Auto maker Jaguar Land Rover has a long-term plan to transform its product range — but it’s also transforming its internal IT. Credit: Getty Images Anthony Battle is leaning heavily on AI and IA — artificial intelligence and intelligent automation — to deliver digital transformation at luxury auto maker Jaguar Land Rover. Battle joined JLR as group chief digital and information officer in February 2022, after a long career managing IT for a succession of oil companies. The auto maker, too, was moving away from oil, having announced plans not long before to make the Jaguar range all-electric by 2025, and to offer electric versions of all its other models by the end of the decade. JLR’s move to electric drive trains is part of a wider business transformation the company calls Reimagine, under which it also plans to halve greenhouse gas emissions from its supply chain and operations, compared to 2019 levels, by 2030, and to reach net zero carbon emissions by 2039. “Our business transformation is 100% underpinned by a digital transformation,” says Battle. That’s as true for the engineering teams electrifying the cars as it is for those that Battle oversees who are transforming the company’s IT systems. Delivering the best user experience for future vehicles will require new digital services and new integrations with existing services. “That means we need to draw off the car, and feed into the car, lots of data from our enterprise,” he says, so at the intersection of product engineering and enterprise IT, “you’ve got an acute level of synergy in terms of cloud, software engineering standards, integration, and APIs.” AI and IA Over the last five years, Battle says, JLR has learned it needs to pivot toward digital centricity, or, in other words, adopt a data-first approach and position the data, structured or unstructured, in a way that the company can adopt AI and intelligent automation tools to help it make informed decisions. There are plenty of software vendors willing to help with that — perhaps too many. “We’re not short of generous opportunities afforded by our strategic suppliers and vendors,” says Battle, wryly. When it comes to anything generative AI or automation orientated, “Everybody wants to help us on that journey.” There’s demand for it, too. “Our business is absolutely craving it,” he adds. “But we’ll do it in a measured way.” Battle has some external support when it comes to evaluating the potential for generative AI, because JLR is part of Tata Group, which also owns Tata Consultancy Services. “TCS and lots of other Tata organizations are already pushing the boundaries in many of these areas,” he says, so he’s looking at collaborations there. Generative AI has already made its entry into the company, with some software development teams using it in various parts of their coding schema and methodology, he says. Now, though, “we’re pausing to consider what to do to set guardrails, directives, and controls,” he says. “It’s a big project for us in terms of defining our strategy for data and AI, but also for automation.” In some of those areas, Battle is already concentrating spend on a small number of vendors, leaning toward Google Cloud Platform for data, and Appian for process automation, for example. “We’ve put in a lot of RPA capability, but I think Appian is probably our biggest engine for now,” he says. The need for change One of JLR’s first projects with Appian began in the months after the Brexit Withdrawal Agreement came into effect in 2020. “As a consequence of Brexit, we had to double down on finding intelligent solutions, ideally automated solutions, to recover from the introduction of all the bureaucracy and legislation that Brexit delivered to us,” says Battle. The company suddenly found its UK manufacturing plants separated from key suppliers in the EU by a mess of new customs regulations and paperwork, and seriously considered hiring staff just to deal with the paperwork. But the IT team proposed a digital solution. To scope out requirements, it pulled together a cross-functional team of subject-matter experts in tax, legislation, materials planning, logistics, aftermarket sales, and finance, along with some external support from Tata Consultancy Services. The document processing system JLR built on Appian has around 150 daily users handling about 250 customs declarations a day. It freed up the employees to do other things and, he says, enabled the company to save £15 million (about US$19 million), largely through reduced duty payments made possible with the data extracted from the automated process. Although the project was a success, there are some things Battle would have liked to do differently. “The speed with which we had to find a solution here didn’t really lend itself to process improvement,” he says. Moving quickly meant the business had to pivot to accommodate the change. “We’ve learned that time spent on process mapping and process engineering up front is a valuable investment,” he says. New tools that promise to free up time will be welcomed by employees who feel their to-do lists are too long, and growing longer every day. Those with more manageable workloads, though, may be suspicious of something that seems redundant. But, says Battle, “There’s nothing more powerful than the power of advocacy.” Having colleagues who have been introduced to a new piece of technology as part of their workflow become advocates or evangelists for it, which reframes the issue. “Then it’s no longer about me asking or directing; it’s the business, the people we’re here to serve, advocating the necessity for change.” Skills development While automation helped JLR avoid the need to hire a bunch of data entry clerks, like any other enterprise undergoing a big technology transformation, it’s had to hire or train up staff to meet the demand for new skills. In November 2022, JLR targeted workers recently laid off by global tech firms as it sought to fill 800 vacancies for experts in AI and machine learning, cloud software, data science, and other domains. With engineers in some big tech companies facing a new wave of layoffs as 2023 comes to an end, JLR’s hiring strategy is something other employers might want to emulate. “It’s been a great success,” says Battle. “We’ve attracted some incredible digital talent at many levels.” One thing manufacturing companies can offer their software developers and other IT workers — something the likes of Google or Meta can’t — is a chance to see what they worked on, or what they supported, roll off the production line and out the door. “You can tangibly see what it is you do relative to the products we create, so you can almost put your hands on the bottom line,” he says. “That seals the deal. It’s an incredible proposition for any tech professional.” Related content brandpost Sponsored by Avanade By enabling “ask and expert” capabilities, generative AI like Microsoft Copilot will transform manufacturing By CIO Contributor 29 Feb 2024 4 mins Generative AI Innovation feature Captive centers are back. 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