Category: 3. Business

• New Lenovo ThinkSystem and ThinkAgile storage and virtualization infrastructure solutions provide optimal performance, security and efficiency for the most demanding AI and enterprise workloads  

• New Lenovo ThinkSystem DS Series Storage Arrays provide simple deployment and management for virtualized environments running mission-critical enterprise workloads 

• New Lenovo ThinkAgile FX Series provides maximum flexibility and investment protection with a multi-vendor hyperconverged infrastructure (HCI) appliance.  

• Tailored Lenovo Hybrid Cloud Advisory and Deployment services leverage structured and unstructured data to achieve business outcomes with AI 

December 10, 2025 – Lenovo today announced an expansive series of new data storage, virtualization solutions and data management services, designed to help customers modernize their IT and data infrastructure for powering enterprise applications and AI ready capabilities. Today’s new offerings include new Lenovo ThinkSystem and ThinkAgile data storage and virtualization solutions, announced in tandem with data management services. Designed to provide a modern foundation for enterprises and mid-size businesses achieving AI innovations, this announcement combines complementary hardware, software and services offerings to help deploy, manage, and unleash the true potential of enterprise data. 

“Sixty-three percent of organizations either do not have or are unsure if they have the right data management practices for AI, according to a survey by Gartner ®.” 1  Customer unique data is the differentiation that will drive their competitive advantage and most accurate results, however 80% of storage deployed in the last 5 years is on slower hard drive-based storage (according to IDC reporting) that is not optimized for AI. At the same time, customers are challenged with new virtualization and containerization requirements that demand open solutions. Businesses must mitigate this risk by ensuring their enterprise data systems and practices are modernized for advanced use cases. 

 “With disruptions in enterprise virtualization strategies and the mandate to make their data ready for the most demanding workloads, organizations are looking to modernize their legacy infrastructure with open solutions,” said Stuart McRae, Executive Director and General Manager of Data Storage at Lenovo. “These new offerings provide the security, flexibility, and performance to optimize enterprise applications and power enterprises to extract maximum value from data.” 

Flexibility and Choice for Virtualization and Data Needs 

Businesses today need the efficiency and cyber resiliency of their systems to run parallel to performance, simplicity, and scalability with an option to deploy on-prem and hybrid so that the data can stay in place for compliance while AI workloads run where appropriate. Lenovo has introduced new Lenovo ThinkSystem and Lenovo ThinkAgile Enterprise offerings optimized or AI, virtualization and storage bottlenecks, including: 

• Lenovo ThinkSystem DS Series Storage Arrays: All-flash and protected Storage Area Network (SAN) block storage systems that are simple to deploy and manage for virtualized environments, improving performance and efficiency for virtualization and data modernization. 

• Lenovo ThinkAgile FX Series: Hyperconverged Infrastructure (HCI) that delivers an open architecture that supports seamless conversion between select HCI solutions without replacing hardware, delivering maximum investment protection and flexibility.   

• Lenovo ThinkAgile MX Series for disaggregated storage for Microsoft Azure Local: As a hyperconverged infrastructure (HCI) integrated appliance provider with Microsoft, we are expanding support for disaggregated external Fibre Channel Storage Area Networks (SAN to deliver greater enterprise storage support for virtualization customers. 

• Lenovo ThinkAgile MX Series with NVIDIA RTX Pro 6000:   Integrated next generation GPU support to power advanced AI performance capabilities for enterprise inferencing with Microsoft Azure Local. 

• Lenovo ThinkAgile HX Series for AI Lenovo’s HCI offering features Nutanix Enterprise AI (NAI) software stack to enable customers running in virtualized and distributed containerized environments to deploy, run, and scale AI models in minutes. 

