Customer Support AI Leaders Pathway | Education Series (Launching 2026)
- AI Foundations for Customer Support: Clear, plain-English lessons on AI fundamentals, prompting, limitations, and safe usage — specifically framed for customer-facing support environments and sensitive interactions.
- Applied AI Customer Support Workflows: Real support use-cases including ticket triage, response drafting, knowledge base search, troubleshooting, escalations, follow-ups, and internal documentation — tailored to your organisation’s support tools, SLAs, and policies.
- Module AI Quizzes: Short assessments to reinforce understanding and confirm practical customer support capability.
- Portfolio-Ready AI Assignment Outputs: Leave with AI-supported ticket workflows, response templates, troubleshooting guides, knowledge base structures, and real support examples specific to your company.
Program Modules (Launching 2026)
Learn how AI actually works inside a customer support environment — what it’s good at, where it struggles, and how to use it confidently without risking customer trust. You’ll understand how AI generates responses, where errors can occur, and why human oversight always remains essential.
You’ll also cover the boundaries of safe usage when handling customer data and sensitive interactions.
Outcome: Clear understanding, reduced fear, and confident, responsible AI usage in support roles.
Map how your support role actually operates today — from ticket intake and triage to resolution, escalation, and follow-up. This reveals where time is lost to repetitive questions, manual categorisation, documentation gaps, and handoff delays.
You’ll define your “before state” so AI supports your work without disrupting service quality or customer experience.
Outcome: A clear, shared view of your real support workflows and where AI can safely create leverage.
Walk through real-world customer support workflows showing how AI supports ticket triage, response drafting, knowledge base search, internal notes, and escalation preparation.
Each example clearly shows what remains human-led and where AI accelerates resolution.
Outcome: A concrete understanding of how AI fits into real customer support work.
Apply AI directly to your live support tasks — such as ticket categorisation, first-draft responses, internal summaries, troubleshooting steps, and post-resolution follow-ups. You’ll redesign real workflows you already use into practical AI-supported processes.
All outputs are generated using your real product, customers, and support policies.
Outcome: Working AI-supported customer support workflows tailored to your role.
Learn how to move from one-off prompts to reusable prompt systems and response templates. You’ll build structured prompts for common issues, refunds, technical troubleshooting, onboarding questions, and escalations.
This ensures faster responses while maintaining accuracy, tone, and brand voice.
Outcome: A personal library of proven support AI prompts and templates.
Apply everything you’ve learned directly to your organisation’s real support environment — including your product, customer segments, SLAs, policies, and escalation paths.
Rather than generic examples, you’ll work through live company-specific scenarios so outputs are immediately usable in production.
Outcome: AI workflows embedded directly into your real support operation.
Move beyond isolated task optimisation and redesign entire support workflows for speed, clarity, and consistency. You’ll simplify ticket handling, reduce backlogs, improve first-response quality, and strengthen handovers between frontline support and product or engineering.
The focus is on faster resolution without sacrificing customer satisfaction.
Outcome: Faster, cleaner support execution without increasing team workload.
Learn how to use AI responsibly in customer-facing roles — including privacy, data protection, misinformation risk, brand tone, liability exposure, and handling vulnerable customers.
This ensures AI strengthens customer trust rather than creating legal or reputational risk.
Outcome: Safe, compliant, and trust-preserving AI usage across the support team.
Learn how to quantify the real impact of AI on customer support — including time-to-first-response, resolution time, ticket volume per agent, backlog reduction, and CSAT/NPS influence.
You’ll build a simple ROI model tied directly to one redesigned support workflow.
Outcome: Clear evidence of productivity, service quality, and customer experience improvements from AI-supported support work.
Compile your redesigned workflows, prompt systems, templates, and real support examples into a practical Applied Customer Support AI Portfolio tailored to your role and organisation.
This portfolio becomes:
- Proof of your AI capability
- An internal support enablement asset
- A future-proof career credential
Outcome: A fully documented, job-ready Customer Support AI portfolio you can apply immediately.

.png)






