AI and the Future of Restaurant Management

00:01 – Cristal Craven
Hi everyone. Thank you for joining us today. We have a lot of content to cover and five great speakers, so we’ll get started quickly. We’ll give it another minute, then I’ll make introductions. I’m excited for today’s topic. During our run-through last week, I listened to some impactful thoughts about AI in the restaurant industry—a hot topic right now. We’ll also touch on build versus buy toward the end.

00:49 – Cristal Craven
My name is Cristal Craven. I am the Director of Strategic Partnerships at Synergy Suite, and I’m joined by Jared Neilsen, our Chief Product and Customer Officer, who will discuss some of our initiatives. We also have Cijoy Olickal, founder of GM Pilot; Todd Vahlsing, Head of Restaurant Sales for Nomad; Jason Brockman, a facilitator and professor at Hamburger University (fun fact: Todd is a Hamburger University graduate and spent 26 years at the Golden Arches Supper Club); and Anthony Presley, Managing Partner at TimeForge. Everyone on this call is utilizing AI and machine learning, and we will explore that today.

01:43 – Cristal Craven
Today’s topic is: What does the GM of the future look like? The role of the GM is evolving; expectations from 20–30 years ago are different in this digital age. With the complexity of our industry and AI at the forefront, we will focus on what AI can and cannot do and how it will shape the GM of the future. We’ll close with insights from Jason, who is at the forefront of training future GMs. But first, I’ll ask Jared a quick question to set the stage.

02:27 – Cristal Craven
There are a few dozen people on this call, and everyone likely has a different answer. Jared, what exactly is AI? When we say AI or machine learning, please break it down.

02:38 – Jared Neilsen
There are as many definitions of AI as there are people to define it. A data scientist might say AI is a branch of complex mathematics. In software and technology, AI is generally considered a set of tools that perform tasks typically requiring human input—such as analyzing data, making predictions, identifying trends, and processing voice and visual information. Essentially, these tools accelerate processes that would otherwise take a human considerably more time. It’s not a revolution, but the next step in technological advancement.

03:30 – Cristal Craven
AI encompasses a wide range of applications, and there are many opinions and myths about it. For instance, some say that AI-driven products will replace jobs in the restaurant industry. Todd, what do you think about that?

04:02 – Todd Vahlsing
AI is a tool that enhances productivity. It is not about a futuristic takeover like Skynet. In the restaurant industry, AI serves as a set of tools that help managers be more productive by keeping them in the loop. Good AI enhances managerial decisions and saves time by automating repetitive tasks and providing insights that would otherwise take a long time to uncover.

04:56 – Todd Vahlsing
This enables restaurants to improve guest service, increase profitability, and make better decisions that drive sales at the right time. Our lineup of experts will demonstrate how this works.

05:18 – Cristal Craven
While these benefits are valuable, what would you say to someone who dismisses AI as a fad? Why invest in it?

05:30 – Cijoy Olickal
AI is not a fad. Fashions like bell bottoms and metaverses are temporary trends, but artificial intelligence has been around since 1956 and has fundamentally impacted our lives. In the 90s, voice-to-text was already on desktop computers, and today we carry powerful AI in our pockets. AI is ubiquitous, so it makes sense to take advantage of it.

06:16 – Todd Vahlsing
Everyone needs to have an AI policy, as it is here to stay and will become even more prevalent in our lives and jobs. While Jared mentioned that AI isn’t a revolution, I believe it is a revolution in the restaurant industry—comparable to the introduction of the first POS system or back-office system. It is a game changer for early adopters.

06:55 – Cristal Craven
I even use one of the first POS systems; I still remember the codes for Romanco.

07:01 – Todd Vahlsing
I remember the old days of printed menu tickets and cash registers at the front counter. No one will return to that way of doing things once AI is fully integrated into restaurants.

07:15 – Cristal Craven
But do people really need it? You make numerous technology decisions, and Anthony shared some surprising statistics: an organization typically uses 20,259 software applications and systems, a team uses 45 daily, and an individual uses 52 spreadsheets or applications weekly. Do we need more technology, or do we need AI?

07:49 – Anthony Presley
That’s a great question. The stats come from a Forrester research paper from December 2022, and the numbers have likely grown since then. Additionally, Okta’s annual survey confirms that many organizations use even more applications, including various shadow applications for tracking mileage, maintenance, POs, back-office tasks, labor, and inventory—not to mention communication tools like text messaging for guests.

