Human rights principles Archives | Page 132 of 157

AI bands rise as real musicians struggle to compete

AI is quickly transforming the music industry, with AI-generated bands now drawing millions of plays on platforms like Spotify.

While these acts may sound like traditional musicians, they are entirely digital creations. Streaming services rarely label AI music clearly, and the producers behind these tracks often remain anonymous and unreachable. Human artists, meanwhile, are quietly watching their workload dry up.

Music professionals are beginning to express concern. Composer Leo Sidran believes AI is already taking work away from creators like him, noting that many former clients now rely on AI-generated solutions instead of original compositions.

Unlike previous tech innovations, which empowered musicians, AI risks erasing job opportunities entirely, according to Berklee College of Music professor George Howard, who warns it could become a zero-sum game.

AI music is especially popular for passive listening—background tracks for everyday life. In contrast, real musicians still hold value among fans who engage more actively with music.

However, AI is cheap, fast, and royalty-free, making it attractive to publishers and advertisers. From film soundtracks to playlists filled with faceless artists, synthetic sound is rapidly replacing human creativity in many commercial spaces.

Experts urge musicians to double down on what makes them unique instead of mimicking trends that AI can easily replicate. Live performance remains one of the few areas where AI has yet to gain traction. Until synthetic bands take the stage, artists may still find refuge in concerts and personal connection with fans.

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Flipkart employee deletes ChatGPT over emotional dependency

ChatGPT has become an everyday tool for many, serving as a homework partner, a research aid, and even a comforting listener. But questions are beginning to emerge about the emotional bonds users form with it. A recent LinkedIn post has reignited the debate around AI overuse.

Simrann M Bhambani, a marketing professional at Flipkart, publicly shared her decision to delete Cha tGPT from her devices. In a post titled ‘ChatGPT is TOXIC! (for me)’, she described how casual interaction escalated into emotional dependence. The platform began to resemble a digital therapist.

Bhambani admitted to confiding every minor frustration and emotional spiral to the chatbot. Its constant availability and non-judgemental replies gave her a false sense of security. Even with supportive friends, she felt drawn to the machine’s quiet reliability.

What began as curiosity turned into compulsion. She found herself spending hours feeding the bot intrusive thoughts and endless questions. ‘I gave my energy to something that wasn’t even real,’ she wrote. The experience led to more confusion instead of clarity.

Rather than offering mental relief, the chatbot fuelled her overthinking. The emotional noise grew louder, eventually becoming overwhelming. She realised that the problem wasn’t the technology itself, but how it quietly replaced self-reflection.

Deleting the app marked a turning point. Bhambani described the decision as a way to reclaim mental space and reduce digital clutter. She warned others that AI tools, while useful, can easily replace human habits and emotional processing if left unchecked.

Many users may not notice such patterns until they are deeply entrenched. AI chatbots are designed to be helpful and responsive, but they lack the nuance and care of human conversation. Their steady presence can foster a deceptive sense of intimacy.

People increasingly rely on digital tools to navigate their daily emotions, often without understanding the consequences. Some may find themselves withdrawing from human relationships or journalling less often. Emotional outsourcing to machines can significantly change how people process personal experiences.

Industry experts have warned about the risks of emotional reliance on generative AI. Chatbots are known to produce inaccurate or hallucinated responses, especially when asked to provide personal advice. Sole dependence on such tools can lead to misinformation or emotional confusion.

Companies like OpenAI have stressed that ChatGPT is not a substitute for professional mental health support. While the bot is trained to provide helpful and empathetic responses, it cannot replace human judgement or real-world relationships. Boundaries are essential.

Mental health professionals also caution against using AI as an emotional crutch. Reflection and self-awareness take time and require discomfort, which AI often smooths over. The convenience can dull long-term growth and self-understanding.

Bhambani’s story has resonated with many who have quietly developed similar habits. Her openness has sparked important discussions on emotional hygiene in the age of AI. More users are starting to reflect on their relationship with digital tools.

Social media platforms are also witnessing an increased number of posts about AI fatigue and cognitive overload. People are beginning to question how constant access to information and feedback affects emotional well-being. There is growing awareness around the need for balance.

AI is expected to become even more integrated into daily life, from virtual assistants to therapy bots. Recognising the line between convenience and dependency will be key. Tools are meant to serve, not dominate, personal reflection.

Developers and users alike must remain mindful of how often and why they turn to AI. Chatbots can complement human support systems, but they are not replacements. Bhambani’s experience serves as a cautionary tale in the age of machine intimacy.

