The impact of AI on fast food and retail jobs.

Introduction

Advances in artificial intelligence (AI) and automation are rapidly transforming service industries like fast food and retail. Self-service kiosks, shelf-scanning robots, AI-driven data analytics, and even robotic cooks are becoming increasingly common. These technologies promise efficiency and cost savings for businesses, but they also raise concerns about job displacement and the future of work for millions of low-skill employees. In sectors traditionally staffed by entry-level and hourly workers – cashiers, sales associates, cooks, and servers – automation poses significant social and economic challenges. This article examines the impact of AI-driven labor automation on these low-level jobs, detailing who is affected and how large the impact may be, and then explores mitigation strategies. In particular, it evaluates two proposed solutions to cushion the negative effects: “human-in-the-loop” approaches (keeping humans involved alongside AI) and corporate upskilling programs that retrain workers for new roles. The thesis is that while AI automation threatens to displace many workers in fast food and retail, combining human oversight with AI and proactively upskilling employees can mitigate these harms by preserving employment opportunities and helping workers transition to more advanced tasks. Evidence from recent industry trends and expert analyses will be used to demonstrate both the scope of the problem and the effectiveness of these solutions.

AI and Automation Threaten Low-Wage Service Jobs

AI and robotics are now capable of performing many repetitive, routine tasks that characterize low-wage jobs in retail and food service. For example, in fast food restaurants, touchscreen ordering kiosks and drive-thru AI voice assistants can replace human cashiers, while robotic kitchen equipment can assemble burgers or fry foods without human cooks. In retail stores, self-checkout machines and inventory-scanning robots reduce the need for checkout clerks and stockers. These technologies directly threaten roles that require relatively basic skills or little formal education – the very jobs that have historically provided entry points into the labor force for teenagers, students, and workers without college degrees. Indeed, an OECD analysis found that jobs requiring only low or basic education will bear the brunt of automation’s impact, and that many “teenage jobs” (common first jobs for young people) are among those at highest risk[1]. In particular, fast-food counter workers and retail cashiers are often cited as being at high risk of replacement by machines.

By the Numbers: The Scale of Automation’s Impact
- More than 80% of restaurant positions could be automated, including 57% of fast-food counter and cashier roles[2].
- The U.S. fast food industry employs about 3.8 million people (as of 2022)[3], and over 9 million Americans work in retail sales or cashier positions[4]. These are the jobs most directly in the crosshairs of AI-driven automation.
- One restaurant industry analysis estimated that 57% of fast-food counter jobs could ultimately be done by robots[2]. The U.S. Bureau of Labor Statistics already projects a 7.4% decline in the number of cashier jobs from 2019 to 2029, largely due to self-checkout kiosks and mobile payments[5].
- Globally, the World Economic Forum’s Future of Jobs 2025 report predicts that 92 million jobs will be displaced by automation by 2030, even as 170 million new tech-driven roles are created – a net gain, but only for those equipped with the skills to fill the new positions[6]. In other words, nearly 14% of the global workforce may need to transition to different occupations by the end of this decade due to AI and automation[7].

Who Is Most Affected? The workers most negatively affected by these changes are typically those with fewer skills, less education, and limited mobility in the job market. In the U.S., fast food counter attendants, line cooks, retail salespeople, and cashiers make up a huge share of teenage and entry-level employment. For many adolescents and young adults, a part-time job at a restaurant or store is a first work experience; unfortunately, researchers note that “the risk of automation is highest among teenage jobs,” meaning the youngest workers may see their opportunities shrink first[1]. Likewise, older workers with years of experience in manual service roles may struggle to find new work if their jobs are eliminated, since their skills often do not easily transfer to more technical occupations. The economic impact on these individuals can be severe – loss of income, long periods of unemployment, and the need to accept lower-paying work if they lack the skills that automated workplaces demand. At a community level, when big retailers or fast food chains automate, entire local economies can suffer from reduced consumer spending by displaced workers. Some analysts worry that unmitigated automation could worsen inequality, as low-wage workers lose jobs while owners of technology and higher-skill professionals reap the gains.

Psychological and Social Impacts on Workers. Beyond direct job loss, there are psychological and social consequences to consider. The threat of automation looms large in workers’ minds, sometimes even before the technology is deployed. In the fast food industry, executives have often invoked the specter of automation as a bargaining chip – for instance, warning that raising the minimum wage will force restaurants to install more robots and hire fewer people. For years, “the fast food industry has used the threat of automation to avoid paying workers more,” essentially telling employees that “if labor gets too expensive, we’ll replace you with machines”[8]. This tactic fosters anxiety and insecurity among workers. It can also be seen as ethically problematic: companies are arguably using fear of technology to undercut workers’ demands for fair pay. The result is often a demoralized workforce that feels undervalued and constantly replaceable.