08:34 – Anthony Presley
Breaking it down, an organization with 2,000, 3,000, or even 5,000 employees might use hundreds of applications. I was skeptical until I attended a MerTech conference where I asked three CIOs about this industry statistic. Two of the larger organizations confirmed they maintain hundreds of applications, while one claimed their tech stack is slim. However, shortly after, that third CIO conceded that they indeed use hundreds of applications.

09:27 – Anthony Presley
The complexity is that managers must navigate dozens of applications daily, from labor management and recruiting to scheduling and follow-ups. The promise of AI is to help managers make decisions by synthesizing data across applications, potentially reducing the number of systems they need to interact with to just a few essential ones.

10:16 – Anthony Presley
Even if there are 500 best-of-breed applications in the future, an integrated AI system can manage them, allowing managers to focus on their core responsibilities.

10:31 – Cristal Craven
Software applications often have their own “language,” essentially asking managers to speak many different languages and switch between them frequently. Streamlining this process is extremely valuable.

11:13 – Cristal Craven
If we agree that we need AI, what does the GM of the future look like?

11:21 – Jason Brockman
To gain a competitive advantage and foster customer loyalty, restaurants must enhance hospitality. When a general manager is bogged down with scheduling, ordering, and other tasks, it detracts from their ability to engage with their team and improve the customer experience. AI—like digital ordering systems, phone apps, and kiosks—saves time and enables managers to focus on what matters. The GM of the future will be an enhanced manager.

12:19 – Jason Brockman
They will have what might be described as “cybernetic inputs” that handle task-based functions rapidly, freeing mental space for focusing on customer loyalty, hospitality, and the employee experience. Ultimately, the restaurant business is about people, and the more time spent on administrative tasks, the less time available for engaging with them.

13:04 – Cristal Craven
Everyone wants to be a good people person, but time is limited. I wish I could spend more time with my crew and guests, but administrative tasks like inventory and scheduling take precedence. While AI for the front of house is appealing, its true impact lies in streamlining back-of-house operations.

13:29 – Cristal Craven
Looking ahead, I’d like to ask Cijoy and Todd—who work directly with two of the biggest areas of management and cost, namely cost of goods and labor—what specific areas will see the most impactful AI adoption in the next five years?

13:52 – Cijoy Olickal
Todd and I agree on focusing our efforts on core costs. Typically, core costs—which account for about 60% of expenses—are evenly split between labor and inventory. Our platform has helped reduce labor costs by 5%—a significant impact on the bottom line—without negatively affecting customer satisfaction; in fact, employee satisfaction improves. This is because AI helps managers avoid the mental strain of switching roles from people management to financial analysis, a challenge we’ve been addressing for over 20 years.

14:37 – Cijoy Olickal
While human analysis doesn’t scale, our platform can perform these tasks efficiently, freeing managers to focus on their teams. With the extra time regained—sometimes a couple of hours per week—they can address inventory issues more effectively, a process that Todd’s solution will further streamline.

14:55 – Todd Vahlsing
That’s correct.

14:59 – Cijoy Olickal
Exactly.

15:01 – Todd Vahlsing
The back of the house is ripe for AI. Many repetitive tasks in the restaurant industry can be automated, allowing managers to focus on the front-of-house operations. Our focus on inventory management is all about giving back the most precious resource: the general manager’s time. I remember when I used to perform manual inventory in freezers and refrigerators—it was time-consuming.

15:49 – Todd Vahlsing
Counting hasn’t changed: you go in, count manually, and record on a clipboard or tablet. Our solution uses spatial AI with an iPhone or iPad to scan a shelf—counting inventory 90% faster and with 99% accuracy. This not only speeds up inventory tasks but also allows for more frequent counts, thereby supercharging back-office systems and improving food cost management.

16:36 – Todd Vahlsing
By removing managers from mundane tasks, we enable them to take actions on the floor that save money. Since the restaurant industry is driven by tight margins, focusing on back-end efficiency is a smart application of AI.

16:58 – Cristal Craven
When discussing AI, we’re addressing both usability and the underlying data infrastructure—massive datasets processed beyond human capacity. A key concern is data privacy, especially as compliance regulations around AI continue to evolve without set standards. Jared, how do you see data privacy playing a role in this?

