I‘m going to share a little inside baseball with you. When I saw the topic ’AI and franchising,‘ I was nervous. It’s a niche subject, and I wanted to cover more than just the expected franchises. You know, the famous fast food franchises. (Although you will find some of that in this article, too.)
Anywho, I was nervous because I thought I wouldn‘t be able to speak directly to any franchises that are currently using AI. Fortunately, I was blessed to hear directly from franchise organizations and people who work with them to implement AI tech. Long story short? I’ve gone from *cold sweats nervous* to super excited to share what I’ve learned with you!
Table of Contents
- How AI Is Used in Franchising
- Benefits of AI and Franchising
- Challenges of AI and Franchising
- Examples of AI Franchising
How AI Is Used in Franchising
Below, you‘ll find various examples of how you can use AI within your franchise organization. I’ve also gathered insights from AI experts — or experts in a relevant field — and corresponding examples of each use case.
Marketing
Around 75% of marketers use AI to reduce manual task time. Manual tasks include anything from image generation, video editing, and content production. However, one area where AI excels in particular is sourcing and organizing data. That‘s because AI tools can process and collate vast amounts of data in minutes, seconds even. Humans simply can’t outpace the tech here. The good news? We can ‘leverage’ (sorry) it!
Beyond collating and organizing data, 44% of marketers find AI very effective at analyzing data. Although, when it comes to analysis, I‘d recommend always keeping a human in the driving seat. It’s all too easy for AI to miss a nuance in the data that a human familiar with your franchise’s inner workings might not.
In Action
Ben Goodey, the founder of Spicy Margarita Content and the SEO podcast and case studies community How the F*ck, shares how he uses AI to assist data organization and analysis. More specifically, he discusses using AI to speed up his location-based keyword research process.
“One of my favorite uses of AI is to scan through tons of keyword research to find the topic I’m looking for,” says Goodey. “For franchise businesses, this is really useful as it can be used to help them find location-based keywords, which with the right technique helps their franchises win more customers in their area.”
Goodey explains how his client Eton, who offers business valuation services, has many location-based keywords like ‘business valuation services in Los Angeles’ for their niche. That’s because some of the legal aspects of the work change based on location.
Much like a franchise business, Eton works across all these locations, so part of the SEO strategy includes creating a locally targeted page optimized for each area.
He adds: “AI is really useful here. You can download a CSV of the entire’ business valuations’ keyword group, which has 1000s of keywords and would take hours to sift through. Then, upload it to ChatGPT and ask it to create another column that flags if there is a location in the keyword phrase. It makes it really quick to find your location-based keywords and start building pages to rank and help customers find you in those areas.”
Data Discovery and Accessibility
Research shows that nearly 40% of data leaders cite the “increasing volume and variety of data” as a significant AI roadblock. That said, when you equip your franchise with the proper tooling and a solid AI business integration roadmap, it‘s much easier to wrangle your data. In fact, the sheer volume of data at your fingertips can become your business’ biggest strength.
In a franchise setup, AI can help you understand what’s happening across hundreds or even thousands of locations. Depending on your chosen AI tool, even non-tech-savvy stakeholders in a franchise network can effortlessly search, discover, and use data. That could be anything from sourcing specific customer information to location-based revenue figures.
In Action
Dexter Chu, head of marketing at data enablement platform Secoda, shares their take on how franchises can use AI to make data more accessible throughout an organization.
He explains that AI data catalog tools allow users “to ask questions to their data in natural language to self-serve insights they wouldn’t have access to otherwise.” Further, AI can surface trends, detect anomalies, and “offer predictive insights to optimize operations across different franchise locations.”
German hypermarket chain Kaufland E-commerce operates much like a franchise. It uses Secoda’s AI-driven platform for data discovery, accessibility, and analysis. Through the no-code platform, they can build and maintain “a consolidated view of all data assets.”
Additionally, Kaufland’s data and analytics team “integrated documentation into their table creation process to ensure all data is verified and up to date, reduced time to insight, and increased transparency.”
