Dealer AI briefing
Practical guidance for dealer principals, GMs, fixed ops leaders, and automotive retail teams evaluating where AI fits, how to deploy it safely, and how to measure whether it works.
10 operator guidesFilter the operator library
Showing all 10 guidesA 30-60-90 day dealership AI pilot plan covering workflow selection, baselines, data, permissions, training, measurement, risk, and scale decisions.
A practical operating model for dealership AI agents: permissions, human escalation, data controls, testing, ownership, measurement, and safe deployment.
A 30-day dealership AI adoption playbook for choosing one workflow, assigning owners, training teams, running a controlled pilot, reviewing evidence, and scaling safely.
A practical dealership AI data-readiness framework for DMS, CRM, service, call, inventory, consent, ownership, quality, access, and measurement.
A practical dealership AI vendor scorecard covering outcomes, DMS and CRM access, data use, security, human control, integration, measurement, and exit terms.
A dealer AI security checklist covering customer data, permissions, vendor risk, prompt injection, vibe coding, testing, logging, and incident response.
A dealer guide to the Automotive AI Summit 2026 agenda, covering AI ROI, technician productivity, security, customer experience, data, and adoption.
A dealer-focused AI ROI scorecard for separating activity from economic value across fixed ops, sales, BDC, marketing, inventory, and management workflows.
A fixed ops AI checklist covering workflow selection, DMS and scheduler data, technician productivity, human handoffs, measurement, and rollout.
A practical framework for dealer principals and GMs evaluating dealership AI across fixed ops, sales, data, customer experience, security, and team adoption.
