'There's an Inevitability' that AI Will Transform the Franchise Industry. Here's How It's Already Happening. From drive-thru assistants to local marketing campaigns, franchisees and franchisors are already busy putting AI to work.
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Two women pull into a Carl's Jr. drive-thru in Anaheim, California, and roll down their window. An employee introduces herself as Tori, and asks, "What can I get started for you?"
The question is normal enough, but something about Tori sounds a little weird. The women in the car start giggling. Tori takes it all in stride. She's not offended. She's a robot, after all.
She collects their order flawlessly — asking about drinks and combo sizes — and even tries to upsell them on some strawberry shortcake. A human employee hands them their food, and as they drive off, the woman riding shotgun gasps. "Oh, my God! AI is coming! AI is at Carl's Jr.!"
All of this played out on TikTok, where you can find a proliferating number of videos of AI taking orders at quick-service restaurants around the country. Franchises like Carl's Jr., McDonald's, Rally's, and Popeyes have all rolled out voice AI at select restaurants. And while these order-taking bots may be the most visible examples of how franchises are starting to use AI, they're just the beginning.
Artificial intelligence is already giving franchises myriad opportunities to improve efficiency and lower costs while increasing revenues — and its applications cannot be ignored. Whether you work for a QSR brand looking to save on staffing and improve operations, a retail brand wanting to boost localized marketing at a fraction of the cost of a traditional agency, a cookie company using predictive analytics to improve wait times and quality control, or a fitness studio developing a personalized coaching system, there are all kinds of novel ways you can put AI to work. And you should — because chances are, someone else in your industry is already doing it.
Related: How AI Is Poised to Help Humanity
For drive-thru in particular, QSR brands' motivation to explore voice automation has been driven by three parallel trends: rising labor costs, a post-pandemic appreciation for the value of drive-thru options, and AI hype.
While there were early concerns about losing control of the customer experience and customers reacting badly to bots, those have largely dissipated. Although customers' videos occasionally highlight hilarious AI missteps — one shows the AI adding nine Long Island iced teas instead of the single Sprite ordered — they reveal more of a sense of wonder than irritation. Nobody seems to miss the human service.
This makes sense. Fast-food ordering has always been relatively transactional. The industry's workers typically work long shifts, make minimum wage, and perform repetitive tasks. The bar that AI needs to clear is low. Brands are concerned about accuracy and efficiency, but if voice automation can hit those marks, then it can be an unalloyed positive. There's even an opportunity for more systematic upselling. "I think no one at this point denies that this is the future," says Krishna Gupta, chairman of Presto Automation, an enterprise software company that sells voice automation systems for drive-thru lanes to franchises like Carl's Jr. and Hardee's. "There's a sort of inevitability about it."
At one point, Gupta had a conversation with the former CEO of Restaurant Brands International, the parent company of Burger King. The executive was candid in his evaluation of his human workforce. He said that 5% of order-takers were exceptional — emotionally intelligent, consistent, diligent — without diminished performance even going into the sixth or seventh hour of their shifts. But understandably, this level of performance was the exception, not the rule. The promise of AI was a much more consistent, standardized experience.
Typically, even after the deployment of a voice automation system, companies will keep human employees on standby — listening in on the drive-thru conversations while simultaneously doing other tasks like making food. That way, when the AI fumbles, a human employee can step in.
Some franchises, like Carl's Jr., have bought enterprise software from an outside vendor like Presto. Others, like McDonald's, have tried to build their own robots in-house — in McDonald's case, acquiring several AI startups to assemble its own tech lab. If brands choose to buy an automation system, the amount of onboarding time varies, but it usually takes months. The hurdles tend to pop up when integrating with in-house point-of-sale and loyalty systems. Menu complexity is also a factor. "If you're a coffee chain that literally just sells coffee, integrating and training our models on your specific menu is not going to be particularly challenging," Gupta says. "If you are a group that does pastries, food, desserts, other drinks, etc., your menu is going to be dramatically more complex and will require more integration."
