AI Productivity Mastery: Research, Analysis & Automation

2 days
8:30 a.m. - 4:30 p.m.
Intermediate
Intensive Hands-On Workshop

Artificial intelligence can significantly improve how professionals research information, analyze data, develop reports, create business deliverables, and manage recurring work. Achieving these benefits, however, requires more advanced skills than basic prompting or occasional AI experimentation.

AI Productivity Mastery is an intensive, hands-on course designed to help business professionals develop practical proficiency with AI-powered research, analysis, visualization, and workflow tools.

Participants explore leading AI platforms and learn structured techniques for prompting, conducting in-depth research, organizing knowledge, analyzing spreadsheet data, creating visual outputs, and validating AI-generated work.

Using a progressive business case study, participants apply new skills throughout the course, developing an integrated set of AI-assisted deliverables.

The course concludes with an applied capstone project and a personalized plan for incorporating AI into recurring professional responsibilities.

The emphasis is on developing practical, reusable capabilities without requiring programming expertise.

Who Should Attend / Audience

Business analysts and project managers
Operations and administrative professionals
Finance, reporting, and process improvement professionals
Sales and marketing professionals
Engineers and technical professionals seeking AI-assisted productivity skills
Professionals responsible for research, reporting, analysis, and recurring workflows

Prerequisites

Participants should be comfortable using computers, web-based applications, and spreadsheets.

Previous experience using a generative AI tool is recommended but not required. No programming knowledge is necessary.

Participants should be prepared to work with multiple AI applications during hands-on exercises. Specific software and account requirements will be communicated before the course.

Course Level

Intermediate / Applied AI Productivity

Designed for professionals ready to move beyond basic AI use and develop more sophisticated research, analytical, and workflow capabilities.

Upon completion of this course, participants will be able to:

Evaluate and select AI tools for research, analysis, reporting, and recurring business tasks.
Apply structured prompting techniques, including the CRIT framework, to improve AI-generated results.
Conduct AI-assisted research and evaluate the reliability of supporting sources.
Develop AI-supported knowledge repositories for organizing and synthesizing information.
Use AI-assisted techniques for spreadsheet analysis, data preparation, and business reporting.
Create visualizations, presentations, and analytical business deliverables.
Apply verification and quality assurance techniques to AI-generated information and analysis.
Develop reusable AI projects, task-specific assistants, and structured workflows.
Complete an integrated AI-assisted business project.
Create a personalized plan for improving workplace productivity with AI.

This course can be completed in two days depending upon client customization.

Day 1: AI Foundations, Advanced Prompting, and Research

Module 1: Building Your AI Productivity Toolkit

Understanding the AI tool landscape
Matching AI platforms to business tasks
Comparing research, analysis, and knowledge management capabilities
Understanding privacy, data stewardship, and workplace security
Selecting appropriate tools for practical applications

Module 2: Advanced Prompting for Business Results

Applying the CRIT prompting framework
Using context, roles, and structured questioning
Applying business frameworks such as SWOT and Porter’s Five Forces
Refining AI responses through iterative dialogue
Generating structured outputs for business workflows
Hands-on advanced prompting exercises

Module 3: AI-Assisted Research and Knowledge Management

Conducting in-depth, multi-step research
Exploring AI-powered research platforms
Evaluating sources, citations, and research reliability
Organizing information in AI-supported knowledge repositories
Synthesizing findings from multiple documents and sources
Building a research foundation for the course case study

Day 2: Data Analysis, Visualization, and Quality Assurance

Module 4: AI-Powered Spreadsheet Analysis

Using natural language to analyze spreadsheet information
Cleaning and organizing datasets
Developing formulas and analytical summaries
Exploring pivot tables and data relationships
Performing what-if and scenario analysis
Applying AI to business reporting and decision support

Module 5: Creating Visualizations and Business Deliverables

Transforming research and analysis into business reports
Creating charts, infographics, and visual summaries
Developing AI-assisted presentations
Exploring dashboards and interactive analytical outputs
Introduction to predictive and scenario-based analysis
Communicating analytical findings to business stakeholders

Module 6: Validating AI-Generated Work

Understanding AI limitations and common failure modes
Verifying facts, citations, and calculations
Evaluating AI-generated analysis and recommendations
Cross-checking results using independent methods
Establishing quality standards for AI-assisted deliverables
Applying validation techniques to the course case study

Day 3: Reusable Workflows and Applied AI Productivity

Module 7: Creating Reusable AI Workflows

Identifying recurring tasks suitable for AI assistance
Creating reusable AI projects and task-specific assistants
Organizing persistent instructions and reference information
Exploring workflow automation capabilities
Maintaining appropriate human oversight
Identifying high-value productivity opportunities

Module 8: Applied AI Capstone Project

Integrating research, analysis, and visualization techniques
Completing an AI-assisted business deliverable
Applying quality assurance and validation practices
Reviewing project results and identifying improvements

Module 9: Developing Your Personal AI Productivity Plan

Evaluating current productivity opportunities
Selecting tools and workflows appropriate to individual roles
Establishing measurable productivity goals
Creating a 30-day AI adoption plan
Identifying next steps for continued skill development

Required Software

Participants will need a laptop with a current web browser, reliable internet access, and access to AI tools approved for the training.

The course may use platforms such as ChatGPT, Claude, Perplexity, Google NotebookLM, and Microsoft Excel or comparable spreadsheet applications.

Some advanced research, spreadsheet analysis, project, or workflow features may require paid subscriptions or organizational licenses.

The instructor will confirm required platforms, account setup instructions, and licensing arrangements before class. Participants will not need individual accounts for every tool demonstrated.

No programming software is required.