Future of work

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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Experts urge broader values in AI development

Since the launch of ChatGPT in late 2023, the private sector has led AI innovation. Major players like Microsoft, Google, and Alibaba—alongside emerging firms such as Anthropic and Mistral—are racing to monetise AI and secure long-term growth in the technology-driven economy.

But during the Fortune Brainstorm AI conference in Singapore this week, experts stressed the importance of human values in shaping AI’s future. Anthea Roberts, founder of Dragonfly Thinking, argued that AI must be built not just to think faster or cheaper, but also to think better.

She highlighted the risk of narrow thinking—national, disciplinary or algorithmic—and called for diverse, collaborative thinking to counter it. Roberts sees potential in human-AI collaboration, which can help policymakers explore different perspectives, boosting the chances of sound outcomes.

Russell Wald, executive director at Stanford’s Institute for Human-Centred AI, called AI a civilisation-shifting force. He stressed the need for an interdisciplinary ecosystem—combining academia, civil society, government and industry—to steer AI development.

‘Industry must lead, but so must academia,’ Wald noted, as well as universities’ contributions to early research, training, and transparency. Despite widespread adoption, AI scepticism persists, due to issues like bias, hallucination, and unpredictable or inappropriate language.

Roberts said most people fall into two camps: those who use AI uncritically, such as students and tech firms, and those who reject it entirely.

She labelled the latter as practising ‘critical non-use’ due to concerns over bias, authenticity and ethical shortcomings in current models. Inviting a broader demographic into AI governance, Roberts urged more people—especially those outside tech hubs like Silicon Valley—to shape its future.

Wald noted that in designing AI, developers must reflect the best of humanity: ‘Not the crazy uncle at the Thanksgiving table.’

Both experts believe the stakes are high, and the societal benefits of getting AI right are too great to ignore or mishandle. ‘You need to think not just about what people want,’ Roberts said, ‘but what they want to want—their more altruistic instincts.’

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Democratising inheritance: AI tool handles estate administration

Lauren Kolodny, who early backed Chime and earned a spot on the Forbes Midas list, is leading a $20 million Series A funding round into Alix, a San Francisco-based startup using AI to revolutionise estate settlement. Founder Alexandra Mysoor conceived the idea after spending nearly 1,000 hours over 18 months managing a friend’s family estate, highlighting a widespread, emotionally taxing administrative gap.

Using AI agents, Alix automates tedious elements of the estate process, including scanning documents, extracting data, pre-populating legal forms, and liaising with financial institutions. This contrasts sharply with the traditional, costly probate system. The startup’s pricing model charges around 1% of estate value, translating to approximately $9,000–$12,000 for smaller estates.

Kolodny sees Alix as part of a new wave of startups harnessing AI to democratise services once accessible only to high-net-worth individuals. As trillions of dollars transfer to millennials and Gen Z in the coming decades, Alix aims to simplify one of the most complex and emotionally fraught administrative tasks.

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Google’s AI Overviews reach 2 billion users monthly, reshaping the web’s future

Google’s AI Overviews, the generative summaries placed above traditional search results, now serve over 2 billion users monthly, a sharp rise from 1.5 billion just last quarter.

First launched in May 2023 and widely available in the US by mid-2024, the feature has rapidly expanded across more than 200 countries and 40 languages.

The widespread use of AI Overviews transforms how people search and who benefits. Google reports that the feature boosts engagement by over 10% for queries where it appears.

However, a study by Pew Research shows clicks on search results drop significantly when AI Overviews are shown, with just 8% of users clicking any link, and only 1% clicking within the overview itself.

While Google claims AI Overviews monetise at the same rate as regular search, publishers are left out unless users click through, which they rarely do.

Google has started testing ads within the summaries and is reportedly negotiating licensing deals with select publishers, hinting at a possible revenue-sharing shift. Meanwhile, regulators in the US and EU are scrutinising whether the feature violates antitrust laws or misuses content.

Industry experts warn of a looming ‘Google Zero’ future — a web where search traffic dries up and AI-generated answers dominate.

As visibility in search becomes more about entity recognition than page ranking, publishers and marketers must rethink how they maintain relevance in an increasingly post-click environment.

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Quantum computing faces roadblocks to real-world use

Quantum computing holds vast promise for sectors from climate modelling to drug discovery and AI, but it remains far from mainstream due to significant barriers. The fragility of qubits, the shortage of scalable quantum software, and the immense number of qubits required continue to limit progress.

Keeping qubits stable is one of the most significant technical obstacles, with most only lasting microseconds before disruption. Current solutions rely on extreme cooling and specialised equipment, which remain expensive and impractical for widespread use.

Even the most advanced systems today operate with a fraction of the qubits needed for practical applications, while software options remain scarce and highly tailored. Businesses exploring quantum solutions must often build their tools from scratch, adding to the cost and complexity.

Beyond technology, the field faces social and structural challenges. A lack of skilled professionals and fears around unequal access could see quantum benefits restricted to big tech firms and governments.