Interestingly, in many cases, the push towards automation and AI is coming from the franchisees themselves. For example, at Carl's Jr. and Hardee's, two leading franchisees reached out to Presto, indicating their interest in trying out the new voice AI technology. Together, they solicited permission from the franchisor.
In the case of Carl's Jr., the franchisees got the go-ahead, the test went well, and Presto later signed a master service agreement with Carl's Jr., which Presto could then take to other individual franchisees as a sort of calling card. CKE Restaurants, the parent company of Carl's Jr., hasn't adopted the technology, but franchisees can choose to adopt and pay for it themselves — the way they might hire or fire a staff member.
The increasing popularity of voice AI for drive-thru is an example of how AI is helping franchises with a niche problem, but franchises are also applying the more generic text- and image-generation capabilities of large language models (like ChatGPT) throughout their workflows. This includes creating social media posts, digesting and summarizing information in large PDFs, interpreting documents, generating Excel formulas, brainstorming names, and responding to customer reviews quickly. But perhaps the most dominant uses are content and marketing.
Pizza Hut Singapore recently announced that its "Takeaway Pocket Pleasers" ad campaign used the generative AI tool Midjourney to quickly create visuals that represent Pizza Hut pizzas in various sizes and flavors, like Cheese 'N' Chic,
Just Cheese, and Chicky Ham 'N' Corn. The franchise trumpeted that it would be passing on these marketing savings to the customer in the form of lower-priced pizzas.
In another example, a recent report on AI in franchising from Brndmkt Consulting shared the experience of an unidentified franchise in the family entertainment industry that used the AI video-editing tool Opus Clip to cut longer brand videos into short clips optimized for social media. The tool could identify key moments in the longer videos, and compress them into 30-to-60-second clips to post. The brand saw a significant increase in engagement, with a 50% rise in likes and shares for the AI-edited video content, and a 30% increase in viewer retention rates.
Another use for AI is helping to bridge the divide between corporate and local marketing. Most franchisees pay a fee to cover their brand's corporate marketing, but local marketing tends to be their responsibility to execute. This leads to hit-or-miss results, because franchisees have to pay a separate marketing agency for their local campaigns, which may or may not adhere to brand guidelines. Balancing the franchise's universal messaging with personalization is a constant challenge.
Generative AI makes this all much easier. ARIA, a software product by Franchisemanager.ai, for example, allows franchisors to create marketing messages that are tailored to each franchise location, all in one stroke — at a cost equivalent to what a single franchisee would have had to pay their marketing agency. This way, franchisees market content that is in their language and that refers to their locations and metadata, but is sanctioned by the mothership.
For example, say you're Dunkin', and it's fall. ARIA will generate a message for you, like: "Fall in love with flavor! Celebrate the season with #Dunkin's pumpkin spice signature latte, every sip is a #sensory adventure." Then, ARIA will localize the message for franchisees, to say something like: "Savor the season at #Dunkin's Harvard Square in Cambridge with our pumpkin spice signature latte. Every sip is a #sensory adventure." ARIA can even tweak messaging according to local idioms and weather forecasts.
As notable as it is that established franchises are adopting AI, perhaps the clearest glimpse of how AI will affect franchising in the future can be seen in a crop of burgeoning brands built by digital natives. These franchises are making AI systems central to how they operate and sell themselves.
Dirty Dough, for example, is a cookie franchise founded in 2018 that now has sold over 400 franchises. Early on, the stores were so overloaded that it could take up to 45 minutes for a customer to receive their box of cookies. The franchisees wanted to solve this, but they also didn't want to overstaff.
The solution the brand landed on was to install cameras that use machine learning and object detection to count the number of employees per hour, as well as customer wait times, and use an equation that considers both metrics to staff appropriately.
