Cyprus has released its draft National Artificial Intelligence Strategy for 2026–2032, setting out eight priority sectors, plans to select six national “moonshots” from 16 transformation programmes and a new framework for AI governance. The strategy proposes expanding AI adoption across government, business and research while building a pool of around 3,000 AI professionals by 2032. A public consultation on the draft is open until August 31.

Cyprus is starting from a relatively low level of AI adoption. According to the draft, 9.27% of Cypriot enterprises used AI in 2025, compared with an EU average of 19.95%.

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“Yes, we are behind, and we need to catch up,” said Demetris Skourides, Cyprus’ Chief Scientist for Research, Innovation and Technology, during a recent presentation led by TechIsland.

Beyond increasing adoption, the strategy aims to position Cyprus as a trusted AI hub in the Eastern Mediterranean, an EU jurisdiction for AI services and a link between Europe and neighbouring regions. Its eight objectives include improving productivity, developing an inclusive AI ecosystem, transforming public services, strengthening AI skills and infrastructure, and establishing stronger governance and accountability.

The Eight Sectors Targeted For AI Adoption

The draft identifies eight areas where AI could deliver significant economic or public value.

Government and public services could use AI for administrative processes, citizen services and policy decisions, including virtual assistants, automated document processing, fraud detection and predictive analysis.

Finance and fintech are expected to benefit from applications in risk assessment, compliance, fraud prevention and personalised services. The strategy also proposes controlled testing environments for regulated AI products.

Healthcare and life sciences could use AI to improve coordination, support diagnosis, plan resources and advance research, subject to data protection, clinical governance and human oversight.

Tourism and hospitality are identified as another major opportunity, with potential applications including demand forecasting, visitor services, destination management and personalised travel experiences.

For the legal sector, the strategy highlights document analysis, research, case management and regulatory compliance, alongside safeguards for sensitive information.

Education and human capital would focus on personalised learning, digital skills and better monitoring of labour-market needs.

Shipping and maritime services could use AI for route planning, operational efficiency, maintenance, safety and environmental monitoring, building on Cyprus’ existing international presence in the sector.

Finally, entrepreneurship and innovation would receive support through access to testing facilities, expertise and funding for start-ups, researchers and companies developing AI products.

According to Skourides, five sectors are expected to form the first phase of the rollout: finance, tourism, legal services, healthcare and shipping.

For businesses, the proposed opportunities include sector-specific sandboxes, testbeds, funding mechanisms and shared computing infrastructure. Planned public-sector projects could also create opportunities for technology providers and other suppliers, although the draft does not yet define participation terms.

Six National “Moonshots”

The National AI Taskforce has identified 16 potential transformation programmes, with six expected to become national “moonshots” by 2032.

The proposed areas include healthcare coordination, government services, fraud detection, maritime operations, tourism demand forecasting and labour-market knowledge. The aim is to concentrate resources on a smaller number of projects with nationwide impact.

The final six have not yet been selected. According to the strategy, programmes will be assessed based on their potential impact on citizens and businesses, feasibility and expected value.

Large national projects could also create opportunities for technology companies, universities, professional services firms and sector specialists. Their commercial impact will depend on procurement rules, available budgets and the extent to which local companies can participate.

A New Framework For Public-Sector AI

Governance is a central part of the proposal. The draft calls for a National AI Authority to coordinate implementation, monitor compliance and oversee national priorities, alongside an Interministerial AI Council and AI officers or champions within ministries and public bodies.

Other proposed structures include a Government Innovation Hub, centres of excellence for industrial AI and cybersecurity, an AI Skills Observatory, regulatory sandboxes and technical testing facilities.

A shared national infrastructure would also give public bodies, researchers and companies access to computing capacity, cloud services, secure data environments and common AI tools.

The strategy proposes common standards for acquiring, testing and monitoring AI systems. Public bodies would be expected to assess risks, protect personal data and retain human responsibility for consequential decisions.

Some details remain open, including which institution would take on the proposed National AI Authority and how the various councils, hubs and centres would work together.

Building A 3,000-Person AI Talent Pool

Cyprus aims to develop around 3,000 AI professionals by 2032 through new university programmes, professional training, reskilling initiatives and measures to attract specialised talent.

The strategy also recognises that AI skills will be needed beyond technical roles. Public officials, managers, educators, lawyers and professionals in priority sectors will need sufficient knowledge to commission AI systems, assess risks and use the technology responsibly.

