Is This the End of Mass Production in Everything From Education To Manufacturing?

It’s not that mass production is a good or bad thing, but rather it’s a question of sustainability. Can it survive in an age when everything that was once strictly business is now highly personal?  “The assertion that AI will bring the end of mass production, from education to manufacturing, is both provocative and prescient. The ability of AI to personalize experiences at scale has the potential to disrupt the very foundations of how we produce and consume goods and services,” says Adnan Masood, UST's chief AI architect and AI scholar. 

It’s difficult to imagine a world where mass production might be losing in the race for more profitability and better sustainability. Especially when you consider how far we’ve come in improving the execution of mass production to perfect form and reduce waste. From Six Sigma and just-in-time manufacturing in factories, to microlearning and gamification in schools, every effort and expense has been made to increase efficiencies and performance.  

Even so, one huge obstacle is now wrecking the mass production model: “People are tired of brands treating everyone the same,” says Chad Reynolds, the CEO and founder of Vurvey, a company that enables “co-creation” between buyers and producers to create new or highly customized products.  

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Extinction or Evolution?  

Although there have been numerous advances in mass production, there’s been little change in how industries reach their goals. In other words, the more things changed, the more they stayed the same. 

“Despite immense shifts in consumer habits and supply chains, manufacturing and warehouse industries have remained largely unchanged for the last 50 years,” says Ahmad Baitalmal, CTO and co-founder of Mytra, a producer of industrial bots, software, and storage cells.  

Mass production across industries is ripe for disruption and therefore inevitable across the board. 

“Generative AI will end mass production in many industries. For example, when it comes to gaming, generative AI will make it possible for each person to play a different game in the same game world,” says Kaveh Vahdat, who leads RiseAngle, a generative AI game creation company, and RiseOpp, a Fractional CMO and SEO services company. 

But that’s not to say that every industry is willing to throw out the old ways -- at least not yet. 

"AI, working in tandem with automation, IoT, and edge computing, will have the opposite effect on manufacturing in the near term,” says Farès Sakka, director of smart industries, Americas at Orange Business. “AI will be a force multiplier through Industry 4.0, boosting the scale of mass production with better control over costs, risks, downtime, or product shortages.”  

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The only question left is whether disruption will eventually render mass production extinct or force it to evolve. After all, there is much benefit in capturing economies of scale. Is it possible to keep the one and toss the other? 

“As manufacturers continue to embrace and operationalize AI, they will inevitably set the underlying foundations of Industry 5.0, handling massive, diverse workloads with speed, resiliency and sustainability beyond what the operator in the factory could pull off. And that is the beginning of a major change, a form of hyper-personalized, tailored and compliant production,” Sakka adds. 

Enter Mass Personalization 

Hyper-personalization means using AI, advanced analytics, and a smattering of other technologies to instantly offer content on products, services, and relevant information of interest to everyone. Doing so at economies of scale is called mass personalization. 

“AI isn’t ending mass production; it's redefining it through hyper-personalization at scale,” says Scarlett Sieber, chief strategy officer at Money20/20, a global producer of fintech events and conferences. “Digitization enabled standardized financial products like loans and credit cards to be delivered at scale. Now, AI is set to drive the next phase of financial services -- delivering uniquely customized products to millions simultaneously. This shift from a one-size-fits-all model to mass customization marks a new era for the industry.”  

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The gobsmacking aspect of this shift is that it looks to be ubiquitous.  

“AI is indeed transforming mass production across industries, and education is at the forefront of this revolution. However, this ed-tech shift doesn't necessarily mean the end of all forms of mass production in education. Rather, AI is enabling us to mass-produce personalization itself. We can create tools and platforms that can provide unique experiences at scale,” says Lynn Rogoff, adjunct associate professor in digital art & design and English at the New York Institute of Technology, who says their emerging technology grant-funded project investigates how AI, particularly chatbots, can personalize and enhance the learning experience.   

“For instance, our AI chatbot can engage students in conversations about historical figures like Sacajawea, Lewis, and Clark, adjusting its language, depth, and focus based on the individual student's responses and learning style. This is based on our recently released film “Bird Woman, Sacajawea” on familytime.tv. We're even exploring multilingual capabilities, developing Spanish language interactions to cater to a diverse student population,” says Rogoff, who has won two Emmy Awards and formerly worked as writer, producer, and director on “Sesame Street”, “Big Blue Marble”, and “Watch Your Mouth in the US”, and “Rechov Sumsum” (Israeli Sesame Street). 

For the most part, organizations across industries are embracing this massive shift. 

“In manufacturing, the shift is equally seismic -- the traditional assembly line, optimized for mass production of identical goods, is giving way to flexible, AI-driven systems capable of producing customized products on demand. Manufacturing would shift to personalized goods using AI-powered robotics and 3D printing. This changes industries from fashion to automotive as we know it -- and crates new levels of personalization previously unimaginable,” says Masood. 

Even software development is seeing a shift to mass personalization. 

“AI unlocks new business models by enabling companies to offer highly specialized and personalized products. For us, this means more opportunities to deliver tailored software solutions to niche markets, helping our clients stay competitive and resilient,” says Venu Moola, CEO of Fleet Studio, a web and mobile app developer company. 

Why this shift is taking place is well-established. How mass production evolves to fit this shift for different industries is still taking shape.  

“Looking ahead, we expect to blend mass production's efficiency with personalization's effectiveness. Our work is pioneering AI platforms that can offer tailored learning experiences to millions of students at once, adapting to each individual's pace, interests, and learning style,” Rogoff says. 

“The challenge and opportunity lie in how we navigate this transition, ensuring that we leverage AI to enhance human learning and interaction rather than replace it. As our grant project demonstrates, the goal should be to use AI to augment and personalize the learning experience while maintaining education's critical social and collaborative aspects,” Rogoff adds.  

While the possibilities appear endless and exciting, the shift isn’t without cost. 

“The transition away from mass production is not without its challenges. The economic implications are complex. AI does drive significant productivity gains and economic growth -- but it also raises concerns about job displacement and the need for workforce reskilling,” Masood says. 

“The societal implications are also equally profound. The ability to personalize everything raises questions about privacy, data ownership, and the potential for AI to reinforce existing biases and inequalities,” Masood adds.