The cameras will also be used for quality control and to enforce brand standards. "Some of our cookies were too messy because the employees put too much drizzle on top, so you couldn't eat them in the car," Bennett Maxwell, founder of Dirty Dough, told the Franchise Secrets podcast. Another camera, set up to face the cookies, will detect not only whether the dimensions of the cookies are correct,
but also whether the employees are decorating them correctly. "We all want to perform," Maxwell said, "but sometimes we just don't know what we're doing. This camera system allows us to have better oversight and help our employees succeed."
The idea is that the camera surveillance system would trigger not only corrections for staff, but also corrective interactions with the customer. For example, if the customer's cookie was too small, they might be sent a feedback question, or offered a loyalty credit, or a gift card. "Anytime a customer has a bad experience, we want them to know we see that and are looking out for them," Maxwell said.
Another example of a new franchise that's gone all-in on AI is Lumin Fitness. Lumin is a smart fitness studio concept — similar to Barry's sBootcamp, but more personalized. Walking into a Lumin studio, participants go to their stations, open up the Lumin smartphone app, and put in their earbuds. For the next 45 minutes, even as they're working out with other people, they're essentially getting a personal training session.
A Lumin studio creates an immersive experience akin to a Van Gogh digital exhibit — some featuring 80 feet of LED panels, nine feet high — that rotates every six to eight weeks. There's also a set of sensors, placed throughout the studio, that monitor each participant's movement. "At traditional boutique fitness studios, there's one coach and 14 to 30 participants," says Brandon Bean, cofounder of Mixed Partners, Lumin's parent company. "The coaches' eyes can't be on everyone at once, so people often get hurt, or they're not getting maximum effectiveness from the workout." Lumin's sensors, on the other hand, monitor and track everything, from your posture and position to the number of reps and the weight of your kettlebells. This information is fed into Lumin's software, which analyzes it and pipes feedback and recommendations directly into the participants' ears.
All of this is powered by AI, from the immersive displays and themes to the voices of the AI coaches. Using object detection and pose algorithms, Lumin software has developed an understanding of what, say, an air squat is supposed to look like. "We know how you're performing your squat, and will give you feedback on whether or not you've done a proper rep, as well as your technique and your range of motion," Bean says.
The more customers who come to the studio, the better the feedback loop becomes. The system constantly gets more data on, for instance, how accurate the rep-counting is, and what a squat looks like on a male or a female depending on the placement of their joints.
At a glance, a fitness studio stuffed to the gills with technology can seem like a gimmick. But Bean doesn't think so. Until 2019, he was the CEO of Gold's Gym, a fitness franchise with a history extending back to the 1970s, when Arnold Schwarzenegger worked out at the original location. Bean left because he saw that fitness trends, and what Gen Z wants in particular, are moving away from big-box gyms and toward single-modality, bespoke fitness experiences like Orangetheory, SoulCycle, and CrossFit. "They like the personalization, they like the gamification, and they want to be there in person with other people."
Plus, Bean hopes that with Lumin, he's eliminated some of the common pitfalls for fitness franchises. "The two big risks are low margins because of high labor costs and lack of differentiation," he says. "Say you've got a great cycling studio. Customers love the instructor, but then he goes across the street to a very similar cycling experience and a lot of your members go with him." Lumin saves on labor costs, and due to its technology, its experience can't be replicated easily — for now, at least.
While scores of recent headlines about AI have painted a grim picture of the future, the applications in franchising don't seem too intimidating so far. On the operations side, AI is helping drive efficiency, quality control, and cost savings. Computer vision tracks customer wait times and product quality, improving staffing and standardization. And large language models are generating localized marketing content to bolster franchisees' digital presence.
But while all franchises can find ways to use AI to do the same tasks faster and cheaper, those leading the charge are using AI to reimagine longstanding experiences — from the drive-thru to the fitness studio. Ten years ago, it simply wouldn't have been possible for AI to handle drive-thru orders with the accuracy and reliability necessary to keep cars moving, or to detect minute differences in posture when a fitness freak is doing an air squat. Chances are that these efficient, affordable, and personalized experiences for consumers will become the norm and the expectation. A few years from now, when you meet the next Tori, you won't bat an eye.
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