Ford Motor is embedding artificial intelligence (AI) across engineering, software and enterprise systems as it accelerates its shift to a technology-led mobility company.
At the centre of that effort is Ford’s enterprise platform engineering and operations (EPEO) organisation, which builds digital infrastructure across engineering, manufacturing and enterprise operations.
Sucheta Walimbe, chief technology officer for enterprise platform engineering and operations at Ford Motor Company, said the unit provides the foundational platforms driving Ford’s technology transformation.
“My organisation runs what I would call the digital backbone of Ford. We support all the different businesses including Ford Blue, Ford Model e and Ford Pro,” Walimbe said in an exclusive interview with Mint.
Ford Blue focuses on internal combustion vehicles, Ford Model e develops electric vehicles and Ford Pro builds commercial vehicle and fleet solutions.
The EPEO organisation operates across roughly 32 locations globally, including in Chennai and Bengaluru, and supports technology systems across about 600 operational sites worldwide, including around 70 manufacturing plants.
AI spreads across Ford’s operations
AI is being embedded across Ford’s technology stack—from engineering simulations to enterprise workflows and productivity tools.
According to Walimbe, the company is pursuing AI across three broad areas: large strategic initiatives overseen by senior leadership, organisation-wide adoption of AI tools by employees, and targeted applications designed to improve specific business processes.
Ford has already begun deploying AI in engineering workflows. Internal high-performance computing clusters powered by graphics processing units are dramatically accelerating simulations used in vehicle design. Computational fluid dynamics simulations that once took 15 hours now run in about 10 seconds using AI-optimised GPU clusters. The company is deploying thousands of GPUs as it expands its AI infrastructure and is preparing its data centres to support next-generation chips.
“The speed at which AI is evolving is unlike anything we have seen before. When we moved to the cloud it took years. AI is moving at a much faster pace,” said the Ford veteran who has spent more than three decades at the company.
Beyond engineering, the company is experimenting with broader use of AI tools across the workforce. Employees are being trained to use AI tools in their daily work, part of a broader effort to embed AI capabilities across the organisation.
Software shift
Ford’s push reflects a wider shift across the automotive industry as vehicles increasingly become software-defined machines rather than purely mechanical products.
Software-defined vehicles allow automakers to add features, improve performance and fix bugs through over-the-air updates, similar to how smartphones receive software updates.
The market for software-defined vehicles is expected to expand rapidly in the coming decade. Allied Market Research estimates the market will grow from about $258 billion in 2024 to nearly $1.9 trillion by 2034.
Automakers are investing heavily in AI infrastructure. Volkswagen plans to invest up to €1 billion by 2030 and already runs over 1,200 AI applications across engineering, manufacturing and IT operations.
General Motors is expanding its use of AI-driven vehicle platforms and plans to introduce features such as conversational AI assistants and advanced driver assistance capabilities in future models. Rivian recently unveiled its in-house autonomy chip designed to power AI-based driving capabilities.
For legacy automakers like Ford, building strong internal software capabilities has become critical to competing with newer electric vehicle companies such as Tesla and Chinese EV makers that designed their vehicles around software architectures from the outset.
Why Ford is doubling down on software and AI
Ford’s investment in AI and enterprise platforms comes as the company navigates a complex transition across the automotive industry.
The automaker reported revenue of about $187 billion in 2025, extending a five-year growth streak driven largely by strong demand for trucks and hybrid vehicles in North America.
However, the transition to electric vehicles and next-generation software platforms has weighed on profitability. Ford’s Model e electric vehicle business reported a full-year operating loss of about $4.8 billion in 2025 as the company continues investing heavily in EV technology and software-driven vehicle platforms.
At the same time, automakers are increasingly looking to generate revenue from software and digital services.
Ford Pro, the company’s commercial vehicle business, reported that paid software subscriptions for fleet services grew 30% in 2025.
The shift reflects a broader industry strategy to generate recurring revenue from connected services and digital features. General Motors generated about $5.4 billion from its OnStar connectivity and Super Cruise driver-assistance services in 2025 and now has more than 11 million OnStar subscribers globally. Tesla charges about $99 a month for its Full Self-Driving software subscription, while BMW has experimented with charging monthly fees for features such as heated seats.
Supporting these services requires large-scale cloud infrastructure, developer platforms and AI systems capable of processing vast volumes of vehicle and customer data.
India’s growing role in Ford’s technology stack
India has become an important engineering hub within Ford’s global technology organisation, with teams working across cloud engineering, cybersecurity, site reliability engineering and enterprise data platforms that power the company’s analytics and AI systems.
“I will go where the talent is. And with the numbers we have (in India) and the universities we have, there is a lot of talent here,” said Walimbe, a first-generation migrant from India.
Beyond talent, India is increasingly handling strategic work within Ford’s enterprise platform engineering organisation. Teams in the country are contributing to core areas such as cybersecurity engineering, cloud infrastructure and AI platforms that support Ford’s global technology backbone.
Some of these initiatives are led from India, including work on Ford’s enterprise “Data Factory”, a Google Cloud-based platform used to process data and train AI models across the organisation. Engineers in India are also involved in maintaining the reliability of global digital platforms and supporting the company’s AI infrastructure.
The expanding scope reflects how India-based teams are increasingly leading core platform and data initiatives rather than functioning as traditional back-office support centres.
“India is extremely important. We are running strategic initiatives from India, and I don’t see that changing. In fact, I see it growing,” Walimbe said.
For Ford, the investments in AI infrastructure, developer platforms and global engineering capabilities represent an effort to ensure that software and AI become core competitive strengths in the next phase of the automotive industry’s transformation.