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Tech giants back Trump’s AI deregulation plan amid public concern over societal impacts

Donald Trump recently hosted an AI summit in Washington, titled ‘Winning the AI Race,’ geared towards a deregulated atmosphere for AI innovation. Key figures from the tech industry, including Nvidia’s CEO Jensen Huang and Palantir’s CTO Shyam Sankar, attended the event.

Co-hosted by the Hill and Valley Forum and the Silicon Valley All-in Podcast, the summit was a platform for Trump to introduce his ‘AI Action Plan‘, comprised of three executive orders focusing on deregulation. Trump’s objective is to dismantle regulatory restrictions he perceives as obstacles to innovation, aiming to re-establish the US as a leader in AI exportation globally.

The executive orders announced target the elimination of ‘ideological dogmas such as diversity, equity, and inclusion (DEI)’ in AI models developed by federally funded companies. Additionally, one order promotes exporting US-developed AI technologies internationally, while another seeks to lessen environmental restrictions and speed up approvals for energy-intensive data centres.

These measures are seen as reversing the Biden administration’s policies, which stressed the importance of safety and security in AI development. Technology giants Apple, Meta, Amazon, and Alphabet have shown significant support for Trump’s initiatives, contributing to his inauguration fund and engaging with him at his Mar-a-Lago estate. Leaders like OpenAI’s Sam Altman and Nvidia’s Jensen Huang have also pledged substantial investments in US AI infrastructure.

Despite this backing, over 100 groups, including labour, environmental, civil rights, and academic organisations, have voiced their opposition through a ‘People’s AI action plan’. These groups warn of the potential risks of unregulated AI, which they fear could undermine civil liberties, equality, and environmental safeguards.

They argue that public welfare should not be compromised for corporate gains, highlighting the dangers of allowing tech giants to dominate policy-making. That discourse illustrates the divide between industry aspirations and societal consequences.

The tech industry’s influence on AI legislation through lobbying is noteworthy, with a report from Issue One indicating that eight of the largest tech companies spent a collective $36 million on lobbying in 2025 alone. Meta led with $13.8 million, employing 86 lobbyists, while Nvidia and OpenAI saw significant increases in their expenditure compared to previous years. The substantial financial outlay reflects the industry’s vested interest in shaping regulatory frameworks to favour business interests, igniting a debate over the ethical responsibilities of unchecked AI progress.

As tech companies and pro-business entities laud Trump’s deregulation efforts, concerns persist over the societal impacts of such policies.

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China issues action plan for global AI governance and proposes global AI cooperation organisation

At the 2025 World AI Conference in Shanghai, Chinese Premier Li Qiang urged the international community to prioritise joint efforts in governing AI, making reference to a need to establish a global framework and set of rules widely accepted by the global community. He unveiled a proposal by the Chinese government to create a global AI cooperation organisation to foster international collaboration, innovation, and inclusivity in AI across nations.

‘China attaches great importance to global AI governance, and has been actively promoting multilateral and bilateral cooperation with a willingness to offer more Chinese solutions‘.

An Action Plan for AI Global Governance was also presented at the conference. The plan outlines, in its introduction, a call for ‘all stakeholders to take concrete and effective actions based on the principles of serving the public good, respecting sovereignty, development orientation, safety and controllability, equity and inclusiveness, and openness and cooperation, to jointly advance the global development and governance of AI’.

The document includes 13 points related to key areas of international AI cooperation, including promoting inclusive infrastructure development, fostering open innovation ecosystems, ensuring high-quality data supply, and advancing sustainability through green AI practices. It also calls for consensus-building around technical standards, advancing international cooperation on AI safety governance, and supporting countries – especially those in the Global South – in ‘developing AI technologies and services suited to their national conditions’.

Notably, the plan indicates China’s support for multilateralism when it comes to the governance of AI, calling for an active implementation of commitments made by UN member states in the Pact for the Future and the Global Digital Compact, and expressing support for the establishment of the International AI Scientific Panel and a Global Dialogue on AI Governance (whose terms of reference are currently negotiated by UN member states in New York).

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AI startup Daydream revolutionises online fashion search

Online shopping for specific items like bridesmaid dresses can be challenging due to overwhelming choices. A new tech startup, Daydream, aims to simplify this. It uses AI to let users search for products by describing them in natural language, making the process easier and more intuitive.

For instance, a user could ask for a ‘revenge dress to wear to a party in Sicily in July,’ or ‘a summer bag to carry to work and cocktails after.’

