The AI-Powered Workplace: Driving Efficiency with Generative AI

Transform the Way You Work with AI

The AI-Powered Workplace: Driving Efficiency with Generative AI is a hands-on, practical AI training program designed for professionals who want to leverage AI for productivity, automation, and decision-making.

Advance Your Career with AI Expertise

AI is transforming industries—those who know how to use it will have a competitive edge. The AI-Powered Workplace: Driving Efficiency with Generative AI gives you the skills, tools, and confidence to integrate AI into your workflow, helping you to work smarter, faster, and more efficiently.

  • 100% Online, Live Instructor-Led Sessions
  • No Technical Background Required
  • Hands-On AI Applications for Real-World Tasks
  • Certificate of Completion Recognizing Your AI Expertise

Who Should Enroll?

This program is designed for non-technical professionals looking to harness AI to improve productivity and decision-making, including:

  • Business Leaders & Managers
  • Government & Public Sector Professionals
  • Educators & Academic Administrators
  • Entrepreneurs & Nonprofit Leaders

No prior AI experience is needed—this course is about practical application, not programming.

Why Choose This Program?

  • Immediate AI Skills You Can Use – No theory, just practical AI applications.
  • Designed for Professionals, Not Tech Experts – AI training tailored to the workplace.
  • Networking & Expert Guidance – Engage with industry leaders & AI practitioners.

Course Overview

Key Topics:

  • What generative AI can and cannot do well in current workplace settings.
  • How to choose among ChatGPT, Claude, Gemini, Copilot, and related tools based on the task.
  • The data line: public, internal, sensitive, and restricted material.
  • CRAFT prompting, iteration, and verification.
  • Preview of the autonomy ladder: chat, workflow, assistant, agent, automation.

Live Demo: The same safe workplace task across multiple AI tools, with a verification pass.

Hands-On Activity: Repair a weak prompt, run it in a tool of choice, and identify what still needs human checking.

Key Topics:

  • Moving from single prompts to repeatable work sequences.
  • Meeting prep, meeting notes, report drafting, email drafts, summaries, and follow-up plans.
  • Audience-specific communication for supervisors, board members, clients, colleagues, and public audiences.
  • Using AI output as the input for the next step without losing judgment or accuracy.

Live Demo: A messy request becomes a structured analysis, draft communication, and follow-up checklist.

Hands-On Activity: Map one recurring task into a reusable workflow and test at least two steps.

Key Topics:

  • Custom GPTs, Gemini Gems, Claude Projects, project knowledge, and reusable instruction packets.
  • When to use a prompt, a project, a custom assistant, or a skill-like playbook.
  • How to give AI role, audience, examples, tone, files, and output rules once instead of repeating them.
  • How memory, project files, connected apps, and assistant instructions differ.

Live Demo: Build a role-specific assistant or project for a real workplace use case.

Hands-On Activity: Create or outline a custom assistant for a recurring task, then test and improve it.

Key Topics:

  • Using AI with spreadsheets, surveys, PDFs, reports, meeting transcripts, public web sources, and video transcripts.
  • Anonymizing data before analysis when the tool or account is not approved for sensitive material.
  • Generating executive summaries, dashboards, charts, infographics, and decision briefs.
  • Checking source citations, calculations, graphs, and claims before relying on the output.

Live Demo: A safe dataset or document packet becomes an analysis, visualization, and decision-ready summary.

Hands-On Activity: Choose a safe document or dataset and produce a short, source-backed insight.

Key Topics:

  • The difference between chat, workflow, assistant, agent, and automation.
  • Built-in agents and app-native assistants across ChatGPT, Gemini, Claude, Microsoft 365, and Google Workspace.
  • Codex and Claude Cowork as supervised artifact builders for non-technical professionals.
  • Permission boundaries, source boundaries, data classification, approval points, verification checks, and stop conditions.

Live Demo: Supervised agent tasks that research, organize, draft, build, or verify a work product.

Hands-On Activity: Write an agent task brief for a real task, including what the AI may do and what the human must approve.

