Future of work

How AI agents are quietly rebuilding the foundations of the global economy 

AI agents have rapidly moved from niche research concepts to one of the most discussed technology topics of 2025. Search interest for ‘AI agents’ surged throughout the year, reflecting a broader shift in how businesses and institutions approach automation and decision-making.

Market forecasts suggest that 2026 and the years ahead will bring an even larger boom in AI agents, driven by massive global investment and expanding real-world deployment. As a result, AI agents are increasingly viewed as a foundational layer of the next phase of the digital economy.

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What are AI agents, and why do they matter

AI agents are autonomous software systems designed to perceive information, make decisions, and act independently to achieve specific goals. Unlike traditional AI applications or conventional AI tools, which respond to prompts or perform single functions and often require direct supervision, AI agents are proactive and operate across multiple domains.

They can plan, adapt, and coordinate various steps across workflows, anticipating needs, prioritising tasks, and collaborating with other systems or agents without constant human intervention.

As a result, AI agents are not just incremental upgrades to existing software; they represent a fundamental change in how organisations leverage technology. By taking ownership of complex processes and decision-making workflows, AI agents enable businesses to operate at scale, adapt more rapidly to change, and unlock opportunities that were previously impossible with traditional AI tools alone. 

They fundamentally change how AI is applied in enterprise environments, moving from task automation to outcome-driven execution. 

Behind the scenes, autonomous AI agents are moving into the core of economic systems, reshaping workflows, authority, and execution across the entire value chain.

Why AI agents became a breakout trend in 2025

Several factors converged in 2025 to push AI agents into the mainstream. Advances in large language models, improved reasoning capabilities, and lower computational costs made agent-based systems commercially viable. At the same time, enterprises faced growing pressure to increase efficiency amid economic uncertainty and labour constraints. 

The fact is that AI agents gained traction not because of their theoretical promise, but because they delivered measurable results. Companies deploying AI agents reported faster execution, lower operational overhead, and improved scalability across departments. As adoption accelerated, AI agents became one of the most visible indicators of where new technology was heading next.

Behind the scenes, autonomous AI agents are moving into the core of economic systems, reshaping workflows, authority, and execution across the entire value chain.

Global investment is accelerating the AI agents boom

Investment trends underline the strategic importance of AI agents. Venture capital firms, technology giants, and state-backed innovation funds are allocating significant capital to agent-based platforms, orchestration frameworks, and AI infrastructure. These investments are not experimental in nature; they reflect long-term bets on autonomous systems as core business infrastructure.

Large enterprises are committing internal budgets to AI agent deployment, often integrating them directly into mission-critical operations. As funding flows into both startups and established players, competition is intensifying, further accelerating innovation and adoption across global markets. 

The AI agents market is projected to surge from approximately $7.92 billion in 2025 to surpass $236 billion by 2034, driven by a compound annual growth rate (CAGR) exceeding 45%.

Behind the scenes, autonomous AI agents are moving into the core of economic systems, reshaping workflows, authority, and execution across the entire value chain.

Where AI agents are already being deployed at scale

Agent-based systems are no longer limited to experimental use, as adoption at scale is taking shape across various industries. In finance, AI agents manage risk analysis, fraud detection, reporting workflows, and internal compliance processes. Their ability to operate continuously and adapt to changing data makes them particularly effective in data-intensive environments.

In business operations, AI agents are transforming customer support, sales operations, procurement, and supply chain management. Autonomous agents handle inquiries, optimise pricing strategies, and coordinate logistics with minimal supervision.

One of the clearest areas of AI agent influence is software development, where teams are increasingly adopting autonomous systems for code generation, testing, debugging, and deployment. These systems reduce development cycles and allow engineers to focus on higher-level design and architecture. It is expected that by 2030, around 70% of developers will work alongside autonomous AI agents, shifting human roles toward planning, design, and orchestration.

Healthcare, research, and life sciences are also adopting AI agents for administrative automation, data analysis, and workflow optimisation, freeing professionals from repetitive tasks and improving operational efficiency.

Behind the scenes, autonomous AI agents are moving into the core of economic systems, reshaping workflows, authority, and execution across the entire value chain.