17:36 – Jared Neilsen
Regulation often lags behind technology. Fortunately, frameworks like GDPR, CCPA, and California’s protection laws are in place, ensuring penalties for lapses in privacy and security. While best practices continue to evolve and SOC 2 controls are being refined, the fundamental principle remains: privacy and security must be integral to the feature specification before any code is written.

18:32 – Jared Neilsen
Privacy by design must be a core consideration in all technology, particularly AI. Companies that treat privacy as an afterthought will face significant challenges. It is essential to prioritize privacy from day one when developing or enhancing any technology.

19:11 – Cristal Craven
How do we ensure that AI doesn’t go off the rails, even with privacy considerations in place? Anthony, you mentioned a term I hadn’t heard before—“hallucinations.” How can we prevent that?

19:24 – Anthony Presley
That’s a great question. At its core, AI is based on mathematical models that require training. These models, composed of many algorithms working in concert, improve over time—much like the model behind ChatGPT. This rigorous math allows AI to analyze visual data and distinguish between foreground and background.

20:15 – Anthony Presley
A model requires training data, and if that data isn’t carefully selected or managed, the AI might be asked to perform tasks it wasn’t designed for. The result can be what is technically called a “hallucination,” where the model generates inaccurate or fabricated information. There are many examples of this online, and it underscores the need for precise training—especially when different companies have different HR policies.

20:56 – Anthony Presley
For example, in labor policies, some companies offer unlimited PTO while others provide only two weeks. If you feed all these HR policies into an AI and ask for the PTO policy of a specific company like TimeForge, it might accurately respond if it has the data. However, if you ask about a company like Boston Robotics, for which it has no data, the AI may provide an average or fabricated response. This is what we refer to as a hallucination.

21:43 – Anthony Presley
In such cases, the AI hallucinates—generating answers despite lacking the necessary data. This can lead to scenarios where the AI makes up information, potentially violating privacy and security policies within an organization. While this isn’t the path to a Skynet scenario, it illustrates how things can go awry if not managed carefully.

22:19 – Cristal Craven
Many are concerned about the ethical implications of AI, yet the efficiency gains are substantial. Jason, given your analysis, how do you balance these efficiency gains with maintaining a human touch for both customers and employees?

22:52 – Jason Brockman
There’s an opportunity cost: the time spent on administrative tasks detracts from engaging with customers and employees. In my training sessions with general managers, I ask them to consider three spheres: the tasks they must complete, the people they interact with (both crew and customers), and the time available for personal growth and leadership development—qualities that bring positive energy to the restaurant.

23:46 – Jason Brockman
When managers are overwhelmed with tasks—reportedly up to 80% of their time—they lack the capacity to invest in their personal development and in interactions with staff and customers. Ideally, a manager’s time would be divided evenly: one third on personal growth and leadership, one third on developing their team and engaging with customers, and one third on essential tasks.

24:33 – Jason Brockman
Currently, most general managers feel out of balance because they devote too much time to tasks that could be expedited with AI tools.

24:52 – Cristal Craven
We’re discussing work balance, but many GMs are salaried and often work more than 40 hours a week. If a manager works 80 hours, 80% of their time on tasks leaves little for personal development and work-life balance. Anthony, having worked with many brands and managers, how do you help reduce their hours and stress?

25:30 – Cristal Craven
How does AI help alleviate this, enabling not just work balance but true work-life balance?

25:37 – Anthony Presley
Overworked managers are a well-documented problem in the industry, exacerbated by COVID. Statistics show that turnover in management is high, with many leaving before two years on the job. With the burden of updating 40 to 50 spreadsheets or applications daily, managers often become overwhelmed. When new applications are introduced, many feel compelled to seek new opportunities. Effective change management is crucial.

26:29 – Anthony Presley
If AI tools are implemented effectively and truly add value—not just as a corporate fad—they can help managers reclaim time for a better work-life balance. There are many examples, especially in budgeting, labor cost management, and turnover analysis, where AI tools streamline operations and reduce administrative burdens.

27:18 – Anthony Presley
Sometimes, the decision to replace a team member is automatic, even when the current team might suffice. AI tools can help by providing data-driven insights to reprioritize staffing needs, potentially allowing managers to reclaim a few hours for personal time—like a date night—rather than being trapped in endless spreadsheets and reports.

28:00 – Jason Brockman
Life balance has an unseen cost in the restaurant industry. The stress from 60–70 hour weeks, coupled with the emotional labor of maintaining a positive demeanor, can lead to serious health issues and increased healthcare costs—including substance abuse. This is a significant consequence of poor work-life balance.

