Automotive CEOs are investing heavily in AI to drive efficiency, but few expect it to fundamentally reshape their operating models.
Automotive retailers are being urged to focus less on headline-grabbing innovation and more on operational discipline as AI investment accelerates across the sector.
According to the latest findings from KPMG’s global CEO research, AI is increasingly being embedded into core processes to reduce manual work, improve decision-making and speed up workflows across finance, procurement, planning and customer operations.
The emphasis is on practical gains rather than futuristic retail concepts.
KPMG’s analysis suggests AI delivers the greatest value when it is integrated across the enterprise, rather than deployed in isolated use cases.
For dealer groups, that means looking beyond individual tools and addressing how AI supports end-to-end processes such as lead-to-order, order-to-delivery and service-to-retention.
Agentic AI: efficiency gains, limited belief in disruption
The report draws a clear distinction between incremental productivity gains and genuine operating model transformation, particularly in relation to so-called agentic AI systems that can act with limited human intervention.
Some 45% of automotive CEOs expect agentic AI to significantly improve efficiency and cost outcomes.
However, only 18% believe it will be transformational in fundamentally changing operating models and workforce management.
Leaders see agentic AI as a lever for throughput and cost control, but most are not yet preparing for the structural changes that would follow widespread deployment of autonomous decision-making systems.
In practical terms, this points to a likely 2026 pattern in retail.
Dealers are expected to deploy AI in admin-heavy processes such as lead triage, call and email summarisation, workshop planning support, finance documentation checks and compliance workflows.
However, fewer appear ready to redesign roles, governance structures and accountability frameworks around autonomous systems.
Retail impact: productivity first, workforce next
Although the research spans global automotive and manufacturing leaders rather than retail specifically, the implications for dealership operations are clear.
Efficiency and productivity gains align directly with dealer priorities around controllable costs, response times and reducing rework. However, talent remains a constraint. Competition for AI and digital skills, combined with the challenge of upskilling existing teams, could slow progress.
The research also suggests a disconnect between board-level confidence and operational readiness. High levels of confidence in AI adoption do not automatically translate into robust data foundations, governance frameworks or workforce strategies.
In practice, the retail groups most likely to secure sustainable gains will be those that treat AI as an operating discipline.
That means defining priority value streams, standardising processes, fixing data quality issues and then automating with clear guardrails.
By contrast, bolting new tools onto fragmented systems risks cost escalation, compliance exposure and limited return on investment (ROI).
A 12-month test for measurable ROI
KPMG reports that many CEOs expect to see a return on AI investment within one to three years, increasing pressure for measurable outcomes rather than experimentation.
For UK dealer executives, the next year is likely to become a test of whether AI can move core performance indicators such as enquiry response times, conversion rates, stock turn, service capacity utilisation and customer retention.
The findings around agentic AI suggest many leaders still underestimate the organisational implications of deeper automation, even as spending rises.
If that assessment shifts, dealerships may face a more fundamental debate about operating model design, including which decisions can be delegated to AI agents, which must remain human-led, and how accountability is managed across customer outcomes, finance and compliance.