Driving Automotive Retail Innovation: AI in Automotive & Beyond

In our recent Keyloop Drivetime podcast, our lovely host Jacqui Barker spoke to Oana Beattie, Vice President of Data and AI at Kyndryl, the global IT infrastructure giant, about how AI is fundamentally reshaping automotive retail and adjacent industries. Having advised global leaders and contributed to early Open AI development, Oana offered valuable insights and some pragmatic strategies for retailers eager to bring AI into their operations. 

We thought we’d put together some key takeaways in case you missed it.  

Data first: The foundation for AI success for automotive retailers  

There’s a critical need to prioritise clean, accessible, and connected data before any AI deployment. Without it, poorly structured data only amplifies inefficiencies.  

60% of organisations across industries, including but not limited to automotive, are still launching or integrating basic AI capabilities, but most struggle due to fragmented CRM, DMS, marketing, and finance systems. 

For retailers, that means: 

• Ensuring your DMS, CRM, inventory, and service systems are integrated. 

• Cleaning data to eliminate duplicate records, outdated entries, or missing fields. 

• Validating that AI systems use up-to-date, accurate data sources. 

Reducing admin waste: AI streamlines internal processes  

One of the most impactful ways that organisations can harness AI is through its ability to automate routine administrative tasks, freeing staff to focus on high-skill interactions. For example: 

• Auto triaging inbound queries (e.g. service requests, test drive bookings) 

• Auto-generating finance quotes based on customer data 

• Populating CRM lead records from online engagements 

This leads to faster response times, higher lead-to-appointment conversion, and ultimately better customer service. 

Trainable AI agents: From chatbots to virtual concierges 

Forward-thinking automotive retailers can build simple, focused AI agents (based on platforms like ChatGPT) with minimal training data. These agents could: 

• Handle scheduling, finance queries, and recall notifications 

• Surface insights like trending online searches or underperforming stock  

Such agents become digital assistants, helping staff manage workflows, automating service reminders, and elevating customer experience. 

Mobility-as-a-Service & AI-driven differentiation 

Looking beyond traditional retail, Beattie explored how Mobility-as-a-Service is emerging as a viable, AI-enhanced alternative to one-off car sales. In this future: 

• AI manages fleet availability, usage predictions, and service scheduling 

• Retailers can become providers of subscription-based vehicular service 

• Customer preferences and vehicle telemetry data guide seamless usage experiences 

This may redefine the value proposition from selling cars to managing mobility experiences tailored by AI. 

Key stats and industry benchmarks 

Industry sources support several powerful trends: 

• 60% of organisations are in early AI adoption phases  

• Retailers with integrated data systems report 15–30% higher lead conversion rates and a 5–10% reduction in acquisition costs 

• AI automation of administrative tasks can reduce staff time wasted by up to 40% in customer operations (general benchmark) 

Retailers embedding AI, rooted in clean data and aligned with strategic use-cases, see measurable and ongoing performance improvements. 

A step–by–step implementation plan 

1: Data audit and cleanup 

Map your data landscape – CRM, DMS, marketing, inventory, service logs, and fix gaps or inconsistencies. 

2: Integrate platforms 

Unify systems to feed real-time data into a central analytics hub or AI platform. 

3: Pilot AI agents 

Choose a manageable use-case (e.g. service scheduling assistant, recall notification bot) and train a small-scale prototype. 

4: Automate admin workflows 

Identify repetitive tasks – quoting, booking, form-filling, and build automation layer powered by AI. 

5: Expand into intelligent mobility 

Explore subscription-based models or usage-based pricing, enabled by AI that anticipates needs and usage patterns. 

6: Measure and iterate 

Track KPIs: response time, lead conversion, appointment booking rates, customer satisfaction. Use feedback loops to refine models. 

7: Governance and culture 

Ensure GDPR compliance, explainability in AI decisions, and foster a mindset of experimentation. Leadership must embrace failure, learning, and AI literacy. 

What AI means for automotive retailers 

With AI and data being bandied around as key buzzwords in the industry right now, it’s hard to cut through the noise and work out what it could mean if retailers harness the technology. Here are a few ways things could change for retailers who choose to embrace AI.  

• Staff empowered, not replaced – AI handles admin so employees can focus on high-touch customer interactions. 

• 24/7 digital responsiveness – Virtual agents ensure customers get real-time answers, even outside business hours. 

• Proactive service – From recalls to MOT reminders, AI identifies and acts on opportunities before customers ask. 

• Futureproofing business – Those who experiment with MaaS and usage-based models position themselves ahead of market disruption. 

Final takeaways  

AI isn’t just hype, but a practical ally for automotive retailers ready to transform their operations, customer experience, and business models. For those wanting to build a plan around data-centric AI strategy, it’s a good idea to start with the following considerations.  

Start with data: Clean, integrated systems are essential. Poor data derails AI. 

Automate admin first: Use AI to cut operational waste and speed up customer processes. 

Deploy simple agents: Train AI assistants to handle basic queries and service flows. 

Explore Mobility-as-a-Service: AI enables usage-based models, moving beyond outright sales. 

Measure, refine, govern: Track real KPIs, iterate models, and maintain ethical oversight. 

For retailers that begin the journey now; with clean data, focused pilots, and a spirit of deployment and learning, the upside is not only operational efficiency but meaningful competitive advantage in a rapidly evolving market. 

Harnessing AI with Keyloop VEGA 

Building a tailored AI strategy is a lot easier if you have the right tools in place; tools that truly help you to harness your vehicle and customer data to streamline processes, empower your teams, and ultimately unlock significant efficiencies and profit.  

Our latest product launch marks a real shift for the future of automotive retail performance: VEGA, our new intelligence platform, is designed to help retailers and OEMs make better-informed, faster decisions with confidence. 

VEGA brings together the right data in the right context, turning noise into clarity and insight into action. It’s built for the pace and complexity of today’s market. 

Learn more about Keyloop VEGA today and request a demo.