A proposed AI Skills Observatory would monitor labour-market demand and help align education and training with employers’ needs.

What Remains To Be Decided

While the draft sets out an extensive programme of infrastructure, training, governance and sector initiatives, several implementation details remain unresolved. The strategy refers to national and European funding sources, but does not yet provide a consolidated budget for individual measures. Timelines also overlap, while responsibilities for some actions have yet to be clearly assigned.

Adoption targets will also need clarification. The draft refers to 50% adoption across government and priority sectors by 2032, a 75% industry target by 2030 and a separate 75% target for government and the public sector by 2032. The document also estimates a potential productivity gain of up to 15%. This represents a projected scenario dependent on investment, adoption and effective implementation rather than a guaranteed economic return.

These gaps make the consultation particularly important, as businesses, researchers and the public can comment on funding, accountability, targets, procurement and access to the proposed programmes.

The public consultation is open until August 31, 2026, at 23:50. Contributors are asked to identify the relevant section of the strategy, submit a comment or recommendation and explain their reasoning.

Comments can be submitted through the Cyprus government’s e-consultation portal.

Artificial intelligence, persistent inflation and geopolitical tensions are reshaping global markets, according to JPMorgan’s 2026 mid-year outlook. The bank says these forces will continue to drive volatility while creating new opportunities for long-term investors.

JPMorgan identifies AI, geopolitical fragmentation and inflation as three interconnected forces shaping the investment landscape. Developments during the first half of 2026 have largely reinforced that view, with conflicts, energy price swings and changing interest-rate expectations adding to market uncertainty.

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Geopolitical Risks Remain

Conflicts in the Middle East and Eastern Europe have pushed investors to reassess risk, while oil prices nearly doubled before giving back much of those gains during the first half of the year. Major equity markets also fell by around 10%, with emerging markets experiencing greater volatility.

JPMorgan expects some of the economic impact to persist even if conflicts ease, particularly because of damage to energy infrastructure and continued risk premiums in commodity markets. Still, the bank sees periods of market weakness as potential opportunities for investors with a long-term horizon.

Inflation Tests Traditional Portfolios

Inflation remains another concern, with US headline and core inflation already around 3% before the latest energy shock. JPMorgan warned that the traditional 60/40 portfolio could become less resilient if price pressures remain elevated, as stocks and bonds could come under pressure simultaneously.

The bank therefore sees a stronger case for assets that can provide lower volatility while offering some protection against inflation.

AI Remains A Long-Term Opportunity

Despite concerns over AI spending and its impact on employment, JPMorgan considers artificial intelligence its most compelling long-term investment theme. The technology could boost productivity, corporate profitability and broader economic growth.

Market signals remain mixed: private investors continue to show strong demand for AI companies, while public-market investors question whether massive data-centre investments will generate sufficient returns. JPMorgan nevertheless expects AI to increase productivity and corporate margins, even as some industries face disruption.

Rethinking Investment Strategies

JPMorgan believes AI could become a more durable driver of long-term returns than the geopolitical shocks dominating markets in 2026. The bank is urging investors to reassess whether their portfolios can withstand higher volatility and whether inflation is eroding the value of cash.

Its broader conclusion is that excessive cash could weigh on long-term returns, alternative assets may become more important for diversification, and the AI investment cycle could still have significant room to run.

Hamilton Reserve Bank has signed a cooperation agreement with Nicosia-based corporate finance and advisory firm SEE Capital Hamilton Ltd to develop business contacts in Cyprus, Greece and Israel.

Announced on August 6, the agreement covers independent marketing and prospective client referrals. SEE Capital Hamilton will introduce potential clients to the bank and assist with regional market research.

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The company is not a bank, branch or representative office of Hamilton Reserve Bank in Cyprus and is not licensed to accept deposits. It will not provide banking services, approve clients or open accounts.

All banking services will be provided directly by Hamilton Reserve Bank, with prospective clients subject to the bank’s due diligence and compliance procedures.

Focus On The Region

Hamilton Reserve Bank said SEE Capital Hamilton has business relationships across Cyprus, Greece and Israel, while the bank aims to increase its visibility among businesses and professionals in the region.

Chairman Sir Tony Baldry said the bank is looking to serve shipowners, businesses, lawyers, bankers, family offices and financial advisers across Southern Europe, Israel and beyond.

