ai

The AI terms that shaped debate and disruption in 2025

AI continued to dominate public debate in 2025, not only through new products and investment rounds, but also through a rapidly evolving vocabulary that captured both promise and unease.

From ambitious visions of superintelligence to cultural shorthand like ‘slop’, language became a lens through which society processed another turbulent year for AI.

Several terms reflected the industry’s technical ambitions. Concepts such as superintelligence, reasoning models, world models and physical intelligence pointed to efforts to push AI beyond text generation towards deeper problem-solving and real-world interaction.

Developments by companies including Meta, OpenAI, DeepSeek and Google DeepMind reinforced the sense that scale, efficiency and new training approaches are now competing pathways to progress, rather than sheer computing power alone.

Other expressions highlighted growing social and economic tensions. Words like hyperscalers, bubble and distillation entered mainstream debate as data centres expanded, valuations rose, and cheaper model-building methods disrupted established players.

At the same time, legal and ethical debates intensified around fair use, chatbot behaviour and the psychological impact of prolonged AI interaction, underscoring the gap between innovation speed and regulatory clarity.

Cultural reactions also influenced the development of the AI lexicon. Terms such as vibe coding, agentic and sycophancy revealed how generative systems are reshaping work, creativity and user trust, while ‘slop’ emerged as a blunt critique of low-quality, AI-generated content flooding online spaces.

Together, these phrases chart a year in which AI moved further into everyday life, leaving society to wrestle with what should be encouraged, controlled or questioned.

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How AI in 2026 will transform management roles and organisational design

In 2026, AI will transform management structures and automate tasks as companies strive to demonstrate real value. By 2026, AI is expected to move beyond experimentation and pilot projects and begin reshaping how companies are actually run.

According to researchers and professors at IMD, the focus will shift from testing AI tools to redesigning organisational structures, decision-making processes, and management roles themselves. After several years of hype-driven investment, many companies are now under pressure to show clear returns from AI.

Those that remain stuck in proof-of-concept mode risk falling behind competitors who are willing to make more significant operational changes. Several corporate functions are set to become AI native by the end of the year.

Human roles in these areas will focus more on interpersonal judgement, oversight and complex decision-making, while software forms the operational backbone. Workforce structures are also likely to change. Middle management roles are expected to shrink gradually as AI systems take over reporting, forecasting and coordination tasks.

At the same time, risks associated with AI are growing. Highly realistic synthetic media is expected to fuel a rise in misinformation, exposing organisations to reputational and governance challenges. To respond, companies will need faster monitoring systems, clearer crisis-response protocols and closer cooperation with digital platforms to counter fabricated content.

Economic uncertainty is adding further pressure. Organisations that remain stuck in pilot mode may be forced to scale back, while those committing to bigger operational change are expected to gain an advantage.

Operational areas are expected to deliver the highest returns on investment. Supply chains, core operations and internal processes are expected to outperform customer-facing applications in efficiency, resilience and cost reduction.

As a result, chief operating officers may emerge as the most influential leaders of AI within executive teams. Ultimately, by 2026, competitive advantage will depend less on whether a company uses advanced AI and more on how deliberately it integrates these systems into everyday decision-making, roles, and organisational structures.

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MIT-IBM researchers improve large language models with PaTH Attention

Researchers at MIT and the MIT-IBM Watson AI Lab have introduced a new attention mechanism designed to enhance the capabilities of large language models (LLMs) in tracking state and reasoning across long texts.

Unlike traditional positional encoding methods, the PaTH Attention system adapts to the content of words, enabling models to follow complex sequences more effectively.

PaTH Attention models sequences through data-dependent transformations, allowing LLMs to track how meaning changes between words instead of relying solely on relative distance.

The approach improves performance on long-context reasoning, multi-step recall, and language modelling benchmarks, all while remaining computationally efficient and compatible with GPUs.

Tests demonstrated consistent gains in perplexity and content-awareness compared with conventional methods. The team combined PaTH Attention with FoX to down-weight less relevant information, improving reasoning and long-sequence understanding.

According to senior author Yoon Kim, these advances represent the next step in developing general-purpose building blocks for AI, combining expressivity, scalability, and efficiency for broader applications in structured domains such as biology.

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IMF calls for stronger AI regulation in global securities markets

Regulators worldwide are being urged to adopt stronger oversight frameworks for AI in capital markets after an IMF technical note warned that rapid AI adoption could reshape securities trading while increasing systemic risk.

AI brings major efficiency gains in asset management and high-frequency trading instead of slower, human-led processes, yet opacity, market volatility, cyber threats and model concentration remain significant concerns.

The IMF warns that AI could create powerful data oligopolies where only a few firms can train the strongest models, while autonomous trading agents may unintentionally collude by widening spreads without explicit coordination.

Retail investors also face rising exposure to AI washing, where financial firms exaggerate or misrepresent AI capability, making transparency, accountability and human-in-the-loop review essential safeguards.

Supervisory authorities are encouraged to scale their own AI capacity through SupTech tools for automated surveillance and social-media sentiment monitoring.

