Overview

Our AI for Managers and Leaders Training Philippines course shows managers and team leaders how to use AI well in their own work, find where it fits in their team's work, and lead their people in using it safely. In 7 hours of live, instructor-led training, you practice on the AI tool your company already uses, whether that is ChatGPT, Claude, Microsoft Copilot or Gemini. Everything you learn works on any of them.

By the end of this AI for Managers and Leaders Training Philippines program, you leave with ready-to-use tools built from your own team's tasks. What you get from AI for Managers and Leaders Training Philippines:

  • 7 hours of Live Online Training with an expert instructor
  • Hands-on exercises on the AI tool your team already uses
  • A reusable team prompt template and a quality checklist for AI output
  • An AI opportunity map of your own team's tasks
  • A one-page team AI usage guide based on the Data Privacy Act
  • A 30-60-90 day team AI adoption plan
  • Digital course materials
  • Course Completion Certificate

Who Should Attend

Individual Professionals

This course is ideal for managers and leaders who want to use AI well in their own work and guide their team, including:

  • Department Heads and Unit Managers who want faster, better-informed decisions
  • Team Leaders and Supervisors who want their team working smarter with AI
  • HR, Sales, Marketing, Finance, Operations and Customer Service Managers
  • Project Managers and Business Owners of small and mid-sized companies

Organizations and Teams

Also a strong fit for companies that want their managers to lead AI adoption the same way across teams, including:

  • Department Heads and Unit Managers who want faster, better-informed decisions
  • Organizations rolling out ChatGPT, Copilot, Gemini or other AI tools and needing managers to lead it
  • HR and Learning and Development teams building AI skills across their leadership team
  • Companies that need clear, consistent AI usage rules across departments

Course Outline

AI Basics and Prompting for Managers

  • How generative AI works, in plain terms, and why it makes confident mistakes
  • Chat assistants, custom assistants and AI agents: what each one does
  • The five-part prompt: Context, Role, Task, Constraints and Output Format
  • Giving AI the right background: documents, examples and style guides
  • Getting better answers by asking AI to critique, list assumptions and give options
  • Common management uses: summarizing reports and meetings, drafting announcements and emails, analyzing spreadsheet data, and comparing options
  • Prompt Lab on two different AI tools, ending in a team prompt template

Checking AI Output

  • Structuring prompts for software testing tasks
  • Common failures: made-up facts, outdated information, bias, wrong math and overconfident tone
  • Quick ways to check: verify sources, cross-check with a second tool, spot-check numbers, ask the AI to show its steps
  • Who is accountable when AI-assisted work goes wrong
  • Spot the Error, then a 5-point team quality checklist

Finding AI Opportunities in Your Team's Work

  • Rating tasks by time spent, how repetitive they are, risk and data sensitivity
  • Sorting tasks into automate, assist with AI, or keep human
  • Picking quick wins first and parking bigger projects
  • Team AI Opportunity Map, using your pre-work task list

AI-Assisted Workflows and Agents

  • Mapping a workflow: trigger, input, AI step, human check and output
  • Custom assistants with saved instructions and reference files
  • What AI agents are, how they act on your behalf, and where they go wrong
  • Placing human approval points and naming who owns and reviews each agent
  • When to bring in IT
  • Sketch one workflow from your opportunity map, with its human check points

Data Privacy and Team AI Rules

  • What never goes into an AI tool: personal data, client information and trade secrets
  • The Data Privacy Act of 2012 and the National Privacy Commission's guidelines on AI, in plain terms
  • Using AI in people decisions such as hiring, appraisals and discipline: fairness and human oversight
  • Approved and unapproved tools, and the risk of staff using personal AI accounts for work
  • Draft a one-page team AI usage guide

Leading Adoption and Planning the Rollout

  • Why people resist: job worries, skill threats and extra workload
  • Leading by example: using AI openly and sharing both wins and mistakes
  • Making it safe for your team to experiment, while keeping core skills sharp
  • What to measure: time saved, quality, error rate and adoption, starting from a baseline
  • Running a small pilot and scaling what works
  • Capstone Activity: Build your 30-60-90 Day Team AI Adoption Plan