Automation: Replacement vs. Augmentation

It is important to note that the impact of AI on jobs is not entirely one-dimensional or uniformly negative. In some cases, automation is augmenting workers rather than fully replacing them. Forward-looking companies have experimented with ways to have humans and machines work side by side, each doing what they do best. The underlying rationale is that humans and AI have complementary strengths: AI excels at “reckoning” – fast calculation, data processing, and repetitive precision – whereas humans excel at “judgment” – common sense, ethical reasoning, empathy, and adaptability[9]. When a routine task is automated, the human worker can shift to more complex duties that benefit from human judgment. In fact, experts argue that a “human + AI” team often outperforms AI alone, since people can handle exceptions and provide context that machines lack[10]. This optimistic scenario envisions robots taking over the drudgery while employees focus on higher-value, customer-facing, or creative activities – potentially making their jobs more engaging, not less.

Real-world examples from the food service industry show how augmentation can work. Fast-casual restaurant Chipotle recently introduced a robotic system for certain kitchen tasks (including an “Autocado” robot that preps avocados for guacamole, and an automated assembly line for bowls and salads), but the company explicitly stated these cobots “will not eliminate any jobs.” Instead, human crew members work in a “collaborative” arrangement with the machines, focusing on more complex orders and customer service while the robots handle repetitive prep tasks[11]. In fact, early pilot programs suggest that automation can even increase the need for human labor in some areas by making businesses more efficient and boosting demand. McDonald’s, for example, found that when it installed self-service kiosks, customers tended to order more items; this led to extra kitchen work that required human staff to fulfill, offsetting any reduction in cashier labor[12]. In scenarios like these, robots take over the mundane tasks but also create new tasks for people – a form of “augmentation” rather than pure replacement.

However, these benefits tend to materialize only when companies deliberately integrate technology in a worker-friendly way. If adopted carelessly with a pure cost-cutting mindset, automation in retail and food service can indeed displace large numbers of vulnerable workers. The contrast is stark when looking at an extreme case: a fully automated restaurant. In 2025, a restaurant called BurgerBot launched what it billed as the world’s first completely automated fast-food establishment. Robots handle the entire burger assembly process without any human cooks or cashiers on site. The restaurant touts the “cold, hard efficiency” of an all-robot kitchen – the machines never need breaks or sick days, won’t demand higher wages, and even promise improved hygiene (as their marketing humorously puts it, no more finding “curly hairs in your buns”)[13]. While BurgerBot eliminates labor costs and treats the absence of human workers as a novelty selling point, it faces open questions about customer acceptance. Many patrons may miss the human interaction or distrust a completely robotic experience. Even BurgerBot acknowledges that “the robots are taking our jobs” and frames it as inevitable, but the dining experience it offers is impersonal by design[14][15]. This raises a critical point: a balanced approach – where automation is introduced but humans are kept in the loop – might ultimately be more sustainable and broadly acceptable than an extreme all-robot model. Mainstream businesses may find that combining AI efficiency with the empathy and flexibility of employees yields the best results in terms of service quality and customer satisfaction.

In summary, automation’s impact on fast food and retail jobs can follow two divergent paths: one of replacement, in which machines wholly substitute for humans (as in the BurgerBot example), and one of augmentation, in which machines and humans work together. The next sections discuss strategies to ensure we lean toward the augmentation path, preserving jobs and empowering workers even as AI becomes more prevalent.

Strategies to Mitigate Automation’s Impact on Workers

To address the negative impacts of AI mechanization on low-level service jobs, experts and industry leaders have proposed several strategies. Two of the most prominent are: (1) adopting “human-in-the-loop” automation designs, and (2) investing in upskilling or retraining programs for employees. These solutions seek to balance the efficiency gains of automation with the irreplaceable strengths of human workers, thereby preserving employment and smoothing the transition to a more AI-centric workplace. Below, we explain each proposal in detail and evaluate their effectiveness with evidence and examples.