Key Objectives:

  • Participants present a real AI-enabled work product or implementation plan.
  • Acceptable capstones include reusable workflows, custom assistants, project spaces, source-backed reports, dashboards, prototypes, and supervised-agent plans.
  • The showcase emphasizes practical value, responsible use, verification, and what the participant will keep using after the course.

Live Showcase: Participants demonstrate their AI workflow or artifact.

Final Deliverable: A short project summary, workflow, assistant brief, analysis artifact, prototype, or implementation plan.

Program Details

  • Format: 100% Online – Live* on Zoom featuring instruction and hands-on exercises
  • Duration: Six weeks, including a Capstone Project
  • Winter 2027 Start Date: Wednesday, January 13, 2027
  • Winter 2027 Session Meeting Dates and Times:
    • Wednesday, January 13, 2027 – 6:00-8:00PM
    • Wednesday, January 20, 2027 – 6:00-8:00PM
    • Wednesday, January 27, 2027 – 6:00-8:00PM
    • Wednesday, February 3, 2027 – 6:00-8:00PM
    • Wednesday, February 10, 2027 – 6:00-8:00PM
    • Wednesday, February 24, 2027 – 6:00-8:00PM
  • Office Hours:
    • Monday, January 18, 2027 — 2:00-3:00 PM
    • Tuesday, January 26, 2027 — 2:00-3:00 PM
    • Monday, February 1, 2027 — 2:00-3:00 PM
    • Monday, February 8, 2027 — 3:00-4:00 PM
    • Monday, February 15, 2027 — 2:00-3:00 PM
    • Monday, February 22, 2027 — 2:00-3:00 PM
  • Cost: $599
    • University of Maine System employees and AI essential participants: See discount codes and enrollment instructions below
  • Earn a Certificate of Achievement Recognizing Your AI Expertise

*While live participation is strongly encouraged, all Zoom sessions will be recorded and made available for participants unable to attend in real time.

Please note that in preparation for the exercises and assignments you will do during the course, we recommend that participants have access to a paid version of a large language model, such as ChatGPT Plus/Team or Gemini Pro. The paid versions of these platforms offer more advanced capabilities, better reasoning, and improved performance for the tools and workflows we will be exploring during the course. Beginning July 1, 2027, University of Maine System students, faculty, and staff will have free access to ChatGPT Edu, which was developed specifically for use in higher education settings and is appropriate for use during this course.

Enroll Today

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Click Here to Register for Winter 2027

Discounts and employee registration instructions:

  • University of Maine System employees: Please submit this form before registering to receive a 20% employee discount code and to pay for this course via interdepartmental transfer.
    If you are an employee who has also participated in a past AI Essentials (90-minute) session, you may be eligible for a combined 40% discount (20% off as a past AI Essentials participant, plus the 20% UMS employee discount). Please submit this form to receive your 40% discount code and pay for the course via interdepartmental transfer.
  • Past Maine Center AI Essentials Series participants (non-UMS): Receive 20% off course registration. Email us at mainecenter@maine.edu for your exclusive discount code.

About The Instructor

Ryan Low, Vice Chancellor for Finance and Strategic AI Integration
Ryan Low, Vice Chancellor for Finance and Strategic AI Integration

Ryan Low serves as the Vice Chancellor for Finance and Strategic AI Integration for the University of Maine System, where he oversees financial operations, resource management, and administrative functions across the system’s seven universities. With a focus on fiscal responsibility, operational efficiency, and the strategic use of AI, he works to ensure the system remains financially sustainable while supporting its mission of accessible, high-quality education for Maine’s students.

Ryan has extensive experience in public administration, higher education finance, and AI integration. He is an active voice in discussions on the role of AI in higher education, presenting at events such as the New England Commission of Higher Education (NECHE) in Boston and the Higher Learning Commission (HLC) in Chicago. He served on Governor Janet Mills’ Maine Artificial Intelligence Task Force and co-chaired the UMS AI Task Force, helping to guide responsible AI adoption within the university system. Additionally, he is a member of the Generative AI Network for Accreditation and Higher Education (GAIN-AHEAD), an HLC-convened group focused on AI applications in accreditation, institutional operations, and policy development.