Daydream, with staff based in New York and San Francisco, represents the latest venture in a growing trend of tech companies utilising AI to streamline and personalise online retail.

Consumer demand for such tools is evident: an Adobe Analytics survey of 5,000 US consumers revealed that 39% had used a generative AI tool for online shopping last year, with 53% planning to do so this year. Daydream faces competition from tech giants already active in this space.

Meta employs AI to facilitate seller listings and to target users with more relevant product advertisements. OpenAI has launched an AI agent capable of shopping across the web for users, and Amazon is trialling a similar feature.

Google has also introduced various AI shopping tools, including automated price tracking, a ‘circle to search’ function for identifying products in photos, and virtual try-on options for clothing.

Despite the formidable competition, Daydream’s CEO, Julie Bornstein, believes her company possesses a deeper understanding of the fashion and retail industries.

Bornstein’s extensive background includes helping build Nordstrom’s website as its vice president of e-commerce in the early 2000s and holding C-suite positions at Sephora and Stitch Fix. In 2018, she co-founded her first AI-powered shopping startup, The Yes, which was sold to Pinterest in 2022.

Bornstein asserts, ‘They don’t have the people, the mindset, the passion to do what needs to be done to make a category like fashion work for AI recommendations.’ She added, ‘Because I’ve been in this space my whole career, I know that having the catalogue with everything and being able to show the right person the right stuff makes shopping easier.’

Daydream has already secured $50 million in its initial funding round, attracting investors such as Google Ventures and model Karlie Kloss, founder of Kode With Klossy. The platform operates as a free, digital personal stylist.

Users can input their desired products using natural language, eliminating the need for complex Boolean search terms, thanks to its AI text recognition technology, or upload an inspiration photo.

Daydream then presents recommendations from over 8,000 brand partners, ranging from budget-friendly Uniqlo to luxury brand Gucci. Users can further refine their search through a chat interface, for example, by requesting more casual or less expensive alternatives.

As users interact more with the platform, it progressively tailors recommendations based on their search history, clicks, and saved items.

When customers are ready to purchase, they are redirected to the respective brand’s website to complete the transaction, with Daydream receiving a 20% commission on the sale.

Unlike many other major e-commerce players, Bornstein is deliberately avoiding ad-based rankings. She aims for products to appear on recommendation pages purely because they are a suitable match for the customer, not due to paid placements.

Bornstein stated, ‘As soon as Amazon started doing paid sponsorships, I’m like, ‘How can I find the real good product?’ She emphasised, ‘We want this to be a thing where we get paid when we show the customer the right thing.’

A recent CNN test of Daydream yielded mixed results. A search for a ‘white, fitted button-up shirt for the office with no pockets’ successfully returned a $145 cotton long-sleeve shirt from Theory that perfectly matched the description.

However, recommendations are not always flawless. A query for a ‘mother of the bride dress for a summer wedding in California’ presented several slinky slip dresses, some in white, alongside more formal styles, appearing more suitable for a bachelorette party.

Bornstein confirmed that the company continuously refined its AI models and gathered user feedback. She noted, ‘We want data on what people are doing so we can focus and learn where we do well and where we don’t.’

Part of this ongoing development involves training the AI to understand nuanced contextual cues, such as the implications of a ‘dress for a trip to Greece in August’ (suggesting hot weather) or an outfit for a ‘black-tie wedding’ (implying formality).

Daydream’s web version launched publicly last month, and it is currently in beta testing, with plans for an app release in the autumn. Bornstein envisions a future where AI extends beyond shopping, assisting with broader fashion needs like pairing new purchases with existing wardrobe items.

She concluded, ‘This was one of my earliest ideas, but I didn’t know the term (generative AI) and I didn’t know a large language model would be the unlock.’

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Delta Air Lines rolls out AI for personalised airfare

Delta Air Lines is shifting the landscape of airfare by leveraging AI to personalise ticket prices. Moving beyond fixed fares, Delta aims to tailor prices closely to each traveller.

Instead of static prices, the system now analyses customer habits, booking history, and even the time of day to predict an individual’s potential willingness to pay. By the end of the current year, Delta aims to set 20% of its ticket prices using AI dynamically.

The goal represents a significant, sevenfold increase from just twelve months prior. Such a high-tech approach could result in more advantageous deals or elevated costs, depending on a passenger’s unique circumstances and shopping behaviour.