The economic impact of AI agents on global productivity

The broader economic implications of AI agents extend far beyond individual companies. At scale, autonomous AI systems have the potential to boost global productivity by eliminating structural inefficiencies across various industries. By automating complex, multi-step processes rather than isolated tasks, AI agents compress decision timelines, lower transaction costs, and remove friction from business operations.

Unlike traditional automation, AI agents operate across entire workflows in real time. It enables organisations to respond more quickly to market changes and shifts in demand, thereby increasing operational agility and efficiency at a systemic level.

Labour markets will also evolve as agent-based systems become embedded in daily operations. Routine and administrative roles are likely to decline, while demand will rise for skills related to oversight, workflow design, governance, and strategic management of AI-driven operations. Human value is expected to shift toward planning, judgement, and coordination. 

Countries and companies that successfully integrate autonomous AI into their economic frameworks are likely to gain structural advantages in terms of efficiency and growth, while those that lag behind risk falling behind in an increasingly automated global economy.

Behind the scenes, autonomous AI agents are moving into the core of economic systems, reshaping workflows, authority, and execution across the entire value chain.

AI agents and the future evolution of AI 

The momentum behind AI agents shows no signs of slowing. Forecasts indicate that adoption will expand rapidly in 2026 as costs decline, standards mature, and regulatory clarity improves. For organisations, the strategic question is no longer whether AI agents will become mainstream, but how quickly they can be integrated responsibly and effectively. 

As AI agents mature, their influence will extend beyond business operations to reshape global economic structures and societal norms. They will enable entirely new industries, redefine the value of human expertise, and accelerate innovation cycles, fundamentally altering how economies operate and how people interact with technology in daily life. 

The widespread integration of AI agents will also reshape the world we know. From labour markets to public services, education, and infrastructure, societies will experience profound shifts as humans and autonomous systems collaborate more closely.

Companies and countries that adopt these technologies strategically will gain a structural advantage, while those that lag behind risk falling behind in both economic and social innovation.

Ultimately, AI agents are not just another technological advancement; they are becoming a foundational infrastructure for the future economy. Their autonomy, intelligence, and scalability position them to influence how value is created, work is organised, and global markets operate, marking a turning point in the evolution of AI and its role in shaping the modern world.

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NVIDIA and Siemens build new industrial AI operating system

Siemens and NVIDIA have expanded their strategic partnership to build what they describe as an Industrial AI operating system.

The collaboration aims to embed AI-driven intelligence throughout the entire industrial lifecycle, from product design and engineering to manufacturing, operations and supply chains.

Siemens will contribute industrial AI expertise alongside hardware and software, while NVIDIA will provide AI infrastructure, simulation technologies and accelerated computing platforms.

The companies plan to develop fully AI-driven adaptive manufacturing sites, beginning in 2026 with Siemens’ electronics factory in Erlangen, Germany.

Digital twins will be used as active intelligence tools instead of static simulations, allowing factories to analyse performance in real time, test improvements virtually and convert successful adjustments directly into operational changes.

Both firms will also accelerate semiconductor design by combining Siemens’ EDA tools with NVIDIA’s GPU-accelerated computing and AI models. The goal is to shorten design cycles, improve manufacturing yields and support the development of advanced AI-enabled products.

The partnership also aims to create next-generation AI factories that optimise power, cooling, automation and infrastructure efficiency.

Siemens and NVIDIA intend to use the same technologies internally to improve their own operations before scaling them to customers. They argue the partnership will help industries adopt AI more rapidly and reliably, while supporting more resilient and sustainable manufacturing worldwide.

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Meta pauses global launch of Ray-Ban Display glasses

The US tech company, Meta, has paused the international launch of its Ray-Ban Display smart glasses after seeing higher-than-expected demand in the US.

Meta had planned to begin selling the glasses in the UK, France, Italy and Canada in early 2026, but will now prioritise fulfilling US orders instead of expanding availability.

These smart glasses work with the Meta Neural Band wrist device, which interprets small hand movements.

Meta demonstrated new tools at CES in Las Vegas, including a teleprompter mode for delivering prepared remarks and a feature that lets users write messages by moving a finger across any surface while wearing the Neural Band. Pedestrian navigation support is also being extended to additional US cities.

Meta says demand has created waiting lists stretching well into 2026, prompting the pause while it reassesses global rollout plans.