28:53 – Cristal Craven
I’m glad you brought that up; it needs to be acknowledged. The restaurant industry is incredibly stressful, and while we love what we do, it’s challenging. Managers may try to have a date night, but they’re often preoccupied with scheduling and other worries. So how do we address this issue?

29:24 – Cristal Craven
Cijoy, given what GM Pilot does, how do you ensure that managers can enjoy personal time without worrying that AI tools are overshadowing their own judgment? In other words, how do you strike the balance between automation and human oversight?

29:46 – Cijoy Olickal
There’s a clear distinction between what AI is designed to do and what a human GM should do. AI excels at processing vast amounts of data and identifying patterns, but it cannot make nuanced inferences based on limited data—a uniquely human ability. Tasks that require extensive data analysis can be handled by AI, while the human element remains irreplaceable.

30:29 – Cijoy Olickal
Let the machine handle the data processing; that doesn’t diminish the role of the GM. No GM claims that back-office tasks are the best part of their day—it’s about engaging with customers, coaching staff, and driving success. Once a GM adopts and trusts these systems, they can focus on what truly matters, benefiting employees, customers, and investors alike.

31:16 – Todd Vahlsing
Exactly. I’ve been in the restaurant industry for a long time, and the way hospitality is delivered has evolved dramatically—from in-person interactions in the 70s and 80s to drive-through and now delivery, where customer interactions occur in microseconds. The GM must now be more focused on coaching and engaging with staff to ensure top-notch hospitality.

32:06 – Todd Vahlsing
In delivery, hospitality means ensuring orders are accurate, presentation is appealing, and food is served hot. This makes it even more critical for GMs to engage with operations rather than being tied to back-office tasks. We need to give them back that time.

32:30 – Cristal Craven
Jared, as our Product and Customer Officer, you build tools for our customers and gather direct feedback on their usage. As these tools evolve and make life easier, what new skills will GMs need to master to run their businesses?

32:59 – Jared Neilsen
As Todd mentioned, the GM remains the most important person in a restaurant, and that importance will only grow. The tools we’re discussing enhance productivity by enabling tasks to be completed faster, freeing GMs to focus on hospitality. With technological change accelerating, successful GMs will be those who adapt and adopt tools that streamline back-office tasks, allowing them to concentrate on the core business.

33:53 – Jared Neilsen
Back-of-house tasks like inventory, purchasing, and scheduling are essential for business efficiency—they must be done to prevent financial losses. In the future, these tasks will be performed continuously, with real-time inventory data feeding into scheduling and purchasing systems to continually optimize business productivity.

34:28 – Jared Neilsen
In the future, GMs must be dynamic leaders who embrace change and guide their teams accordingly. Those who remain set in their ways will continue to achieve the same results while competitors move ahead.

34:56 – Cristal Craven
So if a GM’s resume lists “agent of …”

35:01 – Jared Neilsen
… change, that’s key. Change management is the most important skill a GM needs—not just for themselves but for the entire restaurant. AI adoption is not a one-time event; change will continue to accelerate.

35:31 – Cristal Craven
I agree. Younger generations naturally adopt these tools, making life somewhat easier, despite added complexities. Many brands recognize the importance of this change and aim to hire GMs who embrace it. However, implementing these technologies, especially in back-office operations, remains a significant challenge.

36:11 – Cristal Craven
Inventory, labor, and scheduling are time-consuming to implement. Todd, with Nomad Go, you’ve managed large-scale implementations. What are the biggest hurdles you’ve encountered with adopting products like Nomad Go, and how can they be overcome?

36:33 – Todd Vahlsing
One of the strengths of the restaurant industry is its ability to adapt and get the job done, often through sheer determination. However, this can be both a blessing and a curse. Many of our products have little competition because others continue doing the same thing, even if it yields diminishing returns—a definition of insanity. If current results are satisfactory, the question becomes: why change?

37:28 – Todd Vahlsing
As Jared mentioned, early adopters gain a competitive advantage. It’s critical for providers to deliver products that are user-friendly and easy to implement in a restaurant setting. Utilizing commercial-grade, readily available technology is key, as younger managers are already familiar with devices like iPhones, iPads, and Android devices.

38:16 – Todd Vahlsing
Providing tools on familiar devices facilitates adoption. Long-term general managers, who are accustomed to doing things a certain way, may find change intimidating as it seems to threaten their authority. However, effective technology doesn’t diminish a GM—it empowers them and gives back valuable time.