The note highlights India as a key case study, given the dominance of algorithmic trading and SEBI’s early reporting requirements for AI and machine learning. The IMF also points to the National Stock Exchange’s use of AI in fraud detection as an emerging-market model for resilient monitoring infrastructure.

The report underlines the need for regulators to prepare for AI-driven market shocks, strengthen governance obligations on regulated entities and build specialist teams capable of understanding model risk instead of reacting only after misconduct or misinformation harms investors.

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Drones and AI take over Christmas tree farms

Across Christmas tree farms, drones and AI are beginning to replace manual counting and field inspections.

Growers in Denmark and North Carolina are now mapping plantations using AI-driven image analysis instead of relying on workers walking the fields for days.

Systems can recognise and measure each tree, give it a digital ID and track health and growth over time, helping farmers plan harvests and sales more accurately.

The technology is proving particularly valuable in large or difficult terrain. Some plantations in North Carolina sit on steep slopes where machinery and people face higher risks, so farmers are turning to laser-scanning drones and heavy-duty robotic mowers instead of traditional equipment.

Experts say the move saves time, improves safety and reduces labour needs, while accuracy rates can reach as high as 98 percent.

Adoption still depends on cost, aviation rules and staff training, so smaller farms may struggle to keep pace. Yet interest continues to rise as equipment becomes cheaper and growers grow more comfortable with digital tools.

Many industry specialists now see AI-enabled drones as everyday agricultural equipment rather than experimental gadgets.

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AI disruption risk seen as lower for India’s white-collar jobs

India faces a lower risk of AI-driven disruption to white-collar jobs than Western economies, IT Secretary S Krishnan said. A smaller share of cognitive roles and strong STEM employment reduce near-term impact.

Rather than replacing workers, artificial intelligence is expected to create jobs through sector-specific applications. Development and deployment of these systems will require many trained professionals.

Human oversight will remain essential as issues such as AI hallucinations limit full automation of cognitive tasks. Productivity gains are expected to support, rather than eliminate, knowledge-based work.

India is positioning itself as a global contributor to applied artificial intelligence solutions. Indigenous AI models under development are expected to support jobs, innovation and long-term economic growth.

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Indian banks turn to AI for revenue growth

Indian banks and financial institutions are deploying AI at scale to increase revenue generation. Post-pandemic digitisation has accelerated adoption beyond pilot projects.

Executives say AI deployment now focuses on customer engagement, credit decisions and risk management. Indian revenue growth is replacing cost reduction as the primary objective.

Industry leaders highlight a shift towards agentic AI, where autonomous systems perform complex business tasks. Banking workflows are increasingly handled with minimal human intervention.

Cloud providers say Indian finance is entering a mature AI phase. Digital infrastructure investments are expected to deepen competitive advantage across the sector.

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India to showcase local AI apps at impact summit

India’s technology ministry plans to showcase more than 100 homegrown applications at an upcoming AI Impact Summit. The event aims to highlight locally developed tools across public services and industry.

Officials say the initiative supports domestic innovation while reducing reliance on foreign technology platforms. Priority areas include governance, healthcare, education and small business productivity.

The ministry intends to promote practical AI adoption rather than experimental research. Developers will demonstrate solutions already deployed or nearing commercial readiness.

The showcase reflects India’s broader strategy to position local firms within global AI supply chains. Indian policymakers view applied AI as central to economic growth.

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AI-generated Jesuses spark concern over faith and bias

AI chatbots modelled on Jesus are becoming increasingly popular over Christmas, offering companionship or faith guidance to people who may feel emotionally vulnerable during the holidays.

Several platforms, including Character.AI, Talkie.AI and Text With Jesus, now host simulations claiming to answer questions in the voice of Jesus Christ.

Experts warn that such tools could gradually reshape religious belief and practice. Training data is controlled by a handful of technology firms, which means AI systems may produce homogenised and biased interpretations instead of reflecting the diversity of real-world faith communities.

Users who are young or unfamiliar with AI may also struggle to judge the accuracy or intent behind the answers they receive.

Researchers say AI chatbots are currently used as a supplement rather than a replacement for religious teaching.

However, concern remains that people may begin to rely on AI for spiritual reassurance during sensitive moments. Scholars recommend limiting use over the holidays and prioritising conversations with family, friends or trusted religious leaders instead of seeking emotional comfort from a chatbot.

Experts also urge users to reflect carefully on who designs these systems and why. Fact-checking answers and grounding faith in recognised sources may help reduce the risk of distortion as AI plays a growing role in people’s daily lives.

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Italy orders Meta to lift WhatsApp AI restrictions

Italy’s competition authority has ordered Meta to halt restrictions limiting rival AI chatbots on WhatsApp. Regulators say the measures may distort competition as Meta integrates its own AI services.

The Italian watchdog argues Meta’s conduct risks restricting market access and slowing technical development. Officials warned that continued enforcement could cause lasting harm to competition and consumer choice.

Meta rejected the ruling and confirmed plans to appeal, calling the decision unfounded. The company stated that WhatsApp Business was never intended to serve as a distribution platform for AI services.

The case forms part of a broader European push to scrutinise dominant tech firms. Regulators are increasingly focused on the integration of AI across platforms with entrenched market power.

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