Complete Lifecycle Services Optimized for Advanced Workloads including AI  

To help customers fully realize the benefits of their new systems and prepare their data for AI, Lenovo is extending this momentum with a broad portfolio of hybrid cloud and data lifecycle services designed to modernize environments, strengthen reliability, and support evolving storage and AI workload requirements. This portfolio includes Lenovo Deployment Services for ThinkAgile and ThinkSystem that help organizations accelerate time to value through more efficient infrastructure rollout, alongside a range of storage services that can be consumed individually or through Lenovo’s flexible TruScale model to enhance performance, agility, and innovation across the data storage lifecycle. 

To guide long-term strategy, Lenovo’s Hybrid Cloud Advisory Services help customers align on-prem or hybrid environments with compliance, data protection, and operational efficiency. Lenovo’s Migration Services help organizations optimize data and workloads by combining cloud flexibility with the dependability of existing infrastructure. 

As part of Lenovo’s expanded Data Management Services portfolio, Lenovo Premier Enhanced Storage Support delivers a specialized, storage-focused experience for IT teams managing critical workloads. With direct access to Lenovo experts, customers benefit from proactive monitoring, performance optimization, and guided issue resolution—helping ensure systems run reliably, are better protected, and maintain the resilience needed to support AI innovation and hybrid cloud growth. 

Explore how Lenovo is powering the future of Enterprise AI and Storage at https://www.lenovo.com/datastoragesolutions. 

 

About Lenovo 

Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). To find out more visit https://www.lenovo.com, and read about the latest news via our StoryHub. 

 

LENOVO, THINKSYSTEM, THINKAGILE AND TRUSCALE are trademarks of Lenovo. NVIDIA and RTX are trademarks of NVIDIA Corporation, Inc. All other trademarks are the property of their respective owners. ©2025 Lenovo Group Limited. All rights reserved. 

The question “what present do you recommend for …” will be tapped into phones and computers countless times over this festive period, as more people turn to AI platforms to help choose gifts for loved ones.

With a quarter of Britons using AI to find products, brands are increasingly adapting their strategies to ensure their products are the ones recommended, especially those trying to reach younger audiences.

But can AI offer thoughtful, personal suggestions for friends and family? The Guardian put the idea to the test.

First we tried asking for possible gifts for a middle-aged man who enjoys running and photography. The market-leading chatbot ChatGPT suggested: a Canon lens for £129 from Argos; a Koospur tennis racket sensor tracker for £71.72 on Amazon; and a Boondocker recycled camera bag for £34.98. The AI platform insisted the “ideal present” would be the camera bag, plus maybe the tennis sensor tracker. It also threw in experience ideas such as tennis coaching, whisky tasting or live music.

When asked to work with a more restricted budget it suggested tennis racket-emblazoned socks for £18, which were ugly and definitely not worth the high price tag.

The answers skewed heavily towards big online retailers, with seven of the nine initial suggestions from Amazon. Asking for ideas from more niche companies led to a minimalist tennis court print for £30 from a website called the Smart Party Shop and vague advice to buy from “Etsy or Not On the High Street-type sellers”.

Searching for a woman who likes beauty products, DIY and fitness again produced some middle-of-the-road suggestions. However, with a nudge for more cult picks it steered towards a £17.50 Odylique rose moisturiser gift set, which it described as “luxurious but not mainstream”. It also put forward a £30 Floris sandalwood and patchouli-scented candle, which it claimed was “more personal than just another lipstick”.

When asked to recommend DIY tools, it suggested a small, pink kit with some rather useless-looking pliers, rather than the usual all-purpose devices such as drills, sanders and staple guns – a sign that the longstanding complaint that AI reinforces gender stereotypes remains.

The Guardian then instructed the AI to try shopping locally, using the example of homeware ideas in south London. ChatGPT said to try ALKEMI, an independent lifestyle store in Nunhead. When the area was narrowed down to Herne Hill it suggested two shops: Jo’s House and Forget Me Not And Green.