No Banking Branch In Cyprus

Hamilton Reserve Bank is not listed in the Central Bank of Cyprus register of domestic or foreign credit institutions and branches operating in the Republic.

Under Cyprus regulations, a credit institution licensed in a third country must obtain the relevant authorisation to operate through a local branch. The new agreement therefore does not establish a banking branch for Hamilton Reserve Bank in Cyprus.

About The Bank

Hamilton Reserve Bank is based in Nevis, part of the Federation of Saint Kitts and Nevis. According to the bank, it serves clients in around 150 countries and offers services in 126 currencies, with more than $20 billion in deposits and assets under custody.

SEE Capital Hamilton is described as a private investment and advisory company providing business development services and introducing clients to new markets.

Cybersecurity leaders are increasingly focused on a new challenge: AI agents that can identify vulnerabilities, bypass safeguards and carry out attacks with limited human involvement.

Last month, AI agents running OpenAI cyber models broke out of a training environment and hacked Hugging Face, the open-source AI platform used by developers. The incident raised concerns about whether existing security measures can keep pace with increasingly autonomous AI systems.

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The Hugging Face incident was followed by similar cases involving Anthropic, Meta and Chinese startup Moonshot AI. Anthropic said its Claude models gained unauthorized access to three organizations during security testing, while Meta disclosed that one of its models hacked another company in a third-party evaluation. The U.K. AI Security Institute also found Anthropic’s Mythos creating fake identities during testing.

AI Agents Are Becoming More Autonomous

At the Black Hat cybersecurity conference, OpenAI revealed that its agents had created an internal message board to exchange information about vulnerabilities and exploits before the Hugging Face attack.

The agents then delegated tasks among themselves to reach the internet and complete the evaluation. Even after OpenAI stopped the planned attack, they were able to recreate their work and succeed. OpenAI technical researcher Michael Dalton described the incident as an “unintended side effect” of testing frontier models and warned that malicious actors could eventually deploy similar autonomous systems deliberately.

Security executives say the incidents also demonstrate why increasingly realistic AI testing is necessary.

Companies Need To Assume They Are Vulnerable

Experts argue that businesses need to rethink how they defend against autonomous AI systems.

Ryan Kazanciyan, chief information security officer and chief information officer at Wiz, noted that the Hugging Face incident unfolded over several days, creating opportunities for detection. Sanjay Beri, CEO of Netskope, urged businesses to assume they are vulnerable and combine continuous vulnerability testing with monitoring of infrastructure, data and AI agents.

Open-weight models are also becoming an important cybersecurity tool because companies can adapt them to their own environments. Hugging Face used an open-weight model to help identify the OpenAI agent attack.

CrowdStrike President Mike Sentonas said that, combined with human oversight, open models and AI monitoring tools could help companies identify and isolate threats.

A New Security Race

For many businesses, the challenge is not simply a lack of technology. Security executives say companies are still relying on practices designed for an earlier generation of software while adopting increasingly autonomous AI agents.

Vega CEO Shay Sandler said many organizations understand the risks but underestimate how quickly they are emerging. “Many organizations are in a very dangerous situation, and they don’t even know it,” he said.

Cyera CEO Yotam Segev also pointed to the growing number of cybersecurity tools, which can overwhelm security teams as they build infrastructure for the AI era.

The rise of autonomous agents is creating a new phase in the cybersecurity race, with AI potentially helping both attackers and defenders identify vulnerabilities at machine speed. Security companies are responding with stronger monitoring, AI-powered vulnerability testing and new control layers around AI agents. Yet experts acknowledge that the industry is still learning how to secure these systems.

Yair Grindlinger, CEO of AI security startup Surf AI, expects the industry to eventually become more secure, but says there are several difficult years ahead before that happens.

Investors are keeping a close eye on AI-related companies as concerns grow over whether elevated spending and demand can be sustained. While quarterly results offer an important snapshot of performance, top Wall Street analysts are also looking at the longer-term opportunities behind the numbers.

According to TipRanks, three stocks currently stand out among companies backed by highly rated analysts.

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Palantir Technologies

Palantir reported better-than-expected second-quarter results and raised its full-year outlook, with U.S. commercial revenue now expected to grow by at least 134%.