Customer Support
Around 67% of customers expect companies to resolve tickets within three hours. Meanwhile, over 90% of CRM leaders say AI has improved customer service response times. It’s no wonder, then, that businesses of all kinds, including franchises, are adopting AI to help with customer support.
In Action
When it comes to franchises, in particular, there are numerous ways your organization can enlist AI for customer support. Be that through AI-powered chatbots, self-service resources, or even personalized in-app recommendations based on user preferences.
After interviewing multiple experts about the pros and cons of AI in customer service, I have a word of warning … For all AI’s advantages, including faster response times, it can never replace the human touch.
AI should free up your service team to spend more time on human-centered tasks that move the needle.
AI should not replace the human touch that often prevents service issues from escalating, leading to unhappy customers, and finally churning.
Automation
Dexter Chu says AI tools and data catalogs “offer franchises the ability to automate manual tasks and get more time back in their day.” Automation might include anything from marketing, data discovery, and customer support. Franchises also use AI to automate inventory management, reporting, and resource allocation.
In Action
Returning to Kaufland E-commerce, I love how they used Secoda’s announcement feature to automate stakeholder communication. This feature informs relevant stakeholders of any changes to critical assets.
According to the case study, Secoda automatically grabs the lineage relationships between each data source in the event of a schema change. Then, Kaufland E-commerce triggers a notification to the downstream owners via Slack. This means that people throughout the organization (including across multiple locations) “are always up-to-date with the latest changes and can easily collaborate.”
Benefits of AI and Franchising
So, what are the key benefits for franchises that integrate AI into their operations? I dove into data and reached out to experts for answers.
Time Savings
I was fortunate to speak to Joseph Conlon, the digital director at the franchise organization We Make Footballers. He shares some of the key benefits they’ve found by integrating AI tools into the franchise, all culminating in saving their team time.
“As a franchise organization, we have found a lot of value in using AI tools,” says Conlon. “We regularly rely on ChatGPT for tasks like analyzing copywriting, automating routine reports, and responding to reviews personally. Additionally, we use generative imaging techniques, such as removing backgrounds from images of our coaches and removing ‘off brand’ material from our images.”
Conlon explains how the insights the team has gained from AI’s ability to interpret their various data sources and provide suggestions have been invaluable. He adds: “We are saving time, cost, and resource by adopting these tools and will continue to incorporate more tools as the industry continues to evolve and we find more use cases for AI to support.”
Looking at the data, AI is set to continue saving us time. The Thomson Reuters Future of Professionals report finds that: “Respondents predicted that artificial intelligence (AI) has the potential to save them 12 hours per week in the next five years, or four hours per week over the upcoming year – equating to 200 hours annually.”
Increased Productivity
If you and your franchise team save time through AI, it makes sense that overall productivity increases. In fact, “Businesses using AI-driven data tools have seen up to a 40% boost in productivity,” says Secoda’s head of marketing, Dexter Chu.
Part of this increased productivity comes from using AI tools to “automate repetitive tasks such as data documentation, metadata management, and query resolution.” Chu adds, “This reduces the manual workload on franchise staff, allowing them to focus on higher-value activities such as customer service or strategic growth initiatives, with decision-making speed increasing by up to 10x.”
Reduced Operational Costs
What is the impact of clawing back your team’s time and increasing productivity? Reduced operational costs. Don’t just take my word for it. Joseph Conlon mentioned his franchise organization saving “cost and resource by adopting these tools.” Dexter Chu mirrors this point, citing “a 60% reduction in data management costs” through AI tooling.
Returning to the Future of Professionals report, we can see how saving up to 12 hours per week within the next five years could impact billable hours. The report states, “For a US lawyer, this could translate to an additional $100,000 in billable hours.” Further, the time saved could stack up to the “equivalent of adding an additional colleague for every 10 team members.”
Challenges of AI and Franchising
Below, I share insights from a franchise organization and AI experts who work with franchises to implement the technology. We get into it about the challenges that come with AI and franchising.