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Samsung puts AI trust and security at the centre of CES 2026

The South Korean tech giant, Samsung, used CES 2026 to foreground a cross-industry debate about trust, privacy and security in the age of AI.

During its Tech Forum session in Las Vegas, senior figures from AI research and industry argued that people will only fully accept AI when systems behave predictably, and users retain clear control instead of feeling locked inside opaque technologies.

Samsung outlined a trust-by-design philosophy centred on transparency, clarity and accountability. On-device AI was presented as a way to keep personal data local wherever possible, while cloud processing can be used selectively when scale is required.

Speakers said users increasingly want to know when AI is in operation, where their data is processed and how securely it is protected.

Security remained the core theme. Samsung highlighted its Knox platform and Knox Matrix to show how devices can authenticate one another and operate as a shared layer of protection.

Partnerships with companies such as Google and Microsoft were framed as essential for ecosystem-wide resilience. Although misinformation and misuse were recognised as real risks, the panel suggested that technological counter-measures will continue to develop alongside AI systems.

Consumer behaviour formed a final point of discussion. Amy Webb noted that people usually buy products for convenience rather than trust alone, meaning that AI will gain acceptance when it genuinely improves daily life.

The panel concluded that AI systems which embed transparency, robust security and meaningful user choice from the outset are most likely to earn long-term public confidence.

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UAE deploys AI ecosystem to support climate-vulnerable agriculture

The United Arab Emirates has launched an AI-driven ecosystem to help climate-vulnerable agricultural regions adapt to increasingly volatile weather. The initiative reinforces the country’s ambition to position itself as a global hub for applied AI in climate resilience and food security.

Unveiled in Abu Dhabi, the programme builds on a US$200m partnership with the Gates Foundation announced during COP28. It reflects a shift from climate pledges toward deployable technology as droughts, floods and heat stress intensify pressure on agriculture, particularly in the Global South.

At the core is an integrated ecosystem linking scientific research, AI model development and digital advisory tools with large-scale deployment. Rather than isolated pilots, the programmes are designed to translate data into practical tools used directly by governments, NGOs and farmers.

Abu Dhabi is positioning itself as a hub for agricultural AI through the CGIAR AI Hub and a new institute at Mohamed bin Zayed University of Artificial Intelligence. The ecosystem also includes AgriLLM, an open-source model trained on agricultural and climate data.

Delivery is supported by AIM for Scale, a joint UAE–Gates Foundation initiative expanding AI-powered weather forecasting in data-scarce regions. In India, AI-enabled monsoon forecasts reached an estimated 38 million farmers in 2025, with further deployments planned.

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California launches DROP tool to erase data broker records

Residents in California now have a simpler way to force data brokers to delete their personal information.

The state has launched the Delete Requests and Opt-Out Platform, known as DROP, allowing residents to submit one verified deletion request that applies to every registered data broker instead of contacting each company individually.

A system that follows the Delete Act, passed in 2023, and is intended to create a single control point for consumer data removal.

Once a resident submits a request, the data brokers must begin processing it from August 2026 and will have 90 days to act. If data is not deleted, residents may need to provide extra identifying details.

First-party data collected directly by companies can still be retained, while data from public records, such as voter rolls, remains exempt. Highly sensitive data may fall under separate legal protections such as HIPAA.

The California Privacy Protection Agency argues that broader data deletion could reduce identity theft, AI-driven impersonation, fraud risk and unwanted marketing contact.

Penalties for non-compliance include daily fines for brokers who fail to register or ignore deletion orders. The state hopes the tool will make data rights meaningful instead of purely theoretical.

A launch that comes as regulators worldwide examine how personal data is used, traded and exploited.

California is positioning itself as a leader in consumer privacy enforcement, while questions continue about how effectively DROP will operate when the deadline arrives in 2026.

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Cloud and AI growth fuels EU push for greener data centres

Europe’s growing demand for cloud and AI services is driving a rapid expansion of data centres across the EU.

Policymakers now face the difficulty of supporting digital growth instead of undermining climate targets, yet reliable sustainability data remains scarce.

Operators are required to report on energy consumption, water usage, renewable sourcing and heat reuse, but only around one-third have submitted complete data so far.