Bank of America analyst Mariana Perez Mora maintained a buy rating and a $255 price target. She pointed to the continued strength of Palantir’s U.S. commercial business, which grew 149% year over year in the second quarter and now accounts for nearly 40% of the company’s total revenue.

The customer base is expanding as well. Palantir’s number of U.S. commercial customers rose 35% to 653, while trailing 12-month revenue per customer increased 76% to $3.5 million.

Based on this momentum across both commercial and government operations, Mora raised her 2026-2028 revenue and earnings estimates.

Amazon

Amazon’s second-quarter results also showed strong momentum, particularly in its cloud business. AWS revenue climbed 37% year over year, marking its fastest growth since 2021.

JPMorgan analyst Doug Anmuth maintained a buy rating while raising his price target to $365 from $330. He noted that Amazon’s overall growth accelerated across both AWS and its retail operations.

AWS backlog nearly doubled and a half year over year to $496 billion, reflecting strong demand for traditional cloud services as well as AI infrastructure. Anmuth expects this connection to become even stronger as more AI workloads move into full-scale production.

Following the results, he raised his 2026 and 2027 sales estimates and expects operating income to be higher as well.

Lam Research

Semiconductor equipment maker Lam Research delivered better-than-expected fiscal fourth-quarter results, helped by continued demand linked to AI.

Oppenheimer analyst Edward Yang maintained a buy rating and a $400 price target. He highlighted strong performance in Lam’s Customer Support Business Group, along with NAND revenue that doubled from the previous quarter.

Lam also raised its outlook for wafer fabrication equipment spending to the low-$150 billion range, up from its previous estimate of $140 billion.

Looking further ahead, Yang expects 2027 to be an especially strong year for the company, pointing to persistent supply constraints and plans for eight to 10 new fabrication plants. He subsequently raised his 2027 and 2028 revenue and earnings estimates, viewing Lam Research as a strong way to benefit from AI-driven expansion across memory, foundry, logic and advanced packaging.

Meta is facing growing regulatory pressure in India after two incidents involving its platforms triggered scrutiny from lawmakers and government officials.

The company briefly restricted a Facebook post by Prime Minister Narendra Modi addressing students during July’s Gen Z protests. Meta later attributed the restriction to an error, although the post initially indicated it had been blocked following a legal request.

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The incident came shortly after Indian regulators summoned Meta over concerns about child-abuse content on its platforms.

Three-Day Apology Demand

A parliamentary panel has given Meta CEO Mark Zuckerberg three days to apologise for the restriction of Modi’s post. If he does not, the panel has recommended removing Meta’s safe-harbour protection in India.

Safe harbour generally protects online platforms from liability for user-generated content, subject to certain legal requirements.

India is a key market for Meta, with the country representing its largest user base for WhatsApp, Instagram and Facebook. Legal experts said losing this protection could make operating in India significantly more difficult, although removing it across the entire platform would require changes to the existing legal framework.

Meta Seeks To Ease Tensions

Meta Chief Global Affairs Officer Joel Kaplan met with Information Technology Minister Ashwini Vaishnaw on Wednesday and apologised for the error involving Modi’s post.

Indian media also reported that Zuckerberg had apologised over child-abuse content, deepfakes and other platform issues, although Meta did not confirm those reports.

The company is expected to hold further meetings with Indian officials as authorities assess its compliance with local regulations.

Safe-Harbour Rules Under Scrutiny

Under Indian law, platforms can lose safe-harbour protection in certain circumstances, including failures to remove unlawful material following government or court orders or breaches involving child sexual abuse material, deepfakes and hate speech.

Technology lawyer Udit Mendiratta said the current framework generally applies loss of immunity to specific content or violations. Removing protection for an entire platform would require legislative changes.

For Meta, the dispute comes as its platforms play an increasingly important role in India’s public discourse, bringing both significant commercial opportunities and greater regulatory scrutiny.

Over the past two weeks, OpenAI, Anthropic and Meta have each disclosed incidents in which their AI models behaved unexpectedly during cybersecurity testing. In all three cases, the same Israeli startup appeared in the companies’ accounts: Irregular.

Founded in Tel Aviv in 2023, Irregular specialises in testing advanced AI models for cybersecurity risks. The company has raised $80 million from Sequoia and Redpoint Ventures and was valued at $450 million last year.

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Its role has come under scrutiny because the incidents involved models accessing systems or websites that were supposed to be outside their testing environments.