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Trying other AI models did not appear to vary the quality of responses much. Searching on Google’s Gemini for gifts for a man who likes chess, video games, reading and music, specifically techno and house threw up these top suggestions: a book on chess strategy for £22; a £50 Bandcamp gift card; or a hot sauce tasting kit for about £30-£40.

So what were the main takeaways from the exercise? AI seems to favour bigger brands (especially Amazon) unless you tell it not to. It can find you a gift, just not necessarily one that says anything more than “an algorithm picked this”. Perhaps you’ll have a bit more luck if you are willing to spend the time to steer it towards more relevant answers, but then it sort of defeats the point.

Generative artificial intelligence has become widely accepted as a tool that increases productivity. Yet the technology is far from mature. Large language models advance rapidly from one generation to the next, and experts can only speculate how AI will affect the workforce and peoples’ daily lives.

As a materials scientist, I am interested in how materials and the technologies that derive from them affect society. AI is one example of a technology driving global change – particularly through its demand for materials and rare minerals.

But before AI evolved to its current level, two other technologies exemplified the process created by the demand for specialized materials: cars and smartphones.

Often, the mass adoption of a new invention changes human behavior, which leads to new technologies and infrastructures reliant upon the invention. In turn, these new technologies and infrastructures require new or improved materials – and these often contain critical minerals: those minerals that are both essential to the technology and strain the supply chain.

The unequal distribution of these minerals gives leverage to the nations that produce them. The resulting power shifts strain geopolitical relations and drive the search for new mineral sources. New technology nurtures the mining industry.

The car and the development of suburbs

At the beginning of the 20th century, only 5 out of 1,000 people owned a car, with annual production around a few thousand. Workers commuted on foot or by tram. Within a two-mile radius, many people had all they needed: from groceries to hardware, from school to church, and from shoemakers to doctors.

Then in 1913, Henry Ford transformed the industry by inventing the assembly line. Now, a middle class family could afford a car: Mass production cut the price of the Model T from US$850 in 1908 to $360 in 1916. While the Great Depression dampened the broad adoption of the car, sales began to increase again after the end of World War II.

With cars came more mobility, and many people moved farther away from work. In the 1940s and 1950s, a powerful highway lobby that included oil, automobile and construction interests promoted federal highway and transportation policies, which increased automobile dependence. These policies helped change the landscape: Houses were spaced farther apart, and located farther away from the urban centers where many people worked. By the 1960s, two-thirds of American workers commuted by car, and the average commute had increased to 10 miles.

Public policy and investment favored suburbs, which meant less investment in city centers. The resulting decay made living in downtown areas of many cities undesirable and triggered urban renewal projects.

Long commutes added to pollution and expenses, which created a demand for lighter, more fuel-efficient cars. But building these required better materials.

In 1970, the entire frame and body of a car was made from one steel type, but by 2017, 10 different, highly specialized steels constituted a vehicle’s light-weight form. Each steel contains different chemical elements, such as molybdenum and vanadium, which are mined only in a few countries.

While the car supply chain was mostly domestic until the 1970s, the car industry today relies heavily on imports. This dependence has created tension with international trade partners, as reflected by higher tariffs on steel.

The cell phone and American life

The cell phone presents another example of a technology creating a demand for minerals and affecting foreign policy. In 1983, Motorola released the DynaTAC, the first commercial cellular phone. It was heavy, expensive and its battery lasted for only half an hour, so few people had one. Then in 1996, Motorola introduced the flip phone, which was cheaper, lighter and more convenient to use. The flip phone initiated the mass-adoption of cell phones. However, it was still just a phone: Unlike today’s smartphones, all it did was send and receive calls and texts.

In 2007, Apple redefined communication with the iPhone, inventing the touch screen and integrating an internet navigator. The phone became a digital hub for navigating, finding information and building an online social identity. Before smartphones, mobile phones supplemented daily life. Now, they structure it.