Brussels plans to introduce a rating scheme from 2026 that grades data centres on environmental performance, potentially rewarding the most sustainable new facilities with faster approvals under the upcoming Cloud and AI Development Act.

Industry groups want the rules adjusted so operators using excess server heat to warm nearby homes are not penalised. Experts also argue that stronger auditing and stricter application of standards are essential so reported data becomes more transparent and credible.

Smaller data centres remain largely untracked even though they are often less efficient, while colocation facilities complicate oversight because customers manage their own servers. Idle machines also waste vast amounts of energy yet remain largely unmeasured.

Meanwhile, replacing old hardware may improve efficiency but comes with its own environmental cost.

Even if future centres run on cleaner power and reuse heat, the manufacturing footprint of the equipment inside them remains a major unanswered sustainability challenge.

Policymakers say better reporting is essential if the EU is to balance digital expansion with climate responsibility rather than allowing environmental blind spots to grow.

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AI tool helps find new treatments for heart disease

A new ΑΙ system developed at Imperial College London could accelerate the discovery of treatments for heart disease by combining detailed heart scans with huge medical databases.

Cardiovascular disease remains the leading cause of death across the EU, accounting for around 1.7 million deaths every year, so researchers believe smarter tools are urgently needed.

The AI model, known as CardioKG, uses imaging data from thousands of UK Biobank participants, including people with heart failure, heart attacks and atrial fibrillation, alongside healthy volunteers.

By linking information about genes, medicines and disease, the system aims to predict which drugs might work best for particular heart conditions instead of relying only on traditional trial-and-error approaches.

Among the medicines highlighted were methotrexate, normally used for rheumatoid arthritis, and diabetes drugs known as gliptins, which the AI suggested could support some heart patients.

The model also pointed to a possible protective effect from caffeine among people with atrial fibrillation, although researchers warned that individuals should not change their caffeine intake based on the findings alone.

Scientists say the same technology could be applied to other health problems, including brain disorders and obesity.

Work is already under way to turn the knowledge graph into a patient-centred system that follows real disease pathways, with the long-term goal of enabling more personalised and better-timed treatment.

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Reddit overtakes TikTok in the UK social media race

In the UK, Reddit has quietly overtaken TikTok to become Britain’s fourth most-visited social media platform, marking a major shift in how people search for information and share opinions online.

Use of the platform among UK internet users has risen sharply over the past two years, driven strongly by younger audiences who are increasingly drawn to open discussion instead of polished influencer content.

Google’s algorithm changes have helped accelerate Reddit’s rise by prioritising forum-based conversations in search results. Partnership deals with major AI companies have reinforced visibility further, as AI tools increasingly cite Reddit threads.

Younger users in the UK appear to value unfiltered and experience-based conversations, creating strong growth across lifestyle, beauty, parenting and relationship communities, alongside major expansion in football-related discussion.

Women now make up more than half of Reddit’s UK audience, signalling a major demographic shift for a platform once associated mainly with male users. Government departments, including ministers, are also using Reddit for direct engagement through public Q&A sessions.

Tension remains part of the platform’s culture, yet company leaders argue that community moderation and voting systems help manage behaviour.

Reddit is now encouraging users to visit directly instead of arriving via search or AI summaries, positioning the platform as a human alternative to automated answers.

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Australia weighs risks and rewards of rapid AI adoption

AI is reshaping Australia’s labour market at a pace that has reignited anxiety about job security and skills. Experts say the speed and visibility of AI adoption have made its impact feel more immediate than previous technological shifts.

Since the public release of ChatGPT in late 2022, AI tools have rapidly moved from novelty to everyday workplace technology. Businesses are increasingly automating routine tasks, including through agentic AI systems that can execute workflows with limited human input.

Research from the HR Institute of Australia suggests the effects are mixed. While some entry-level roles have grown in the short term, analysts warn that clerical and administrative jobs remain highly exposed as automation expands across organisations.

Economic modelling indicates that AI could boost productivity and incomes if adoption is carefully managed, but may also cause short-term job displacement. Sectors with lower automation potential, including construction, care work, and hands-on services, are expected to absorb displaced workers.

Experts and unions say outcomes will depend on skills, policy choices, and governance. Australia’s National AI Plan aims to guide the transition, while researchers urge workers to upskill and use AI as a productivity tool rather than avoiding it.

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