- 01
Clean the skills and routing model before enabling predictive routing
- 02
Retire any bot without a named owner and a weekly containment metric
- 03
Digital channels, not voice, hold most compliance and redaction gaps
1. Architecture and org hygiene
Check divisions, roles and permission sets against who actually administers the platform today. Confirm one naming convention across queues, skills, flows and data tables. Pass test: any new administrator can locate the live flow for a given DID within two minutes without asking a person.
2. Routing and skills debt
Count active skills versus skills used in routing decisions in the last 90 days. Most estates carry 2–3x more skills than they route on. Consolidate to a skills model tied to real proficiency, then move from static queue routing to predictive routing only after the skills model is clean — predictive routing amplifies whatever data you feed it.
3. Bots, containment and Agent Assist
Audit each Genesys Dialog Engine or third-party bot against a containment target and a live escalation rate. Any bot without a named owner and a weekly metric review gets retired or re-scoped. Agent assist and knowledge surfacing should be rolled out on the same queues you are automating, so you can prove containment rose and quality held in the same quarter.
4. Integration and data health
Validate data actions, CRM screen pop latency, WFM adherence feeds and the analytics export path. Two failure modes dominate: data actions calling deprecated endpoints, and interaction exports silently dropping fields after a platform release. Both need a scheduled synthetic test, not a quarterly manual check.
5. Quality, compliance and automated QA
Replace manual sampling with automated evaluation across 100% of interactions, then keep a human calibration sample. Confirm recording retention, consent capture, PCI pause-and-resume and redaction behave the same on voice, chat and messaging channels — most gaps live on digital, not voice.
6. Run-state governance and roadmap
A named platform owner, a fortnightly change board, a release-note review cadence against Genesys feature drops, and a rolling two-quarter roadmap with a business sponsor per item. Modernization that ends at go-live decays within three quarters.
- Clean the skills and routing model before enabling predictive routing
- Retire any bot without a named owner and a weekly containment metric
- Digital channels, not voice, hold most compliance and redaction gaps
- Synthetic tests on data actions and exports catch platform-release regressions early
Questions leaders ask us
- What does Genesys Cloud modernization actually involve?
- Six workstreams: architecture and org hygiene, routing and skills debt, bots and agent assist, integration and data health, automated QA and compliance, and run-state governance. Most programs need all six, sequenced so routing hygiene precedes AI routing.
- Should we enable predictive routing straight away?
- Not before the skills model is clean. Predictive routing learns from your existing assignment data, so an estate carrying two to three times more skills than it routes on will encode that noise into the model.
- How do we prove modernization worked?
- Baseline containment, AHT, transfer rate, QA score and CSAT per queue before the first change, then report the same five metrics per queue every fortnight. Improvements that cannot be attributed to a queue and a change are not improvements.
- Do we need to leave Genesys Cloud to adopt agentic AI?
- No. The automation and orchestration layer sits above the CCaaS platform, so agentic workloads can run on Genesys Cloud today and remain portable if the platform decision changes later.