39:07 – Todd Vahlsing
If you’re currently working 60 to 80 hours a week, a future with better work–life balance is achievable, enabling you to focus on what truly matters.

39:24 – Cristal Craven
There’s a wide range of GMs—from younger, tech-savvy individuals to veterans who have relied on spreadsheets for decades. Jason, with your PhD in organizational management and experience in training, what tips can you offer to simplify AI training and onboarding for such a diverse group?

40:00 – Jason Brockman
This is a multi-layered question. My background is in organizational development and leadership, specializing in corporate training. The first point is that brands must invest in training—not just in technology but also in developing leadership skills like coaching. For example, I’ve trained GMs as young as 18 or 19, who are managing million-dollar restaurants despite their age.

41:00 – Jason Brockman
Remember that many younger managers are digital natives, having grown up with touchscreens and applications. Training should focus on developing leadership and coaching skills, including learning to leverage the strengths of tech-savvy team members. Investing in these digital natives can enhance onboarding and the effective use of AI tools.

41:53 – Jason Brockman
One effective strategy is to create an AI ambassador program within your restaurant. For experienced managers, admitting that technology may not come as naturally allows you to delegate and empower others to serve as AI ambassadors. This not only facilitates learning but also helps develop the next generation of leaders.

42:35 – Todd Vahlsing
Let me add to Jason’s points. One common mistake is promoting top performers into management without adequate training. Investing in comprehensive management training is crucial—so much so that McDonald’s has its own training school, which I attended. Managers need to invest time not only in teaching tasks but also in explaining the reasons behind them, as well as in developing hospitality and coaching skills, which are not innate to everyone.

43:29 – Todd Vahlsing
Proper training is essential for managers to excel in these areas, and it’s important to lean into this development.

43:40 – Cristal Craven
I agree, Jason. As we approach the end of our session, I want to ensure we have time for questions and to hear what each of you is doing with AI in your companies. Jared, please tell us about what Synergy Suite is working on.

44:05 – Jared Neilsen
Our latest initiative is predictive ordering. We leverage extensive data on sales and current inventory to predict exactly which items will be sold—not just in volume or revenue, but the specific products. The system then automatically generates the order list for the GM, ensuring the right items, in the correct quantities, at the optimal time and price from various vendors. This results in higher-quality orders with significantly less effort, ultimately boosting productivity.

44:50 – Jared Neilsen
This allows them to spend less time on ordering while receiving higher-quality orders.

44:59 – Cristal Craven
Anthony, can you share what TimeForge is doing with AI?

45:03 – Anthony Presley
At TimeForge, we’ve integrated machine learning since 2007 and continuously enhance it as we collect more data. Our system provides enhanced sales forecasting—from 15-minute intervals up to predictions for the next two weeks or even six months. This forecast informs other business decisions, such as scheduling and staffing. For example, if a GM wanted to grant spring break to staff three months in advance, our tool would adjust schedules accordingly.

45:57 – Anthony Presley
We integrate AI into various decision-making processes, including forecasting, scheduling, and compliance—which varies by state. Additionally, our system aids in the hiring process by helping managers decide whom to hire based on factors like location. We also use feedback mechanisms, such as thumbs up or thumbs down for shifts, to analyze employee satisfaction and predict retention issues.

46:48 – Anthony Presley
Employee dissatisfaction might stem from factors like a slow day, low tips, poor management, or inconvenience. Our AI addresses various aspects of the employee experience throughout the application.

47:03 – Cristal Craven
I see some questions coming in, which is great. Todd, could you tell us about Nomad Go?

47:10 – Todd Vahlsing
No one enjoys performing physical inventory. We use a combination of computer vision and spatial AI to recognize and count inventory much faster and more accurately than manual methods—reducing a task that might take an hour to just six minutes with 99% accuracy. This precise data supercharges your back-office system, accounting for unexplained variants that traditional methods might miss.

48:07 – Todd Vahlsing
Using accurate inventory data helps address waste by identifying unexplained variances that frustrate operators. Moreover, it improves managers’ quality of life and mitigates risks such as running out of product—avoiding scenarios where customers are disappointed or a manager must rush to borrow stock, which can lead to traceability and food safety concerns.

48:56 – Todd Vahlsing
For instance, carrying a case of meat in your car for half an hour in the middle of summer is a liability you want to avoid. To prevent such issues, you need accurate data and the right tools. That’s precisely what Nomad Go provides.