In 2000, fewer than half of American adults owned a cellphone, and nearly all who did it only sporadically. In 2024, 98% of Americans over the age of 18 reported owning a cellphone, and over 90% owned a smartphone.

Without the smartphone, most people cannot fulfill their daily tasks. Many individuals now experience nomophobia: They feel anxious without a cellphone.

Around three quarters of all stable elements are represented in the components of each smartphone. These elements are necessary for highly specialized materials that enable touch screens, displays, batteries, speakers, microphones and cameras. Many of these elements are essential for at least one function and have an unreliable supply chain, which makes them critical.

Critical materials and AI

Critical materials give leverage to countries that have a monopoly in mining and processing them. For example, China has gained increased power through its monopoly on rare earth elements. In April 2025, in response to U.S. tariffs, China stopped exporting rare earth magnets, which are used in cellphones. The geopolitical tensions that resulted demonstrate the power embodied in the control over critical minerals.

The mass adoption of AI technology will likely change human behavior and bring forth new technologies, industries and infrastructure on which the U.S. economy will depend. All of these technologies will require more optimized and specialized materials and create new material dependencies.

By exacerbating material dependencies, AI could affect geopolitical relations and reorganize global power.

America has rich deposits of many important minerals, but extraction of these minerals comes with challenges. Factors including slow and costly permitting, public opposition, environmental concerns, high investment costs and an inadequate workforce all can prevent mining companies from accessing these resources. The mass adoption of AI is already adding pressure to overcome these factors and increase responsible domestic mining.

While the path from innovation to material dependence spanned a century for cars and a couple of decades for cell phones, the rapid advancement of large language models suggests that the scale will be measured in years for AI. The heat is already on.

Christmas shopping – some love it, to others it’s a chore and this year for the first time many of us will outsource the annual task of coming up with gift ideas to artificial intelligence.

While traditional internet search, social media – especially TikTok and Instagram – and simply wandering a local high street will still be the main routes to presents for most this year, about a quarter of people in the UK are already using AI to find the right products, according to PricewaterhouseCoopers.

For brands appealing to younger people, the revolution is well under way: the rival advisory firm KPMG says as many as 30% of shoppers aged 25-34 are using AI to find products, compared with 1% of those aged over 65.

Asking a large language model (LLM) such as ChatGPT or Gemini what you should get your father-in-law – rather than typing “whisky” or “socks” into Google or DuckDuckGo – may seem a small change in habits. However, it marks a sea change for retailers accustomed to paying search engines to promote their listings.

LLMs allow users to ask questions in conversational language, perhaps by speaking into their computer or phone. Instead of just providing a list of links, they offer specific suggestions with the potential for big sales for items that are regularly recommended.

The chatbots produce their responses by scraping the internet and inbuilt datasets for relevant information, with some sources given more trusted status than others.

Companies large and small are scrambling to adapt to this new world where the keywords and advertising deals previously central to web marketing hold less importance than the reviewers’ opinions, accurate availability information and product details read by LLMs such as OpenAI’s ChatGPT, Google’s Gemini and Meta’s Llama.

The shake-up may create an opening for independent businesses to cut through online, but some big brands are concerned they will be lost in a wild west where it is unclear how to reach the consumer. Marketers must now appeal not only to shoppers directly but also to their AI bots.

“Retailers can’t buy their way into the search – they have to earn it,” says Emma Ford, the director of digital transformation for PwC UK. “The experience, expertise, authenticity and trustworthiness [of a brand online] help. Sentiment across the internet is really important.”

Several large UK retailers have told the Guardian they already have teams on the case looking at a wide variety of tactics, from making sure they appear in Reddit forums – a key source for some platforms – to responding to reviews on Google or Trustpilot, and ensuring AI models can access the correct product data.

While some say they are being cautious with resources, amid signs certain individual LLMs could disappear as rapidly as they have sprung up, the belief is that this new way of interacting online is here to stay.

