Every year, Euromonitor International identifies the top global consumer trends for the coming year. For 2025, one major trend is “AI Ambivalent,” which captures the complex emotions consumers feel about AI – is it a friend or a foe?
November 2022 marked the dawn of a new era with the release of ChatGPT, introducing generative AI (GenAI) to millions of people worldwide. Since then, individuals have experimented with it, creating AI-generated texts, poems, and even images. By 2024, Euromonitor predicted the increasing integration of GenAI into daily consumer lives and business operations, from automating routine tasks to enhancing customer experiences.
In this context, we ask: what are the potential upsides and downsides of AI in the logistics and supply chain industries? Where do industry experts see opportunities, and where do fears and concerns about new technology arise?
The Efficiency Promise
One of AI’s biggest promises is improved efficiency, a critical need during times of rising inflation, labour shortages, and supply chain challenges. Logistics and supply chain management, in particular, stand to benefit significantly from AI-driven technologies.
AI enables businesses to predict demand more accurately, reduce stock shortages, and streamline operations. For example, machine learning algorithms can analyse past sales trends to anticipate future consumer needs, preventing overstocking or understocking. Automation also minimizes manual interventions, reducing errors and freeing employees to focus on higher-value tasks.
42% of professional expect Gen AI to help optimise supply chains with automated order and vendor management in the coming years
Source: Euromonitor International Voice of the Industry Survey, fielded September 2024 (n=305).
However, this promise comes with its share of challenges. The same efficiencies that benefit businesses raise anxieties among workers who fear job displacement. AI has already demonstrated its potential to replace repetitive and manual tasks, but recent advancements in generative AI also threatens roles requiring creativity and problem-solving – positions once thought immune to automation.
This dichotomy leaves industries and workers grappling with a question: how do we harness the efficiency of AI without undermining the workforce’s stability and livelihood?
Tech Replacing Humans?
Underlying this anxiety is a broader, more primal fear: will technology replace humans altogether? Much of this concern stems from uncertainty. Historically, humans have always been sceptical of new technologies, from the printing press to the steam engine. AI is no exception.
For many, the rapid evolution of AI feels unfamiliar and daunting. According to Euromonitor International’s Digital Consumer Survey, 54% of global consumers still prefer talking to a human to address customer service questions. There is still a higher level of comfort interacting with a human instead of a bot. However, this is also a chance for GenAI which mimics human-like conversations and provides a higher level of confidence. In fact, 43% of consumers considered generative AI a trustworthy source of information in 2024. This underscores the need to use generative AI in a transparent and ethical manner, while offering human oversight in critical situation, as the human interaction remains crucial.
The challenge lies in balancing caution with openness to innovation. Too much fear slows progress, while unchecked adoption could lead to a loss of trust.
Will AI Solve the Climate Crisis?
Another area where AI shows promise is within the sustainability sector. By making processes more efficient, AI has the potential to reduce environmental impact. In the food industry, for instance, AI can help minimize food waste by optimizing supply chains. Predictive models can forecast demand with precision, ensuring the right quantities of food are produced and distributed, reducing overproduction and waste.
However, while AI may help industries become more sustainable, it is not without its downsides. Large AI computing centres require significant energy to process vast datasets, often relying on non-renewable energy sources like oil and gas. This creates a paradox: AI may make supply chains more efficient, but its environmental cost cannot be ignored.
Ethical concerns also arise. AI systems are only as unbiased as the data they are trained on, meaning existing human prejudices can be inadvertently encoded into decision-making processes. Furthermore, the collection of vast amounts of data – much of it sensitive – concentrates power in the hands of a few companies, raising questions about transparency and fairness.
AI’s role in addressing the climate crisis remains promising but fraught with challenges. For it to be a true ally in sustainability, industries must ensure the energy footprint of AI is minimized and its applications remain ethical and equitable.
Personalization at What Cost?
AI is often lauded for its ability to enhance personalization. In the logistics and food industries, this means tailored shopping experiences, such as health-conscious meal recommendations or curated grocery lists based on dietary needs. AI-powered platforms can analyse individual preferences and provide hyper-targeted suggestions, creating convenience and improving customer satisfaction.
However, this comes with trade-offs. Hyper-personalization often requires detailed data collection, raising concerns about privacy and how companies use consumer information. For example, some may worry about their health data being exploited for profit rather than used to improve well-being.
Personalization can inadvertently fuel overconsumption. By constantly suggesting products, AI risks encouraging excessive purchasing behaviour, counteracting sustainability goals. While AI creates opportunities for tailored experiences and products, businesses must navigate its implementation carefully to avoid losing the consumer’s trust.
Conclusion
As AI continues to reshape industries, it brings both incredible opportunities and significant challenges. In logistics and supply chains, the efficiency promise offers a transformative potential to optimize processes, reduce waste, and improve sustainability. Yet, it also raises concerns about job displacement, ethical practices, and the environmental cost of AI systems.
The path forward lies in striking a balance between innovation and humanity. Businesses must ensure that AI is used as a tool to empower rather than replace workers, address ethical concerns transparently, and prioritize sustainable practices. Similarly, scepticism of AI should not hinder its adoption but instead encourage its responsible and thoughtful integration.
AI is not inherently friend or foe. Its impact depends on how we choose to use it – and the choices we make today will shape the world consumers and businesses inhabit tomorrow.
