AI Training Program for Customer Support and Sales Teams: AI in the Loop Highlights

by Venchito Tampon | Last Updated on September 24, 2026

In September 2026, Rainmakers delivered AI in the Loop: Smarter Customer Conversations, Sales Decisions, and Everyday Work. It was a two-day AI training program for the Customer Support and Sales teams of Creatunity LLC, designed and facilitated by Coach Bryl Zenarosa, CPHR, CLDP.

AI tools are now easy to get. Using them well at work is harder. This program was built on one idea: AI can help with the task, but people stay responsible for the result.

Over two days, the teams went from clearing up AI myths to presenting real AI business cases to their own management. Here are the highlights.

Training at a Glance

Why AI Training Matters for Customer Support and Sales Teams

Customer support and sales teams write, summarize, reply, and decide all day. That makes them some of the people who gain the most from AI, and the people most exposed when it is used carelessly.

Without training, teams tend to trust AI too much, or not use it at all. Both cost time. A confident but wrong answer can reach a customer. Customer details can end up in a tool they should never have been pasted into. And a good AI idea can stall because nobody knows how to make the case for it.

That is why AI has become one of the most requested topics among our AI training programs in the Philippines. The goal is not to use AI more. It is to use it well, and to turn it into results the business can see.

Program Goal: The 6A Action Journey

AI in the Loop was built to help Creatunity’s teams become confident, responsible AI users. That means people who know when to use AI, how to guide it, how to check it, and how to turn it into better ways of working.

The program followed the 6A Action Journey across both days:

• Day 1: Align, Assess, Ask
• Day 2: Apply, Audit, Adopt

Meet the Facilitator: Coach Bryl Zenarosa

Coach Bryl Zenarosa, CPHR, CLDP, is a Learning and Development leader with more than 15 years of experience. He was named the 2024 Corporate Educator of the Year and one of LinkedIn Philippines’ Top 30 Leaders. He is a former manager at Shopee Academy PH, and a certified MBTI® and DISC® practitioner.

His sessions feel like a work lab, not a lecture. Participants don’t just hear about AI. They try it on real situations from their own work, check what it gives them, and talk openly about what worked and what didn’t. Learn more about the Rainmakers team.

Day 1: Building a Responsible AI Foundation

The first day opened with an AI Work Readiness Check. Each participant placed themselves on a five-stage scale, from “curious” to “already built into my workflow.” They took it again at the very end of Day 2.

1. Align: myths, facts, and guardrails

The teams worked through common beliefs about AI in a quick guess, reveal, and discuss format. Then, before anyone wrote a prompt, they joined an AI Governance Sprint. Each group turned one working rule into a practical AI Use Guide Card for their own function and presented it to the room.

2. Assess: the right AI tool for the job

The teams looked at how AI grew from early tools into today’s AI agents. Then they watched Micro-Demo: 5 Tools, 5 Jobs, a set of live demos built around Creatunity-style scenarios. The message was simple: there is no single best AI tool, only the right tool for the task in front of you.

3. Ask: hands-on prompting practice

The teams learned the CRIT-C+ Prompting Method and put it to work in a Case-Based Prompt Lab. Each team took a weak starting prompt, rebuilt it, tested it, and improved it over several rounds. Day 1 ended with a look at metaprompting: using AI to improve the prompt itself.

Day 2: From AI Ideas to Business Cases

Day 1 was about using AI safely and well. Day 2 was about making it count for the business. It opened with a Rapid Fire Review to bring back what the teams had learned the day before.

4. Apply: finding the right opportunities

In AI Use Case Sorting, the teams judged real work tasks as a good fit for AI, a use-with-caution case, or something AI should not touch. They then built an AI Opportunity and Risk Map from their own work, looking at business value and risk rather than enthusiasm alone.

This led into the main event of the program: the AI Business Case Lab. Each team took a real business challenge and turned it into a case for action that management could approve, using AI to sharpen their thinking without letting it make up facts or make the decisions.

5. Audit: review before release

Fast output is not the same as finished work. In a Cross-Team Capstone Audit, each team reviewed another team’s work using the 4-Check Review Loop. They returned feedback in a psychologically safe format, and each team used it to improve its case before presenting.

6. Adopt: building the habit

The last stage made sure the learning didn’t end with the workshop. In a group planning sprint, the teams chose their 30-Day AI Activation Priorities: what to test, who owns it, and what guardrails come with it. They then shared their commitments with the group.

The Final Output: AI Business Case Toolkit

Every team left the program with more than notes. As the final output, each group produced an AI Business Case Toolkit, a package that makes an AI idea ready to act on:

• A business case built around a real problem at Creatunity
• A mini pitch deck and a 30-day pilot plan
• A working tool or process draft built with AI support
• A management approval email with a clear, concise ask

Each group then had seven minutes to present its case using a simple structure: the problem (What), why it matters (So What), and the proposed action (Now What).

The program closed with the AI Work Readiness Check one more time, so each participant could see how far they had moved. Anna Beneliza Manila, HR Specialist at Creatunity, gave the closing message, and everyone joined a final group photo.

Program Highlights

1. We cleared up common myths about what AI can and can’t do.
2. We agreed on smart guardrails before writing the first prompt.
3. We matched the right AI tool to the right job.
4. We wrote, tested, and improved prompts using real work scenarios.
5. We turned AI ideas into business cases that management can act on.
6. We reviewed each other’s work before calling it finished.
7. We committed to 30-day AI priorities so the learning continues on the job.

We’re proud to be Creatunity’s learning partner in building confident, responsible AI users. Thank you to Creatunity LLC for trusting Rainmakers with your teams’ growth, and to Coach Bryl for two practical, high-energy days.