1. Human-in-the-Loop Automation (Augmentation, Not Replacement)

A human-in-the-loop approach means designing AI systems to work with and under the oversight of human beings, instead of aiming for full autonomy. In practical terms, this could mean using AI to handle repetitive or physically demanding tasks while keeping humans in control of decision-making, customer interaction, and supervision of the technology. The guiding principle is that automation should augment human labor rather than replace it entirely. By keeping a person in the loop, companies can ensure that critical decisions or exceptions are handled with human judgment, reducing errors and improving service quality. It also inherently preserves some human roles that fully autonomous systems would eliminate. AI excels at speed and consistency, but humans excel at adaptability and understanding context – so a hybrid system can leverage the best of both.

Figure 1: A Chipotle crew member (top) works alongside an automated makeline (beneath the counter) that assembles bowls autonomously while she prepares more complex orders, illustrating a collaborative human–robot process. Chipotle’s approach integrates human-in-the-loop robotics: the robot increases efficiency for routine tasks, while humans focus on customer-facing work and quality control (Photo courtesy of Chipotle).

In the context of fast food and retail, human-in-the-loop design can take many forms. One example is the “cobotic” kitchen model at Chipotle mentioned earlier. The robot (located under the counter in Figure 1) builds simple bowl orders from a digital queue, but a human worker is still right there preparing the final platters, handling custom orders like burritos or tacos, and interacting with customers. This is a collaborative process rather than a replacement – the automation boosts output for routine orders, while humans ensure everything meets quality standards and that non-routine needs are met. Similarly, Amazon’s experimental cashierless grocery stores (Amazon Go) use AI vision systems to automate the checkout process, yet they still employ human staff in each store to handle customer questions, restock shelves, and troubleshoot issues. Many big-box retailers deploying shelf-scanning robots also retain human workers to interpret the data (deciding how to resolve inventory problems) and to perform tasks the robots cannot, like delicate merchandising or helping indecisive shoppers. In car dealerships, AI tools might automate initial paperwork or online chat inquiries, but human salespeople remain in the loop to provide personalized advice, handle negotiations, and build customer relationships. All these scenarios exemplify augmentation – using AI to enhance human productivity rather than render the human obsolete.

The benefit of human-in-the-loop systems is twofold. First, they help preserve jobs (or even create new ones) by ensuring that automation does not completely replace human labor. The tasks and skill requirements of a job might change – for instance, a fast food worker might spend less time taking orders and more time expediting orders or managing the machines – but the worker remains employed in a meaningful capacity. Second, these approaches often yield better business outcomes in terms of quality and flexibility. Humans in the loop provide creativity, empathy, and problem-solving abilities that machines lack; they can handle unusual requests or solve problems when the automated system encounters something unexpected. This can lead to higher customer satisfaction and trust. For example, even the most advanced burger-flipping robot cannot appease an angry customer’s complaint or accommodate a special dietary request – but a human employee can. Keeping employees in customer-facing or supervisory roles thus maintains a level of service quality and personal touch that pure automation would lose. Research in various industries has underscored that human–AI teams usually outperform AI alone because humans can catch the AI’s mistakes and provide context that the technology doesn’t have[10]. In white-collar fields, this concept is sometimes called intelligence augmentation (IA), and it is equally applicable to service industries like restaurants and retail.

Real-world deployments support the viability of human-in-the-loop automation. We’ve already noted Chipotle’s approach: the company explicitly designed its Autocado robot and automated makeline to work in tandem with human crew, “supposed to have a ‘cobotic relationship’” with employees, and stated that introducing these robots “will not eliminate any jobs”[11]. Instead, the goal is to free up staff for more valuable tasks – employees can spend more time on food prep that requires finesse or on providing hospitality to customers, rather than tediously chopping vegetables or portioning rice. A labor economist observing these pilots confirmed that the worst fears of mass job loss haven’t materialized; automation, in these cases, “has shown to make workers more productive and effective,” and the increased efficiency can lead companies to grow or reassign staff rather than fire them[16][12]. Another example comes from the burger chain White Castle, which has been testing a robotic fry cook named Flippy 2 (from Miso Robotics). At one White Castle location, Flippy 2 handles the hot fryers for French fries and chicken, a task that is repetitive and hazardous. By doing so, the robot frees up an employee who would have been stuck at the fry station to instead work at the “hospitality” position – greeting drive-thru customers and delivering orders to cars – which improved service speed by 15–25% at that store[17]. In other words, the robot took over a dull job and enabled a person to perform a more customer-centric role, resulting in faster service. Notably, White Castle did this during a time of labor shortages; the intent was to augment a shorthanded team, not to lay off workers. These case studies show that when implemented thoughtfully, human-in-the-loop automation can be a win–win: workers keep their jobs (often doing safer or more enjoyable tasks), and businesses gain efficiency and customer service improvements.