It is crucial to understand how this system operates, Delta’s motivations, and its implications for consumer finances. Traditional ticket pricing has long relied on ‘fare buckets,’ where customers are categorised based on their booking method and timing.

Delta’s new AI ticket pricing system fundamentally shifts away from these static rates. It analyses real-time information to calculate precisely what a specific customer will likely spend on a seat for any given flight.

Glen Hauenstein, Delta’s President, describes this as a complete re-engineering of pricing. He characterises AI as a ‘super analyst’ working continuously, 24/7, to identify the optimal price for every traveller, every time.

The airline has collaborated with Fetcherr, which provides the underlying technological infrastructure and supports other global airlines. Airlines do not adopt advanced, high-tech pricing systems to reduce revenue.

Delta reports that initial results from its AI-driven pricing indicate ‘amazingly favourable’ revenues. The airline believes AI will maximise profits by more accurately aligning fares with each passenger’s willingness to pay.

However, this is determined by a vast array of data inputs, ranging from individual booking history to prevailing market trends. Delta’s core strategy is straightforward: to offer a price available for a specific flight, at a particular time, to you, the individual consumer.

Consumers who have previously observed frequent fluctuations in airfare should now anticipate even greater volatility. Delta’s new system could present a different price to one person compared to another for the same seat, with the calculation performed in real-time by the AI.

Passengers might receive special offers or early discounts if the AI identifies a need to fill seats quickly. However, discerning whether one is securing a ‘fair’ deal becomes significantly more challenging. The displayed price is now a function of what the AI believes an individual will pay, rather than a universal rate applicable to all.

The shift has prompted concerns among some privacy advocates. They worry that such personalised pricing could disadvantage customers who lack the resources or time to search extensively for the most favourable deals.

Consequently, those less able to shop around may be charged the highest prices. Delta has been approached for comment, and a spokesperson stated: ‘There is no fare product Delta has ever used, is testing, or plans to use that targets customers with individualised offers based on personal information or otherwise.

Various market forces have driven the dynamic pricing model used in the global industry for decades, with new tech streamlining this process. Delta always complies with regulations around pricing and disclosures.’

Delta’s openness regarding this significant policy change has attracted considerable national attention. Other airlines are already trialling their AI fare systems, and industry experts widely anticipate that the rest of the sector will soon follow suit.

Nevertheless, privacy advocates and several lawmakers are vocalising strong objections. Critics contend that allowing AI to determine pricing behind the scenes is akin to airlines ‘hacking our brains’ to ascertain the maximum price a customer will accept, as described by Consumer Watchdog.

The legal ramifications of this approach are still unfolding. While price variation based on demand or timing is not novel, the use of AI for ultra-personalised pricing raises uncomfortable questions about potential discrimination and fairness, particularly given prior research suggesting that economically disadvantaged customers frequently receive less favourable deals.

Delta’s AI pricing system personalises every airfare, making each search and price specific to the user. Universal ticket prices are fading as AI analyses booking habits and market conditions. This technology can quickly offer special deals to fill seats or raise prices if demand is detected.

Conversely, the price can increase if the system senses a greater willingness to pay. Shopping around is now an absolute necessity. Utilising a VPN can help outsmart the system by masking location and IP address, which prevents airlines from tracking searches and adjusting prices based on geographic region.

Making quick decisions might result in savings, but procrastination could lead to a price increase. Privacy is paramount; the airline gains insights into a user’s habits with every search. A digital footprint directly influences fares. In essence, consumers now possess both increased power and greater responsibility.

Being astute, flexible, and constantly comparing before purchasing is vital. Delta’s transition to AI-driven ticket pricing significantly shifts how consumers purchase flight tickets.

While offering potential for enhanced flexibility and efficiency, it simultaneously raises substantial questions concerning fairness, privacy, and transparency.

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Robot artist Ai-Da explores human self-perception

The world’s first ultra-realistic robot artist, Ai-Da, has been prompting profound questions about human-robot interactions, according to her creator.

Designed in Oxford by Aidan Meller, a modern and contemporary art specialist, and built in the UK by Engineered Arts, Ai-Da is a humanoid robot specifically engineered for artistic creation. She recently unveiled a portrait of King Charles III, adding to her notable portfolio.

Aidan Meller, Ai-Da’s creator, stated that working with the robot has evoked ‘lots of questions about our relationship with ourselves.’ He highlighted how Ai-Da’s artwork ‘drills into some of our time’s biggest concerns and thoughts.’

Ai-Da uses cameras in her eyes to capture images, which are then processed by AI algorithms and converted into real-time coordinates for her robotic arm, enabling her to paint and draw.

