Executives from DXC Technology, SoftClouds, Kyndryl and Perficient share how their solution providers are taking automotive clients into the AI fast lane.
Applying artificial intelligence to electronic vehicle battery passports.
Using AI to turn service road records into predictive-maintenance data.
And leveraging AI to deliver car documentation to mechanics in their own languages.
These are just some of the ways solution providers who work with automotive customers are applying generative artificial intelligence to one of the world’s most complex industries, reaping early wins in automotive manufacturing, supply chain, retail and customer service with the future of automotive AI looking even more promising for new revenue opportunities for partners.
Executives with four automotive solution provider giants–Perficient, Kyndryl, SoftClouds and DXC Technology–shared in interviews with CRN how they are bringing automotive clients into the agentic AI era.
“Collaboration is very important,” Michelle Blakeley, who was promoted to the role of vice president and automotive client partner and managing director at Perficient in January, told CRN in an interview. “Helping them understand–here’s how you can activate AI and here’s, now, how you can measure–is how we’re helping the automotive industry really get ready and be optimistic about the outcome.”
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AI In Automotive
Although each of the solution providers are finding different areas to plant their flag in automotive AI, they all leverage long-term trusted relationships with vendors throughout the technology stack and clients from the various subsectors within automotive to further AI adoption and increase the odds of a successful AI experiment moving into production and scaling.
While rising costs and uncertainty from overseas wars and changing global tariff policies can make some areas of technology experimentation look too risky, all of the executives who spoke with CRN said that macroeconomic volatility has increased automotive clients’ interest in applying AI to take down operating costs, increase productivity and open new routes to market–similar to what’s happening with solution providers who take an AI-first approach internally themselves.
Multiple industry studies show how generative AI is evolving the automotive industry. GenAI applications can deliver up to 25 percent cumulative cost improvements and productivity gains of up to 30 percent within three years, according to a report published by consulting giant BCG in January. GenAI can take computer-aided design cycles and rework down by up to 60 percent and eventually provide a 40 percent reduction in vehicle time-to-market.
Documentation copilots can remove up to 90 percent of administrative effort in automotive. Maintenance AI agents can reduce costs by about 30 percent, reduce downtime by 20 percent and boost inspection efficacy by 60 percent, according to BCG.
McKinsey & Co. put the automotive software and electronics market at $519 billion by 2035, with a compound annual growth rate of 4.5 percent and AI a factor. The overall vehicle market is growing by around 1 percent CAGR annually.
AI could improve software features that make up 70 percent of the market, including advanced driver assistance systems (ADAS) and infotainment. The technology also has potential for improving body features that will make up 57 percent of the market in 2035, powertrain features that will reach 49 percent of the market by then and connected services, which will stay consistent at around 41 percent, according to McKinsey.
Dealerships also show untapped potential, with automotive finance and insurance (F&I) services company Protective Asset Protection reporting in January that only 8 percent of dealers are currently active AI users.
“Where the rubber hits the road, they (auto clients) are trying to figure out how best they can utilize this technology for better usage for their business,” Asokan Ashok, chief technology and innovation officer at San Diego-based Oracle and Salesforce solution provider SoftClouds, told CRN in an interview. “They’re seeing value and then, OK, they go from there.”
Here’s how four solution providers are taking automotive clients into the AI adoption fast lane.
Perficient’s AI for Supply Chain Visibility
One of the areas where St. Louis-based Perficient–No. 61 on CRN’s 2025 Solution Provider 500–and its automotive clients are applying AI is greater visibility into supply chains.
For example, some geographies mandate that electric vehicles track battery lifecycles through a battery passport digital document. Perficient–which works with seven of the top 10 automotive OEMs–has worked with auto clients on battery passports to help track battery material sourcing origins, ensure ethical sourcing and make sure decommissioning electric vehicles doesn’t hurt the environment, Justin Huckins, who’s worked at Perficient for about 10 years on and off and has served as the solution provider’s director of digital and product strategy since 2022, told CRN in an interview.
“AI in and of itself drives a lot more transparency and visibility because it has access to all the data and information and can serve it in real time,” Huckins said. “That has just heightened or increased the desire for that visibility.”
Reimagining the “frustrating process” of processing warranties is another area Perficient has found success in, Huckins said. Using AI to process more claims faster and more quickly sort out reasonable and unreasonable claims also quickly shows clients ROI.
“It’s going to make people much happier, much more efficient,” he said.
Similar to how solution providers are navigating an IT world with tighter margins around hardware, auto OEMs are increasingly looking for ways to make up for slim margins on selling vehicles through connected capabilities, subscriptions and leveraging telematics.