49:22 – Cristal Craven
Thank you, Todd. Cijoy, you offer a service rather than a product. Can you tell us about that?

49:27 – Cijoy Olickal
As a restaurant CIO with 30 years in enterprise IT, I’ve seen systems become increasingly capable—and sometimes more complex. The demands on GMs are growing, and many tasks don’t enrich their roles. We wondered: what if we could accelerate the training cycle by running these systems on behalf of the GM? Imagine deploying someone like Brian Roberts—one of my favorite FP&A experts—in every building to manage these systems. We started with labor costs, a major component of core costs. By optimizing labor, we free up funds that can be reinvested in areas like marketing spend, online ordering thresholds, and inventory management. This approach takes away much of the theoretical workload from the GM, allowing them to focus on customer interaction.

50:44 – Cijoy Olickal
We operate your existing software like a super analyst working overnight, producing analytics that reveal where money is lost and who is performing well. Our service can eliminate biases in scheduling, ensuring that the best people get the best shifts—whether it’s matching appetizer specialists to peak times or balancing family schedules. By modeling human intuition on our platform, we deliver creative results that make employees, guests, and GMs happier. This is the focus of our service at WijianPilot.

51:26 – Cristal Craven
I know our panelists are eager to connect further; you can find them on LinkedIn. I believe you’re doing some innovative work in the industry. Now, for a final question: Jason, what is the next iteration of AI and technology for restaurants? What comes after controlling core costs?

52:07 – Jason Brockman
In the coming years, beyond the applications we’ve discussed today, expect increased use of AI in simulations for training and development. There’s also significant potential for AI in real-time translation, ensuring that customers who speak different languages receive a seamless experience—particularly in tourist-heavy areas.

52:46 – Jason Brockman
Adaptive learning and simulation will be crucial, allowing individuals to practice essential skills such as emotional intelligence and conflict management in a safe, controlled environment. AI could simulate scenarios like dealing with an upset customer or managing challenging situations, thereby preparing new employees for real-life interactions. Training and development in leadership skills are where the future lies.

53:37 – Cristal Craven
That’s a practical application, as conflict resolution in real time is challenging. I’d love to see that technology emerge. One key point you made was that the GM of the future won’t just be a manager—it will be a leader. That’s incredibly poignant. We have five minutes and five questions left, so I’ll try to cover them quickly.

54:18 – Cristal Craven
Here’s a great question: How do you see AI reshaping the typical workday of a GM in the next five years? I’ll open this up for discussion. If we don’t cover everything, we’ll follow up with an email.

54:44 – Anthony Presley
The workday still begins with a long list of tasks, which is why many GMs work 60 to 70 hours a week—because an eight-hour day isn’t enough. Despite that, the core tasks of a restaurant still need to be completed.

55:22 – Anthony Presley
I hope to see more software products that use AI to make data-driven decisions, reducing the number of manual tasks a GM must complete—be it purchasing, inventory counts, or even aspects of performance management. This will ultimately lessen the workload.

56:04 – Todd Vahlsing
I agree with Anthony. In the future, GMs could start their day with an AI-generated list of the most impactful actions for improving profitability and guest satisfaction—essentially an AI roadmap. This would shift focus from overwhelming task lists to exception reporting, empowering managers to take the right actions.

56:55 – Todd Vahlsing
This approach would reduce the stress of decision-making, allowing managers to focus on personal interactions with customers and staff—ultimately enabling them to perform their roles more effectively.

57:20 – Cristal Craven
We have just a minute left, so I’ll briefly touch on a couple more questions and follow up via email. How should operators consider AI’s impact on future technology and service implementation? For restaurant brands looking to integrate AI, where should they start, and what advice would you offer GMs preparing for increased AI integration? Jason, I have a great question for you.

57:57 – Cristal Craven
Another question: Younger generations are often seen as less interested in working in restaurants, including in management roles. Do you agree, and can AI make these jobs more fulfilling? (Feel free to share your thoughts.) We are now down to the final seconds. Thank you so much to everyone for joining the call. We’ll follow up with additional details via email. Thank you to our panelists—I am excited about today’s discussion, and although we didn’t cover build versus buy, perhaps that will be our next webinar topic. I truly appreciate everyone’s time.

58:37 – Cristal Craven
Thank you, everyone. Goodbye.