Nickyl Raithatha, the chief executive of the online card and gift seller Moonpig, says AI search’s relevance for companies this year is relatively low but his company is well-prepared for rapid change.

He says Moonpig is ensuring its products are picked up in AI search by using generative engine optimisation (GEO) techniques such as “online content with people discussing the best way to make someone happy on Mothers Day” in its own content or on discussions boards and in YouTube videos. He adds: “There is a growing science around this and we are all learning.”

Ford says businesses are still feeling their way into the nuances of how the technology will find and respond to their online presence. Online reviews, for example, are clearly a factor in AI decision-making, but it is not clear how much importance is placed on particular platforms or how they rank against other factors such as reliable availability data, longevity of a brand or secure payment options.

It may be that suppliers that have been around longer and have a broader profile are foregrounded, but their long history of ups and downs could also play against them.

“I do think AI will change retail for the next 20 years,” says Peter Ruis, the managing director of John Lewis. He contends that established brands such as his will benefit from having a strong reputation with the technology in place to sell online, while shoppers could discover they stock items previously assumed to have been available only at a specialist.

In future, industry watchers believe, ChatGPT, Amazon and Google are likely to try to monetise their AI platforms with some form of paid search or featured ads.

More sophisticated “AI agent” models are also being developed – bots that can autonomously perform complex multistage tasks such as seeking out the best deals, placing orders and organising delivery.

For example, it could be possible for these digital secretaries to negotiate offers tailored to particular customers, such as bundling together a number of furniture purchases from various outlets during a move, which have been customised to fit budget, style and delivery preferences, according to the advisory firm McKinsey.

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That could lead retailers into allowing their systems to flex product prices to attract particular searchers.

Organising the return of an unwanted item could also be taken on by AI agents, with one acting on behalf of the shoppers and the other for the retailer.

However, such technology is fraught with potential pitfalls. Retailers will need systems that can cope with a potential flurry of queries and to have clear rules on who might be responsible for glitches such as unwanted purchases made by a bot.

In the US, the online marketplace Etsy was the first to team up with ChatGPT to make it possible to pay for goods via the LLM’s instant checkout service. The e-commerce platform Shopify and the retailers Walmart and Target swiftly followed. While the deals do not appear to prioritise their products in searches, the inclusion of a “buy” button for their goods could put them ahead of the pack.

Anna Bancroft, a partner in PwC’s digital transformation team, points out that under current UK rules it is not possible for an AI bot to make a purchase on behalf of a human, and regulation would need to change for such systems to run without human oversight. She says retailers and shoppers are cautious about giving the robots access to customer data and handling payment.

There are also concerns about agents being susceptible to manipulation, as Microsoft has found in research simulations. Meanwhile, tech retail players are becoming territorial about who gets to crawl whose data.

Last month, Amazon sued the AI company Perplexity over its shopping feature that automates placing orders for users. Amazon accused the startup of covertly accessing customer accounts and disguising AI activity as human browsing. Perplexity hit back, defending users’ right to delegate their shopping to AI agents and calling the suit “a bully tactic to suppress competition”.

In this rapidly shifting landscape, Ford suggests independent retailers may have a chance to shine. “Independents have potential to go faster,” she says, with the ability to respond nimbly without having to sign off large budgets.

Michelle Ovens, the founder of Small Business Britain, which advises independent retailers on how to survive on the changing high street, agrees. “[Independent businesses] don’t necessarily need to spend a lot of money. You don’t necessarily need a big team,” she says.

Ovens advises local shopkeepers to ask AI platforms themselves how best to make sure they can appear. “Be clear about who you are,” she says, with a description making clear that you are an independent specialist, up-to-date pictures and “encourage customers who have got experience of the brand to give a good review”.

However, all of this should not stand ahead of making a website engaging and easy to shop on, Ovens adds. “There will not be a dramatic shift this Christmas. We’ll see change over time and operators will rise to the challenge.”