Identifying Use Cases
Joseph Conlon from the franchise organization We Make Footballers shared the many benefits he and his team have experienced using AI above. He was also generous enough to share some of the challenges he faced.
“Our initial challenge was identifying the best use cases for AI within our business,” says Conlon. “There were seemingly endless pathways we could go down which initially felt quite overwhelming and impossible to achieve with the associated costs.”
He adds, “Each different stakeholder in the company, from Marketing to Operations to Tech, needed a number of different tasks or processes automated, generated or made more accessible. In all cases, there were different priority levels and orders of magnitude and complexity.”
To overcome this, We Make Footballers worked with an AI Consultancy called Delegaite to identify “a pathway towards what would be most beneficial for our organization and built out a roadmap of how we would reach our north star.”
Interpreting Data
Building their roadmap meant “bringing all our data sources into one data platform that we could then analyze.” Beyond that, the next step “took many painstaking months.” We Make Footballers focused on interpreting this data and ensuring they could reference it correctly when required.
Conlon explains that this required a lot of manual analysis and reconfiguring the in-house technology ecosystem, “which had both financial and resource implications.”
He adds: “We are very early in the journey, and part of the challenge is not getting carried away with what is currently possible or could be possible. We have to be patient with the process and build our capability over time and in alignment with our strategic objectives.”
Data Silos
John Pennypacker, VP of Sales and Marketing at Deep Cognition, shares one of the most significant challenges the company has encountered when implementing AI solutions for franchise networks.
“Franchises, by nature, operate as semi-independent entities, often with their own localized systems and data collection methods,” says Pennypacker. “This decentralization can create a maze of disconnected data silos that hinder the effectiveness of AI implementations across the entire franchise network.”
He adds, «We worked with a large quick-service restaurant franchise that wanted to use AI to optimize inventory and predict customer demand. While the corporate office was eager to roll out a network-wide AI solution, we quickly discovered that each franchise location had its own point-of-sale system, inventory tracking method, and even different naming conventions for menu items.»
Pennypacker explains how this fragmentation meant it had to undertake a massive data standardization project before the team could even begin training its AI models. The project took months of collaboration with franchise owners to align data formats, create universal APIs, and “establish a centralized data lake that could feed our AI systems with consistent, quality data from all locations.”
“The challenge wasn’t just technical — it was also deeply human,” says Pennypacker. “We had to navigate the concerns of franchise owners about data privacy, the potential loss of autonomy, and the fear of being compared unfavorably to other locations once all the data was centralized and analyzed.”
According to Pennypacker, overcoming this challenge required a delicate balance of technical innovation and change management. «We ended up developing a hybrid AI model that could work with both standardized and non-standardized data, along with a phased implementation approach that allowed franchise owners to see the benefits gradually, building trust in the system over time.
“This experience taught us that in franchising, the success of AI isn‘t just about the algorithm — it’s about creating a data ecosystem that respects the unique nature of franchise networks while still enabling the power of centralized AI insights.»
Examples of AI Franchising
Now, it’s time to see AI and franchising in action. I relay the direct experience of franchise organizations and those who work with franchises specifically to integrate AI. I also share examples from franchise outfits you may already know and love.
Hopefully, there‘s a range of inspiration that’ll help you wherever you are in your AI and franchising journey.
We Make Footballers
Joseph Conlon, the digital director of We Make Footballers, has already shared the benefits and challenges they’ve faced with AI. Now, he shares more details about how the franchise organization integrates AI within the business.
“We started the journey of using AI in our franchise organization some 12 months ago,” says Conlon. “We are currently using GenAI within a wide range of everyday tools such as graphics production, creating franchise training modules, video editing on Podcasts, email content production, and copywriting.”
He adds: “At a more sophisticated level, we are beginning to use it to analyze large data sets across our organization and provide insights and analysis that would not be possible (or at least be extremely time intensive) by human observation.”
Conlon explains that these insights help the team understand franchise performance, marketing analysis, and customer experience trends across the business. Plus, they can “quickly flag up issues that might occur and essentially query all our data sets on demand.”