Security is another looming concern, as future quantum machines may be capable of breaking current encryption standards. Policymakers and businesses must develop defences before such systems become widely available.

AI may accelerate progress in both directions. Quantum computing can supercharge model training and simulation, while AI is already helping to improve qubit stability and propose new hardware designs.

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Trump AI strategy targets China and cuts red tape

The Trump administration has revealed a sweeping new AI strategy to cement US dominance in the global AI race, particularly against China.

The 25-page ‘America’s AI Action Plan’ proposes 90 policy initiatives, including building new data centres nationwide, easing regulations, and expanding exports of AI tools to international allies.

White House officials stated the plan will boost AI development by scrapping federal rules seen as restrictive and speeding up construction permits for data infrastructure.

A key element involves monitoring Chinese AI models for alignment with Communist Party narratives, while promoting ‘ideologically neutral’ systems within the US. Critics argue the approach undermines efforts to reduce bias and favours politically motivated AI regulation.

The action plan also supports increased access to federal land for AI-related construction and seeks to reverse key environmental protections. Analysts have raised concerns over energy consumption and rising emissions linked to AI data centres.

While the White House claims AI will complement jobs rather than replace them, recent mass layoffs at Indeed and Salesforce suggest otherwise.

Despite the controversy, the announcement drew optimism from investors. AI stocks saw mixed trading, with NVIDIA, Palantir and Oracle gaining, while Alphabet slipped slightly. Analysts described the move as a ‘watershed moment’ for US tech, signalling an aggressive stance in the global AI arms race.

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AI music tools arrive for YouTube creators

YouTube is trialling two new features to improve user engagement and content creation. One enhances comment readability, while the other helps creators produce music using AI for Shorts.

A new threaded layout is being tested to organise comment replies under the original post, allowing more explicit and focused conversations. Currently, this feature is limited to a small group of Premium users on mobile.

YouTube also expands Dream Track, an AI-powered tool that creates 30-second music clips from simple text prompts. Creators can generate sounds matching moods like ‘chill piano melody’ or ‘energetic pop beat’, with the option to include AI-generated vocals styled after popular artists.

Both features are available only in the US during the testing phase, with no set date for international release. YouTube’s gradual updates reflect a shift toward more intuitive user experiences and creative flexibility on the platform.

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ASEAN urged to unite on digital infrastructure

Asia stands at a pivotal moment as policymakers urge swift deployment of converging 5G and AI technologies. Experts argue that 5G should be treated as a foundational enabler for AI, not just a telecom upgrade, to power future industries.

A report from the Lee Kuan Yew School of Public Policy identifies ten urgent imperatives, notably forming national 5G‑AI strategies, empowering central coordination bodies and modernising spectrum policies. Industry leaders stress that aligning 5G and AI investment is essential to sustain innovation.

Without firm action, the digital divide could deepen and stall progress. Coordinated adoption and skilled workforce development are seen as critical to turning incremental gains into transformational regional leadership.

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Amazon closes AI research lab in Shanghai as global focus shifts

Amazon is shutting down its AI research lab in Shanghai, marking another step in its gradual withdrawal from China. The move comes amid continuing US–China trade tensions and a broader trend of American tech companies reassessing their presence in the country.

The company said the decision was part of a global streamlining effort rather than a response to AI concerns.

A spokesperson for AWS said the company had reviewed its organisational priorities and decided to cut some roles across certain teams. The exact number of job losses has not been confirmed.

Before Amazon’s confirmation, one of the lab’s senior researchers noted on WeChat that the Shanghai site was the final overseas AWS AI research lab and attributed its closure to shifts in US–China strategy.

The team had built a successful open-source graph neural network framework known as DGL, which reportedly brought in nearly $1 billion in revenue for Amazon’s e-commerce arm.

Amazon has been reducing its footprint in China for several years. It closed its domestic online marketplace in 2019, halted Kindle sales in 2022, and recently laid off AWS staff in the US.

Other tech giants including IBM and Microsoft have also shut down China-based research units this year, while some Chinese AI firms are now relocating operations abroad instead of remaining in a volatile domestic environment.

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Teen builds Hindi AI tool to help paralysis patients speak

An Indian teenager has created a low-cost AI device that translates slurred speech into clear Hindi, helping patients with paralysis and neurological conditions communicate more easily.

Pranet Khetan’s innovation, Paraspeak, uses a custom Hindi speech recognition model to address a long-ignored area of assistive tech.

The device was inspired by Khetan’s visit to a paralysis care centre, where he saw patients struggling to express themselves. Unlike existing English models, Paraspeak is trained on the first Hindi dysarthic speech dataset in India, created by Khetan himself through recordings and data augmentation.

Using transformer architecture, Paraspeak converts unclear speech into understandable output using cloud processing and a neck-worn compact device. It is designed to be scalable across different speakers, unlike current solutions that only work for individual patients.

The AI device is affordable, costing around ₹2,000 to build, and is already undergoing real-world testing. With no existing market-ready alternative for Hindi speakers, Paraspeak represents a significant step forward in inclusive health technology.

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