Retain and Grow Your Clients with AI Insight
Map every task across your account portfolio onto the AI Opportunity Matrix, so you know what to automate, where AI adds the most value by augmenting your work, and what to protect — and reclaim your biggest unclaimed hour.
Run a five-dimension PULSE health snapshot on any account in about twenty minutes — Performance, Uptake, Loyalty Signals, Stakeholder Map, Expansion Potential — so quiet risk surfaces months before it turns into churn.
Build a living 90-day account plan and prepare a complete QBR package in under ninety minutes, with AI as a challenger that argues against your plan before the client can.
Monitor renewal risk from six months out with PULSE, build a business case your client's finance team will accept, and rehearse the hardest objections before you are ever in the room.
Write client correspondence that reads as more tailored, not less, and turn monitored expansion signals into a grounded expansion conversation that never feels like a pitch.
Tier your whole portfolio into a three-tier cadence, run a weekly AI-assisted triage that tells you which accounts need you this week, and leave with a 30-day plan you can start on Monday.
Module by module, in the order they are assigned.
AI in account management is about putting evidence, monitoring, drafting, and synthesis around portfolios where renewal, growth, and trust compete for attention. By the end, you can sort tasks with the AI Opportunity Matrix, use the Augmentation Ladder, and protect human-led relationship moments.
PULSE replaces portfolio memory with a current, evidence-led account health read, so quiet clients show risk before renewal pressure appears. By the end, you can gather existing signals, build and check an AI-supported snapshot, handle client data safely, and turn the read into one accountable action.
Account planning and QBRs turn account health into decisions clients can recognise, helping account managers avoid stale documents, reactive relationships, and backward-looking reviews. By the end, you can build a lean plan, test client context with AI, challenge assumptions, prepare a QBR package, and apply TRUST.
Managing Renewals treats renewal as a preparation discipline: early PULSE risk signals, verified value evidence, safe data handling, objection rehearsal, and red-account repair before positions harden. By the end, you can assess risk, build the case, protect restricted data, and negotiate with rehearsed judgment.
Client communication and expansion connect portfolio rhythm with signal-led growth, so account managers stay useful without reactive check-ins or pitch-like outreach. You design touchpoint strategies, brief safe AI correspondence, apply TRUST, read PULSE Expansion Potential signals, and prepare conversations, proposals, and handoffs.
Large account portfolios need allocation rules because inbox visibility hides quiet risk, stale assumptions, and missed expansion signals. By the end, you can tier accounts, triage priorities from evidence, maintain relationship intelligence, judge automation boundaries, and choose real accounts for AI-assisted practice.
The course closes with a timed final exam with a pass mark and a limited number of attempts. A pass issues a PDF certificate with its own serial, in the name of the Straits Institute for Applied AI. Cohort progress, at-risk learners and a CSV export are in the admin console throughout.
No. The course assumes you are already a capable account manager or customer success professional who may only have used AI casually. It teaches the AI layer on top of account work you already do well — no coding and no existing AI workflow required.
No. Account management is a relationship discipline, and the course is explicit that AI handles the research, health monitoring, and preparation around the relationship. The live renewal negotiation, the executive conversations, and the trust you have built stay yours — that is the work AI is there to protect, not do.
The course is tool-agnostic. The prompts and workflows are written to run in any capable general-purpose AI assistant, so you can use whatever your organisation already has.
Module 2 teaches the AI Safety Checklist — Gauge, Understand, Authority, Risk, Decide — as a deliberate gate before any client data reaches a tool, and it recurs where client financials (Module 4) and stakeholder personal information (Module 5) are handled. The practical rule throughout: when in doubt, anonymise first and query later.
Six 60-minute modules — about six hours total — self-paced with video and slides. Each module follows a watch, then try it yourself, then practice rhythm, and leaves you with something usable on your own accounts that week.
It is recommended, not required. This course builds on the AI fundamentals introduced there and reintroduces what you need as it goes — the AI Opportunity Matrix, TRUST, and the AI Safety Checklist are each set up in context, so you can start here.
Frame Better Problems, Make Better Decisions
Cut Through Complexity with AI-Assisted Thinking
Sharper Questions, Better Answers, Stronger Closes
Hire, Develop and Lead Your Team with AI
Align, Influence and Communicate Across Every Level
Course libraries are assigned per user, team or department, and the reporting comes back to whoever has to answer for the programme. Tell us who needs it and we will show you the console.