AI “is driving those work streams in their own unique way, in a way they couldn’t have been driven,” Huckins said. “It’s creating more synergies where customers can understand the OEM a little bit more, the OEM can understand their customers a little bit more, and we can understand what drives vehicle pricing.”
Auto clients are also looking for AI to gather the best intelligence on supply chains for cost savings on parts and components, Blakeley told CRN.
Blakeley–who joined Perficient in 2024 as managing director for the Detroit and Chicago markets after a career working in just about every part of the auto industry outside of insurance, from car dealerships to OEMs and marketing–sees AI adoption happening much faster than the e-commerce revolution when, as she remembers, auto executives couldn’t believe people would one day spend hours researching cars online before going to a lot.
Now, part of Perficient’s work in the auto industry is helping the parts of the business that depend on website traffic navigate new buyer behavior norms as consumer AI tools summarize web search results instead of sending users to a client’s website, Blakeley said.
In the age of AI, solution providers are necessary for ensuring the data informing AI tools is of a quality good enough for generating trustworthy results, she said. Perficient has helped auto clients find operational areas for early AI wins before scaling projects throughout a division or even moving to a new part of the client. Perficient change management capabilities have also served clients by setting up proper success and impact measurements and showing where AI augments employees so that morale stays strong and employees don’t see AI as replacing the parts of the business where human interaction and relationships remain essential.
Some early and simpler AI projects Perficient likes to start with for auto clients is unlocking agentic AI capabilities in existing platforms, like activating Agentforce capabilities within Salesforce, Blakeley said. Perficient is also working to automate manual tasks, activate agentic frameworks to more quickly migrate environments to the cloud or assess site content, and build chatbots for information retrieval. Perficient is also training employees to leverage AI to take ideas through exploration and bringing them into production. AI can judge the ideas, develop prototypes and assess the business case for the organization.
With AI, “there’s incredible potential and I think everyone sees it, but success really comes down to the right data and then the execution of it,” she said. “Everyone wants it. They want it now instead of understanding, again, the automotive industry and the complexities that may come with it, the time that it takes to ensure that the data is there so we can activate some of these agentic models. But the excitement is 100 percent still there. It’s just we have to prepare everyone and their teams where they’re at.”
Kyndryl’s AI Hackathons, Predictive Service Insights
Giovanni Carraro, senior vice president of global strategic alliances at New York-based Kyndryl–No. 11 on CRN’s 2025 Solution Provider 500–describes the company’s role in proliferating automotive AI as almost like an integrated ecosystem orchestrator, marrying relationships with technology vendors, automakers, part suppliers and other organizations that make up the industry to take AI projects from experimentation to production.
In one example, Kyndryl–which counts eight out of the top 10 global automakers by revenue size as customers–helped a hyperscaler and major auto manufacturer client take hundreds of idea submissions through pitching, sandboxing and actionable demonstrations, Carraro said. The hackathon resulted in around five production-ready winners. Projects like that take on increasing importance as auto clients look for returns on their AI investments.
“All these automakers are seeing this advent, and they see the need to modernize and be able to take advantage of all these new technologies and innovations,” he said. “They recognize that if they’re not doing (AI innovation), they’re going to be at a disadvantage with their competitors because everybody’s doing it. It’s a little bit of a race.”
Kyndryl has helped auto clients apply AI to predicting defects before they lead to an expensive recall and monitor supplier networks to anticipate shortages and more dynamically handle inventory. The solution provider has been turning unstructured service road records into predictive quality management, which also helps insurance and financial services sectors, too.
“We’re seeing a lot of our clients really be looking at AI from an experimentation kind of point and moving into a production ready solution,” he said. Kyndryl helps “create the infrastructure so that then you can deploy and then you can also run all these models in a confident way. You can monitor the infrastructure, you can provide the governance around it so you’re sure that the model is trained with the right data and that the model is behaving the right way.”
The solution provider has invested in its Vital design-led transformation practice for mapping out customer, employee and machine interactions with AI to create adaptive journeys while maintaining brand intent and purpose.
Kyndryl is also building AI innovation labs like the flagship that opened last year in Liverpool, England, where Kyndryl professionals advise businesses on adopting and implementing AI through business applications and integrating mission-critical operations.
The Liverpool lab aims to reach 1,000 software engineering and AI-related roles by 2028, according to Kyndryl. An AI Innovation Lab Kyndryl launched in Singapore in June started with 50 local data scientists, data engineers, AI developers and other AI specialists with access to launch partner Google Cloud’s Vertex AI, BigQuery, Agent Development Kit (ADK) and Google Agentspace to help with co-creation.
Kyndryl aims to give auto clients “confidence that they’re using the right data to train the model, confidence that the models are doing what they’re supposed to be doing. And ultimately the confidence in saying, ‘I can rely on the action that an agent or a group of agents that work with each other (takes),’” he said.