To make AI work for them, We Make Footballers have “provided training for all our head office staff and recommended our franchisees to adopt the responsible use of AI where it makes sense within the delivery of their organization.”
My thoughts? I love how We Make Footballers use AI to work with large data sets across the organization. It’s hard to deny that AI has an advantage over humans regarding how quickly it can process data.
That said, you must also recognize how vital data permission security is in this effort. That’s why I also love how We Make Footballers have trained their head office staff with “responsible use of AI” in mind.
Lanch/Happy Slice
The Co-Founder and CEO of Torg, an AI-powered platform for sourcing food and beverage products, Hans Kristian Furuseth, contacted me to share how they work with Lanch/Happy Slice. For context, Lanch/Happy Slice is Germany’s seventh-largest franchise chain.
Furuseth explains how the franchise sought manufacturers to produce for their restaurants. “They were looking for producers for a wide range of products,” says Furuseth, “including pizza crusts that they had unsuccessfully tried to source with a traditional procurement consultancy where they, after three months, had only gotten three quotes, all above their target price.”
He adds: “They, therefore, wanted to test Torg. Within two weeks, they received 15 quotes from top manufacturers, most below their target price.”
If you’ve read literally anything I‘ve written about AI, you’ll know I’m a big fan of keeping humans front and center. For example, the quality and effectiveness of elements like content writing or customer service can soon nose dive without human intervention. However, for some tasks, AI is more efficient than humans.
For this franchise, the difference was between waiting three months for three pizza crust quotes or receiving 15 quotes within two weeks. However, my instincts say there could be even greater success by merging a human team with AI here. But that’s based on my observations and many interviews with other folks using AI in their businesses.
McDonald’s
Regarding the drive-thru, McDonald’s has used AI-powered technology in multiple ways. The first one I’ll talk about is my favorite: order prediction.
I love how McDonald‘s uses AI for dynamic menu boards. Their system analyzes external factors like weather and time of day to recommend items. For instance, it might highlight hot beverages and comfort foods on a rainy day and share them on digital displays. This level of personalization helps McDonald’s create a better customer experience and drive sales.
The second use of AI is something McDonald’s has recently walked back since launching the service in 2021. McDonald‘s has been testing drive-thru voice AI for the last few years. Through the technology, the franchise could offer automated order-taking (AOT). Although McDonald’s representatives say “there have been successes to date,” they are now exploring “voice ordering solutions more broadly.”
In my humble opinion, something like the drive-thru is still best served with the human touch. Why? Well, it’s called fast food for a reason. I can only imagine how frustrating it could be if the AOT misunderstood your order or got it wrong. Then, a human had to resolve your order anyway. That’s adding a chunk of time onto what you had planned to be a quick breakfast before work.
Anytime Fitness
The franchise Anytime Fitness has integrated AI into its app to provide personalized customer experiences. More specifically, the app offers customized workout plans and nutrition advice. By analyzing user data — like workout frequency, preferences, and even personal fitness goals — AI can generate customized plans that adapt as members progress.
According to Gartner, “over 80% of organizations expect to compete mainly based on CX.” The crux? Personalization is increasingly becoming the difference maker when it comes to customer experience. That’s why I appreciate the level of personalization in this use case. It not only keeps members motivated but also helps them achieve their goals more effectively.
It Doesn’t Take Grandiose Changes for AI to Impact Your Franchise
You don’t need to make grandiose organizational changes to make AI in franchising work for you. A little purposeful action goes a long way. Take the franchise Lanch/Happy Slice, for example. By adopting a single tool, they sped up sourcing manufacturers to produce for their restaurants by months.
Then take We Make Footballers, who have used AI in their franchise for about a year. The use cases are varied with tasks like analyzing copywriting, automating routine reports, and responding to reviews personally. Still, they have taken a grounded and gradual approach to implementing the technology.
As an organization, they recognize that part of the challenge “is not getting carried away with what is currently possible or could be possible.” Instead, it’s vital “to be patient with the process and build our capability over time and in alignment with our strategic objectives.”
I don’t know about you, but I think those are very wise words to end this article on, indeed.