Mr Meller explained, ‘You can meet her, talk to her using her language model, and she can then paint and draw you from sight.’

He also observed that people’s preconceptions about robots are often outdated: ‘It’s not until you look a robot in the eye and they say your name that the reality of this new sci-fi world that we are now in takes hold.’

Ai-Da’s contributions to the art world continue to grow. She had produced and showcased her work at the AI for Good Global Summit 2024 in Geneva, Switzerland, an event under the auspices of the UN. That same year, her triptych of Enigma code-breaker Alan Turing sold for over £1 million at auction.

Her focus this year shifted to King Charles III, chosen because, as Mr Meller noted, ‘With extraordinary strides that are taking place in technology and again, always questioning our relationship to the environment, we felt that King Charles was an excellent subject.’

Buckingham Palace authorised the display of Ai-Da’s portrait of the King, despite the robot not meeting him. Ai-Da, connected to the internet, uses extensive data to inform her choice of subjects, with Mr Meller revealing, ‘Uncannily, and rather nerve-rackingly, we just ask her.’

The conversations generated inform the artwork. Ai-Da also painted a portrait of King Charles’s mother, Queen Elizabeth II, in 2023. Mr Meller shared that the most significant realisation from six years of working with Ai-Da was ‘not so much about how human she is but actually how robotic we are.’

He concluded, ‘We hope Ai-Da’s artwork can be a provocation for that discussion.’

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Guess AI model sparks fashion world debate

A striking new ‘supermodel’ has appeared in the August print edition of Vogue, featuring in a Guess advert for their summer collection. Uniquely, the flawless blonde model is not real, as a small disclaimer reveals she was created using AI.

While Vogue clarifies the AI model’s inclusion was an advertising decision, not editorial, it marks a significant first for the magazine and has ignited widespread controversy.

The development raises serious questions for real models, who have long campaigned for greater diversity, and consumers, particularly young people, are already grappling with unrealistic beauty standards.

Seraphinne Vallora, the company behind the controversial Guess advert, comprises founders Valentina Gonzalez and Andreea Petrescu. They told the BBC that Guess’s co-founder, Paul Marciano, approached them on Instagram to create an AI model for the brand’s summer campaign.

Valentina Gonzalez explained, ‘We created 10 draft models for him and he selected one brunette woman and one blonde that we developed further.’ Petrescu described AI image generation as a complex process, with their five employees taking up to a month to create a finished product, charging clients like Guess up to the low six figures.

However, plus-size model Felicity Hayward, with over a decade in the industry, criticised the use of AI models, stating it ‘feels lazy and cheap’ and worried it could ‘undermine years of work towards more diversity in the industry.’

Hayward believes the fashion industry, which saw strides in inclusivity in the 2010s, has regressed, leading to fewer bookings for diverse models. She warned, ‘The use of AI models is another kick in the teeth that will disproportionately affect plus-size models.’

Gonzalez and Petrescu insist they do not reinforce narrow beauty standards, with Petrescu claiming, ‘We don’t create unattainable looks – the AI model for Guess looks quite realistic.’ They contended, ‘Ultimately, all adverts are created to look perfect and usually have supermodels in, so what we do is no different.’

While admitting their company’s Instagram shows a lack of diversity, Gonzalez explained to the BBC that attempts to post AI images of women with different skin tones did not gain traction, stating, ‘people do not respond to them – we don’t get any traction or likes.’

They also noted that the technology is not yet advanced enough to create plus-size AI women. However, this mirrors a 2024 Dove campaign that highlighted AI bias by showing image generators consistently producing thin, white, blonde women when asked for ‘the most beautiful woman in the world.’

Vanessa Longley, CEO of eating disorder charity Beat, found the advert ‘worrying,’ telling the BBC, ‘If people are exposed to images of unrealistic bodies, it can affect their thoughts about their own body, and poor body image increases the risk of developing an eating disorder.’

The lack of transparent labelling for AI-generated content in the UK is also a concern, despite Guess having a small disclaimer. Sinead Bovell, a former model and now tech entrepreneur, told the BBC that not clearly labelling AI content is ‘exceptionally problematic’ due to ‘AI is already influencing beauty standards.’

Sara Ziff, a former model and founder of Model Alliance, views Guess’s campaign as “less about innovation and more about desperation and need to cut costs,’ advocating for ‘meaningful protections for workers’ in the industry.