One potential drawback of human-in-the-loop designs is that they may offer fewer immediate cost savings than full automation. Companies might be tempted to eliminate as many workers as possible to maximize labor cost reduction in the short run. However, the long-term advantages of augmentation – including higher quality output, better safety, and sustained customer loyalty – can outweigh the immediate savings of an all-robot workforce. The case of BurgerBot (the fully automated restaurant) illustrates this tension. While BurgerBot drastically cuts labor costs and showcases cutting-edge tech, it also faces skepticism about an experience with no human workers. Many customers value human interaction, or at least the assurance that a person is overseeing quality and available to help if something goes wrong. Thus, a hybrid approach – automation with human oversight – might ultimately be more sustainable for most businesses than an extreme push to remove humans entirely. On balance, the evidence suggests that human-in-the-loop strategies can be an effective solution: they leverage technology for efficiency but still value human labor for its unique capabilities, thereby mitigating the social harm of job loss. Companies pursuing this path (like Chipotle or White Castle with its Flippy assistant) have managed to improve productivity without mass layoffs, often by retraining or reassigning workers to new tasks that emerge from the technology deployment.

2. Upskilling and Reskilling Programs for Workers

The second major proposal to address AI’s impact is to equip the affected workers with new skills so that they can transition into the jobs that automation creates, or into other roles that are less automatable. Upskilling refers to training current employees in new or more advanced skills that allow them to move into higher-value positions (often within the same company). Reskilling is similar, though it typically implies preparing workers for a different career path after their old job is eliminated. The premise here is that while technology may eliminate certain tasks, it also generates demand for new tasks and oversight roles – and with proper training, displaced workers can fill those new positions. Rather than leaving low-skill employees behind, companies (and society at large) can “lift up” the workforce to be compatible with an AI-driven economy.

Corporate upskilling has gained traction in recent years as business leaders acknowledge their workforce will need help adapting to rapid technological change. A McKinsey Global Institute analysis estimated that by 2030, as many as 375 million workers worldwide (about 14% of the global workforce) will need to switch occupational categories or acquire new skills due to automation and AI disruption[7]. Such a massive shift cannot be managed by hiring new talent alone; it requires retraining existing workers at an unprecedented scale. In a survey of executives at large companies (>$100 million revenue), 82% said that retraining and upskilling employees is at least half of the answer to addressing the skill gaps caused by automation[18]. Crucially, these business leaders also believed that companies – not just governments or individuals – must take the lead in this effort (by a 5-to-1 margin over those who thought government should lead)[19]. This sentiment has led to highly publicized corporate initiatives aimed at workforce development, acknowledging that simply automating tasks and laying off workers is socially and economically unsustainable in the long run.

Several large companies have already launched ambitious upskilling programs for their employees. Two notable examples:

• AT&T (Future Ready Initiative): In 2018, telecom giant AT&T committed $1 billion to a multi-year effort to retrain roughly 100,000 employees for “jobs of the future” inside the company[20]. Branded “Future Ready,” the program offers online courses and collaborations with universities to teach skills like data science, coding, and networking to AT&T’s workforce, aiming to fill roles in emerging technical areas. The goal was to transform nearly half of AT&T’s employees from obsolete roles (like traditional telephone line work) into roles needed for the digital era.
• Amazon (Upskilling 2025 Pledge): In 2019, Amazon announced a pledge to upskill 100,000 of its U.S. employees (about one-third of its workforce at the time) by 2025, investing $700 million in the effort[21]. This initiative includes programs like the Amazon Technical Academy (to train non-technical workers for software engineering roles), machine learning bootcamps, and a Career Choice program that pre-pays tuition for employees to earn certificates or degrees in high-demand fields (even outside of Amazon). Amazon’s motivation is to ensure its warehouse associates, retail staff, and other entry-level workers have a pathway into better-paying, more technical jobs – either within the company (e.g. transitioning from an order packer to an IT support technician or data analyst) or in the broader economy.