Carraro positions AI as more of an evolution than a revolution for auto clients to illustrate adopting the technology as more of a journey and make the changes easier to digest.
For auto clients, Kyndryl has been working to bring in connected vehicle data, customer relationship management (CRM), enterprise resource planning (ERP) and other once-siloed system data for AI friendly data warehouses, Carraro said. An iterative approach to AI adoption is usually the best way for auto customers with complex IT environments.
“We run their system, we help them transform, we run their system again after they are transformed so that we’re now ready to think about what’s the next transformation and continuing to have that evolution,” he said. “That is not a revolution, a major thing, but there’s a progression through a maturity journey that they themselves are going through as they adopt more AI.”
SoftClouds’ AI for Knowledge Management, CPQ
SoftClouds CTIO Ashok told CRN in an interview that the solution provider is using AI for improving localization in automotive knowledge management systems to improve language localization, with the ability to take one document needed by car repairers worldwide and creating dozens of versions of the document in different languages.
SoftClouds, which employs about 200 people, has also built a knowledge base generator that can transform long auto manuals to give users shorter versions to speed up repairs and troubleshooting, Ashok said. For car service centers, a SoftClouds solution can ingest service tickets, automatically create a knowledge base and enable natural-language based search.
Applying AI to anomaly detection, better sales lead scoring and forecasting, and the configure, price, quote process are also resonating with customers. For AI and CPQ, SoftClouds is investing in a way for auto clients to allow customers to go online and preview what cars might look like with different spoilers, wheels, interiors and other adjustments before making a purchase.
Solution providers are key for sifting through AI noise to find short-term and long-term wins applying the technology, he said.
“When a lot of people think about AI, people think that, OK, AI means it’s only text, it’s just knowledge,” he said. “AI is a group of technologies. So we are building into image. If we are building into automatic speech recognition. We are building into color matching and video processing. There are multiple other areas of AI that we are already looking at.”
DXC’s Amber Infotainment, AI-Improved Software Development
Uwe Brandenburg, who became chief technology officer and senior vice president for automotive and manufacturing last year at Ashburn, Va.-based DXC Technology –No. 61 on CRN’s 2025 Solution Provider 500–told CRN in an interview that the solution provider’s innovations in automotive AI range from the Amber infotainment software stack launched at CES 2026 earlier this this year to leveraging AI to improve car safety.
Amber comes with underlying middleware and provides voice recognition and other innovations, Brandenburg said. DXC is also applying AI to the software development process with its clients. AI is enabling DXC to develop software faster with improved quality and lower costs.
Embedded software and physical AI in autonomous driving and advanced driver assistance systems (ADAS) for automated braking, steering and increasing safety are also major opportunities for DXC.
DXC has developed AI tools for reusing existing data for future car platforms to help speed up the testing validation cycle, which can see upwards of 70 percent of costs come from driving older models to collect data.
“This is (our) DNA–and now this DNA is powered by AI,” he said. “In the end, it’s delivering faster releases, time to market, lowering the integration and software costs. And of course, what we also wanted to do is create new revenue streams and opportunities.”
DXC and its Luxoft division purchased in 2019 count eight of the 10 biggest global automotive makers as clients who can leverage 3,500 DXC engineers in nine locations worldwide. DXC has delivered 600-plus auto projects in the field, with 50 million cars in the field with DXC software in them. Every three seconds a car is built with DXC software inside, Brandenburg said.
Macroeconomics not only create an urgency for Western automakers to adopt AI, but so does the potential of catching up with–and not falling behind–auto upstarts like Tesla and Eastern auto companies that might face fewer regulations for adopting cutting edge technology.
The DXC strategy with auto clients has spanned advisory and consulting, delivery and engineering as well as strategic planning. DXC has taken a platform-led, agent-led, outcome-driven approach to client AI projects, he said.
“This makes us really strong,” he said. “We can really cover everything. And I would say, for me, we are, in all areas, quite strong.”
DXC has also taken a leadership position in regulation around automotive AI, playing a major role in a working group that is exploring frameworks around AI in automotive software and its acceptability when certifying cars for safety and technical standards for public sale.
“AI is really sexy, but we need to also find how we manage and create the boundaries and framework,” he said.
Brandenburg also foresees AI playing a role in improved user experiences in a car, through changing car climate with gesture or voice-enabled controls, for example. He foresees AI in cars allowing for social media posts without interrupting a drive, improving in the field, over the air upgrades to not only entertainment systems but even –not to mention the long-held dream of self-driving cars.
“I’m really curious how long it really takes to have full autonomous driving cars with AI on the market, which also can pass this regulation,” he said.