WASHINGTON, Dec. 10, 2025 (GLOBE NEWSWIRE) — FTI Consulting, Inc. (NYSE: FCN) today announced the appointment of Mitch Harris as a Senior Managing Director in the Healthcare Risk Management & Advisory practice within the firm’s Forensic and Litigation Consulting segment.

Mr. Harris, who is based in Los Angeles, has more than three decades of experience driving healthcare strategy for major health plans, health systems and pharmacy benefit managers across the United States. His expertise includes leveraging data and AI to improve performance and support clients with operational and regulatory challenges.

In his role at FTI Consulting, he will support clients with regulatory strategy and government programs compliance, as well as operational optimization and turnaround initiatives.

“The healthcare industry is experiencing rising costs, increased regulatory complexity and intensified oversight, creating operational and financial volatility and continuing to increase our clients’ need for expert support and advice,” said Wayne Gibson, Leader of the Healthcare Risk Management & Advisory practice at FTI Consulting. “Mitch brings diverse capabilities to our deep bench of experts, working with clients to address regulatory, operational and financial risk and support innovative digital transformation, ultimately unlocking value.”

Earlier in his career, Mr. Harris held roles at PwC’s Health Industries Advisory practice, where he led business development and operational strategy for the national health plan compliance and regulatory practice. He has also served in management roles at Caremore Medical Management Company (now Carelon) and Blue Shield of California.

Commenting on his appointment, Mr. Harris said, “FTI Consulting is a global, expert-driven firm with a reputation for supporting high-stakes, high-profile projects. Our experts can predict and remediate risk and proactively mitigate issues while implementing process improvement to optimize costs. I look forward to joining my colleagues as we work to solve our clients’ biggest challenges.”

About FTI Consulting 
FTI Consulting, Inc. is a leading global expert firm for organizations facing crisis and transformation, with more than 8,100 employees located in 32 countries and territories as of September 30, 2025. In certain jurisdictions, FTI Consulting’s services are provided through distinct legal entities that are separately capitalized and independently managed. The Company generated $3.70 billion in revenues during fiscal year 2024. More information can be found at www.fticonsulting.com. 

FTI Consulting, Inc.  
555 12^th Street NW  
Washington, DC 20004  
+1.202.312.9100 

Investor Contact:  
Mollie Hawkes 
+1.617.747.1791 
mollie.hawkes@fticonsulting.com 

Media Contact:  
Sam Ford 
+1.617.480.7402 
samantha.ford@fticonsulting.com

Source: FTI Consulting, Inc.

Tui, Europe’s biggest travel operator, has said it is investing heavily in AI as more people turn to ChatGPT to help book their holidays, including using the technology to create “inspirational” videos and content.

The chief executive, Sebastian Ebel, said the company was investing in generative engine optimisation (GEO), the latest incarnation of search engine optimisation (SEO), to help push Tui to the top of results from AI chatbots including ChatGPT and Gemini.

While traditional SEO relied on links and keywords to increase visibility in search engine results, GEO tries to increase recommendations via chatbots by ensuring a product is mentioned in the message boards, videos and other online datasets that the AI agents crunch to produce their answers.

Ebel said connecting to large language models and social media companies would help Tui to grow. “By being part of their ecosystem, not depending on Google alone any more, [we are] going into the space where our customer is,” he said. “We are building a partnership where we can optimise search, where we can broaden distribution and proximity to ChatGPT and TikTok.”

It comes as people increasingly use AI agents – autonomous digital secretaries – to help with their online shopping. This year OpenAI, Perplexity, Google and Microsoft all launched AI features that allow users to search for products through their chatbots, with agents that can complete orders on behalf of consumers.

Tui said it was using AI to help create “inspirational videos, content and translations to improve trip planning”, as well as AI-powered voice and chat agents for customer services.