Redacted Hosting’s Mission: Veteran- and Career-Changer Upskilling

Redacted Hosting’s upskilling is explicitly focused on veterans and career-changers seeking durable entry points into technology and adjacent fields. Our model pairs secure, production-grade hosting with a structured learning ecosystem—so learners do not just study technology; they operate it under mentorship. Concretely, participants receive:

• Hosted, hands-on environments to deploy real applications (web, data, and security labs), converting coursework into operating services with uptime, observability, and security baselines.
• Access to a select cadre of practitioners (cloud, cybersecurity, devops, and e-commerce) for critique, code reviews, and architecture guidance—accelerating the transition from theory to tradecraft.
• A networked pathway—peer cohorts, practitioner roundtables, and portfolio reviews—that keeps graduates competitive in an ever-changing environment where skills and tooling evolve rapidly.

This approach complements firm-level upskilling programs discussed above by addressing two persistent gaps: (1) initial opportunity for those without a four-year CS pedigree, and (2) operational fluency—the capacity to run, harden, and iterate real systems. Veterans, in particular, bring strengths in discipline, mission focus, and risk management; when combined with live hosting, CICD, and security instrumentation, these strengths translate into measurable readiness for roles in cloud operations, platform engineering, and security operations. For career-changers, operating a portfolio of deployed, defended, and iterated services provides credible evidence of capability to employers—bridging the experience gap that often blocks entry.

In short, Redacted Hosting’s mission is not merely to teach technology but to socialize learners into the practices of modern infrastructure and security—with mentorship, real systems, and a resilient professional network. This is the practical substrate that makes upskilling stick and ensures participants remain competitive as AI, LLMs, and automation continue to reshape the work.

These examples show a proactive approach: instead of waiting for layoffs to happen, the companies are anticipating the skills that will be needed and helping their employees obtain those skills. Other firms, like Walmart, IBM, JPMorgan Chase, and numerous others, have launched their own upskilling and career development programs in recent years, often in partnership with educational institutions. A survey by the World Economic Forum found that 85% of employers plan to significantly increase their investment in upskilling and internal training by 2025, recognizing that continuous learning is now a business imperative[22][23].

Upskilling and reskilling offer multiple benefits. For workers, the obvious benefit is improved employability – they can move from a shrinking occupation (like cashier or assembly line worker) into a growing one (like robot maintenance technician, data entry analyst, or customer experience specialist) without undergoing the hardship of long-term unemployment. For businesses, upskilling can help address talent shortages and improve employee morale and loyalty. It is often more cost-effective to retrain a proven, experienced employee in new skills than to lay off everyone and hire brand-new specialists (especially since there is competition for tech-savvy talent). As one expert put it, “when you have workers that already possess much of what you need, it makes more sense to retrain them than to go out and hire new workers”[24]. Investing in employees also boosts public image and fulfills a company’s social responsibility, which can be important for brand value.

Of course, upskilling is not a simple cure-all. Training programs need to be well-designed and aligned with real job opportunities; otherwise, they risk becoming empty promises. Not all workers will succeed in acquiring advanced skills, and there is the question of who bears the cost – companies are stepping up, but government support (through community college funding, tax incentives, etc.) can help expand these efforts to smaller businesses and to workers between jobs. Additionally, upskilling needs to be continuous. The half-life of technical skills is shrinking, meaning workers might need to refresh their knowledge every few years. The McKinsey study noted that many executives feel unprepared to address skill gaps, and public policy support for training has been declining in many countries[25][26]. This indicates that a broader, systemic approach may be required, combining corporate programs with public workforce development initiatives.

Nonetheless, the momentum behind upskilling is growing. Industry groups and nonprofits are forming coalitions (such as the Aspen Institute’s UpSkill America initiative) to share best practices and encourage more employers to join the movement[27][28]. In some cases, upskilling programs even extend beyond a company’s own workforce to the general public – for example, Microsoft and Google have offered free AI and IT training courses online to help upskill the broader labor force. The consensus among experts is that preparing workers for the new types of jobs created by AI and automation is far more constructive than simply reacting to layoffs after the fact. Upskilling can cushion the transition to an automated economy by ensuring that workers aren’t left behind but instead move up the value chain.

Conclusion

Automation and AI are penetrating the fast food and retail industries in ways that could fundamentally change the nature of low-skill work. The negative impacts of this shift – from potential mass job displacement to heightened economic inequality and worker anxiety – are real and significant. Millions of entry-level workers such as cashiers, cooks, and sales staff face an uncertain future as algorithms and robots encroach on tasks traditionally done by humans. The evidence shows that these technologies could automate a majority of routine service roles, putting vulnerable populations (youth, less-educated workers, and others with limited options) at risk of unemployment or stagnant wages. At the same time, a nuanced look reveals that automation does not have to be an all-or-nothing, zero-sum game. The outcome will depend largely on how businesses and society choose to integrate AI into the workplace.