Seraphinne Vallora, however, denies replacing models, with Petrescu explaining, ‘We’re offering companies another choice in how they market a product.’

Despite their website claiming cost-efficiency by ‘eliminating the need for expensive set-ups… hiring models,’ they involve real models and photographers in their AI creation process. Vogue’s decision to run the advert has drawn criticism on social media, with Bovell noting the magazine’s influential position, which means they are ‘in some way ruling it as acceptable.’

Looking ahead, Bovell predicts more AI-generated models but not their total dominance, foreseeing a future where individuals might create personal AI avatars to try on clothes and a potential ‘society opting out’ if AI models become too unattainable.

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The US push for AI dominance through openness

In a bold move to maintain its edge in the global AI race—especially against China—the United States has unveiled a sweeping AI Action Plan with 103 recommendations. At its core lies an intriguing paradox: the push for open-source AI, typically associated with collaboration and transparency, is now being positioned as a strategic weapon.

As Jovan Kurbalija points out, this plan marks a turning point where open-weight models are framed not just as tools of innovation, but as instruments of geopolitical influence, with the US aiming to seed the global AI ecosystem with American-built systems rooted in ‘national values.’

The plan champions Silicon Valley by curbing regulations, limiting federal scrutiny, and shielding tech giants from legal liability—potentially reinforcing monopolies. It also underlines a national security-first mentality, urging aggressive safeguards against foreign misuse of AI, cyber threats, and misinformation. Notably, it proposes DARPA-led initiatives to unravel the inner workings of large language models, acknowledging that even their creators often can’t fully explain how these systems function.

Internationally, the plan takes a competitive, rather than cooperative, stance. Allies are expected to align with US export controls and values, while multilateral forums like the UN and OECD are dismissed as bureaucratic and misaligned. That bifurcation risks alienating global partners—particularly the EU, which favours heavy AI regulation—while increasing pressure on countries like India and Japan to choose sides in the US–China tech rivalry.

Despite its combative framing, the strategy also nods to inclusion and workforce development, calling for tax-free employer-sponsored AI training, investment in apprenticeships, and growing military academic hubs. Still, as Kurbalija warns, the promise of AI openness may clash with the plan’s underlying nationalistic thrust—raising questions about whether it truly aims to democratise AI, or merely dominate it.

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AI reshaping the US labour market

AI is often seen as a job destroyer, but it’s also emerging as a significant source of new employment, according to a new Brookings report. The number of job postings mentioning AI has more than doubled in the past year, with demand continuing to surge across various industries and regions.

Over the past 15 years, AI-related job listings have grown nearly 29% annually, far outpacing the 11% growth rate of overall job postings in the broader economy.

Brookings based its findings on data from Lightcast, a labour market analytics firm, and noted rising demand for AI skills across sectors, including manufacturing. According to the US Census Bureau’s Business Trends Survey, the share of manufacturers using AI has jumped from 4% in early 2023 to 9% by mid-2025.

Yet, AI jobs still form a small part of the market. Goldman Sachs predicts widespread AI adoption will peak in the early 2030s, with a slower near-term influence on jobs. ‘AI is visible in the micro labour market data, but it doesn’t dominate broader job dynamics,’ said Joseph Briggs, an economist at Goldman Sachs.

Roles range from AI engineers and data scientists to consultants and marketers learning to integrate AI into business operations responsibly and ethically. In 2025, over 80,000 job postings cited generative AI skills—up from fewer than 4,000 in 2010, Brookings reported, indicating explosive long-term growth.

Job openings involving ‘responsible AI’—those addressing ethical AI use in business and society—are also rising, according to data from Indeed and Lightcast. ‘As AI evolves, so does what counts as an AI job,’ said Cory Stahle of the Indeed Hiring Lab, noting that definitions shift with new business applications.

AI skills carry financial value, too. Lightcast found that jobs requiring AI expertise offer an average salary premium of $18,000, or 28% more annually. Unsurprisingly, tech hubs like Silicon Valley and Seattle dominate AI hiring, but job growth spreads to regions like the Sunbelt and the East Coast.

Mark Muro of Brookings noted that universities play a key role in AI job growth across new regions by fuelling local innovation. AI is also entering non-tech fields such as finance, human resources, and marketing, with more than half of AI-related postings now being outside IT roles.

Muro expects more widespread AI adoption in the next few years, as employers gain clarity on its value, limitations and potential for productivity. ‘There’s broad consensus that AI boosts productivity and economic competitiveness,’ he said. ‘It energises regional leaders and businesses to act more quickly.’

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