It is the latest effort by the German travel operator to incorporate AI technology into its customer experience, after it started using ChatGPT in its app to provide holiday recommendations in 2023. Its first launch had some hiccups, with the Guardian finding at the time that the bot struggled with basic conversation.

Tui reported annual pre-tax profits up 20% to just over €1bn (£904m), close to a record high. Revenue rose 4% to €24.2bn but is expected to grow at a slower rate next year, between 2% and 4%, reflecting “prevailing macroeconomic and geopolitical uncertainties”, Tui said.

The company, which has been struggling in its core German market, also laid out plans to cut costs by €250m by 2028, though Ebel insisted “there is a big difference in having less jobs versus cutting jobs”.

He said: “Our workforce is changing and we are getting more efficient. We will not get less people in total. We want to grow and we want to be more efficient.”

The company, which is headquartered in Hanover, employs about 67,000 people around the world. Its shares fell by 2.8% in early trading on Tuesday and are down by about 34% over the past five years.

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Ebel said he was “very unsatisfied” with the share price, though the chief financial officer, Mathias Kiep, said a new dividend policy of €0.10 a share could help revive the stock.

The company signalled that some of the price pressure on travellers could ease, with Ebel saying the market was “over the high inflation times”.

Holiday bookings for next summer have been positive so far, Tui said, with popular destinations for 2026 including Greece, the Balearic Islands and Turkey.

McDonald’s has taken down a Christmas advert made with Artificial Intelligence (AI) following online backlash.

The 45-second advert was produced with generative AI clips and released publicly on McDonald’s Netherlands YouTube channel on 6 December.

Viewers on social media denounced the use of AI in the film, with one commenter calling it “the most god-awful ad I’ve seen this year”.

On 9 December McDonald’s Netherlands removed the video, adding in a statement to BBC News that the moment served as “an important learning” as the company explored “the effective use of AI”.

The advert was created for McDonald’s by Dutch company TBWANeboko and US production company The Sweetshop.

Adverts which include generative AI have become a growing trend among major brands, such as Coca-Cola, particularly for the Christmas season.

The McDonald’s advert depicted things that can go wrong during the Christmas break, using the slogan “the most terrible time of the year”, and suggesting the time was better spent in the company of the fast food giant.

Following its release, viewers criticised the film’s uncanny-looking characters and large number of stitched together clips, calling it “creepy” and “poorly edited”.

As clips made using generative AI are more likely to distort the longer they run for – most clips made using the process tend to be roughly six to 10 seconds long – even a 45-second advert would likely consist of many videos edited together.

The video also provoked concerns for job displacement in the industry, with one Instagram comment noting: “No actors, no camera team..welcome to the future of filmmaking. And it sucks.”

Following the video being made private on the McDonald’s Netherlands YouTube channel, The Sweetshop’s chief executive Melanie Bridge defended the advert.

As quoted in Futurism, she said the production process took “seven weeks” where the team “hardly slept” and created “thousands of takes – then shaped them in the edit just as we would on any high-craft production”.

“This wasn’t an AI trick,” she said. “It was a film.”

In a statement to BBC News, McDonald’s Netherlands said the video was meant to “reflect the stressful moments that can occur during the holidays” but had decided to remove the advert.

“This moment serves as an important learning as we explore the effective use of AI,” it said.

Where normally a high-publicity Christmas campaign could take up to a year to pull off, companies have begun to look to firms which can produce films in a much shorter time span, using prompts from generative AI tools to create new video content.

Coca-Cola seems to have been able to sway at least some of the general public with its second AI-generated Christmas ad in a row.

While the use of AI to create the advert has been divisive, a report from analytics company Social Sprout found it had a 61% “positive sentiment rating” from commenters online.

But several other businesses such as the Italian luxury fashion house Valentino have come under fire for using the technique in their campaigns, with critics calling Valentino’s advert “cheap” and “lazy”.

BBC News has contacted The Sweetshop and TBWANeboko for comment.