This article discussed two key mitigation strategies – human-in-the-loop system design and proactive upskilling of workers – and found that together they form a compelling approach to address automation’s downsides. By keeping humans involved in AI-powered processes, companies can maintain jobs, harness uniquely human skills, and deliver better quality service than machines alone could achieve. By training and upskilling their employees, companies (often in partnership with educational institutions and government) can ensure that those whose old jobs do get fully automated can move into new, higher-skilled positions instead of being left behind. These strategies are already being validated in the real world. Some restaurants using robots have deliberately avoided layoffs and even improved productivity by pairing humans with machines[11][17]. And many large employers are pouring resources into workforce development programs to meet future skill needs[18][21].

Of course, no single solution is foolproof. Human-in-the-loop approaches require a business culture that values workers as long-term assets rather than just costs to minimize. Upskilling programs need commitment, scale, and smart planning to truly be effective. There may still be sectors or companies that choose wholesale automation without mitigation, leading to difficult adjustments for workers and communities. Nonetheless, the overall evidence and real-world trends suggest that the most dire outcomes can be substantially alleviated by thoughtful, human-centric strategies. In fact, by combining AI efficiency with human creativity and empathy, businesses might achieve the best of both worlds – higher productivity and a resilient, engaged workforce. The transition to an AI-rich economy will not be easy, but with human-in-the-loop designs and upskilling initiatives, it can be navigated in a way that limits harm to workers and spreads the benefits of technology more equitably. The onus is now on employers, policymakers, and communities to implement these solutions at scale, so that automation becomes a tool for augmenting human labor rather than rendering it obsolete. - RH

[1]Meet the Future - OECD Report

https://www.kmc.ac.uk/college/wp-content/uploads/sites/2/2022/07/Meet-The-Future-OECD-Report-2022.pdf

[2]80% of restaurant jobs could be taken over by robots

https://www.adeccogroup.com/future-of-work/latest-insights/80-of-restaurant-jobs-could-be-taken-over-by-robots

[3]75+ Fast Food Statistics & Industry Trends Every Hospitality Professional Should Know

https://oysterlink.com/spotlight/fast-food-statistics-us/

[4]Economic Backbone of Holiday Shopping Season: Retail Workers

https://www.census.gov/library/stories/2023/12/holiday-retail-workers.html

[5]Growth trends for selected occupations considered at risk from automation : Monthly Labor Review : U.S. Bureau of Labor Statistics

https://www.bls.gov/opub/mlr/2022/article/growth-trends-for-selected-occupations-considered-at-risk-from-automation.htm

[6][22][23]WEF: How AI Will Reshape 86% of Businesses by 2030 | Technology Magazine

https://technologymagazine.com/articles/wef-report-the-impact-of-ai-driving-170m-new-jobs-by-2030

[7][18][19][25][26]Retraining and reskilling workers in the age of automation | McKinsey

https://www.mckinsey.com/featured-insights/future-of-work/retraining-and-reskilling-workers-in-the-age-of-automation

[8]Fast Food’s Automation Problem - Progressive.org

https://progressive.org/latest/fast-foods-automation-problem-park-20240815/

[9][10]AI Won’t Take Your Job if You Know About IA | Harvard Graduate School of Education

https://www.gse.harvard.edu/ideas/news/24/02/ai-wont-take-your-job-if-you-know-about-ia

[11][12][16]Data, pilot projects showing food service robots may not threaten jobs • Missouri Independent

https://missouriindependent.com/2024/10/02/data-pilot-projects-showing-food-service-robots-may-not-threaten-jobs/

[13][14][15]Robots replace human workers at new automated fast-food restaurant | Entrepreneur

https://www.entrepreneur.com/growth-strategies/robots-replace-human-workers-at-new-automated-fast-food/491356

[17]Inside the restaurant: How a fry cook robot holds the line for White Castle | HR Dive

https://www.hrdive.com/news/miso-robotics-flippy-2-holds-the-line-for-white-castle/625701/

[20][24][28]Upskilling in the News: AT&T Invests $1 Billion in Employee Reskilling

https://www.aspeninstitute.org/of-interest/upskilling-news-att-invests-1-billion-employee-reskilling/

[21][27]Amazon Pledges $700 Million to Upskill 100,000 Workers - UpSkill America

https://www.aspeninstitute.org/blog-posts/amazon-pledges-700-million-to-upskill-100000-workers/