workflow. **Lesson 13 — AI Assistants and Reusable Workflows** Building a persistent, role-specific AI assistant with standing instructions, supporting knowledge, and defined boundaries. The assistant becomes a working component of the capstone. **Lesson 14 — AI for Research, Analysis and Synthesis** Combining external research, internal documents, and structured data into one coherent picture while separating fact from assumption. Output is a business intelligence brief. **Lesson 15 — AI Quality, Accuracy and Verification** Common AI failure modes, detecting hallucinations and unsupported claims, and building review checkpoints. Learners audit and correct a flawed AI-generated analysis. **Lesson 16 — Responsible AI and Business Risk** Privacy, confidentiality, sensitive data, bias, and where human accountability sits. Learners write a risk assessment for AI use in their own role. **Lesson 17 — Building an End-to-End AI Business Workflow** Connecting research, analysis, writing, and communication into one repeatable process with human review built in. Learners build the workflow architecture their capstone runs on. **Lesson 18 — AI-Powered Decision and Recommendation Systems** Combining qualitative and quantitative evidence into a defensible recommendation, with assumptions and uncertainties made explicit. Learners finalize their capstone decision model. **Lesson 19 — Capstone Preparation and Integration** Integrating every prior workflow, validating the AI-assisted work, and closing gaps in evidence. Learners assemble the full capstone package, from research brief through risk assessment. **Lesson 20 — Final Capstone: AI-Powered Business Decision & Productivity Assistant** Learners present an evidence-based recommendation on a real business problem, demonstrating human oversight throughout. They also explain how the workflow could be reused or automated going forward.