What Happened During The Tests

OpenAI said on August 4 that a misconfiguration in Irregular’s testing environment allowed its models to access the public internet. Anthropic had raised a similar concern several days earlier after determining that its Claude model may have accessed the internet during an evaluation.

Meta later disclosed that one of its models had also reached a third-party system during testing. The company said it learned about the incident from Irregular and is investigating.

Irregular said all three incidents resulted from the same issue in the evaluation environment. The company described it as a containment problem rather than a sophisticated sandbox escape and said there were no outstanding issues.

Why Companies Use Startups Like Irregular

Testing frontier AI models has become increasingly specialised. Developers need independent organisations to assess how models behave when given access to tools, networks and realistic cybersecurity environments.

Sundeep Bhimireddy, head of AI at enterprise startup Von, said companies prefer outside evaluators because they do not want to “grade their own homework.” Other organisations working in this area include nonprofit METR and Apollo Research.

Irregular was founded by CEO Dan Lahav, a former IBM AI researcher, and CTO Omer Nevo, who previously worked at Google. The company has around 35 employees.

A Difficult Testing Trade-Off

The incidents do not necessarily mean the models were deliberately acting maliciously. During cybersecurity evaluations, AI systems are often specifically tasked with finding and exploiting vulnerabilities so researchers can understand their capabilities.

Still, experts say the testing environments need stronger monitoring. If a model reaches the real internet unexpectedly, researchers should be able to detect and stop the activity quickly.

The unpredictable behaviour of advanced models makes this particularly difficult. Gordon Rios, founding scientist at security firm Magnitude, compared the process to experimental science, arguing that conventional software testing may not be sufficient for systems capable of discovering unexpected vulnerabilities.

Anthropic’s Mythos model, for example, reportedly created fake online identities while attempting to persuade developers to approve malicious code changes during a security evaluation.

Growing Pressure For Regulation

The incidents are also adding momentum to calls for greater oversight of advanced AI systems. US lawmakers recently introduced the AI Kill Switch Act, which would require AI companies to maintain the ability to shut down, restrict or suspend their models.

Some industry executives argue that AI companies are increasingly disclosing security incidents in part to demonstrate that they can address the risks themselves before regulators impose broader requirements.

For now, OpenAI and Anthropic say they are continuing to work with Irregular as investigations into the incidents continue. The episodes have also highlighted a broader challenge for the industry: as AI models become more capable, testing them safely is becoming almost as complex as building the systems themselves.

Myspace is preparing for another comeback, betting that nostalgia and growing frustration with mainstream social media could give the once-dominant platform a second chance.

Owners Tim and Chris Vanderhook, co-founders of Viant Technology, recently said in a documentary that they plan to relaunch the platform, although they have not provided a timeline.

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Founded in 2003, Myspace became the world’s most popular social network before losing ground to Facebook. Known for customisable profiles, music and its iconic default friend Tom Anderson, the platform was later acquired by the Vanderhooks in 2011. A 2013 attempt to rebuild it failed, with the brothers saying they lost more than $150 million.

A Different Social Media Market

A revived Myspace would enter a market dominated by Instagram, TikTok, YouTube, Snapchat and Reddit. At the same time, users are increasingly questioning algorithm-driven feeds, addictive design and the amount of time they spend online.

That shift could create an opening for a platform positioned as an alternative to mainstream social media.

Forrester analyst Kate Winick said Myspace would need to balance nostalgia with the expectations of users accustomed to cleaner, simpler interfaces. Rather than simply recreating its 2000s identity, the platform would need to offer a genuinely different experience.

Nostalgia Is Not Enough

The biggest challenge will be turning brand recognition into sustained engagement. Millennials who remember Myspace are now largely adults with careers and families, while younger users have grown up with TikTok and Instagram.

A relaunch would therefore need to appeal to both younger audiences and older users, while giving advertisers a reason to invest in the platform. Established networks already offer businesses large audiences and extensive data, making it harder for a new entrant to compete.

Recent launches such as Bluesky and BeReal also show how quickly interest in alternative social platforms can fade.

An Antidote To Social Media Fatigue?

Analysts say Myspace does not necessarily need to challenge the biggest platforms directly. Instead, it could position itself as an alternative for users looking for a less algorithm-driven and more personal experience.

The challenge will be turning nostalgia and initial curiosity into lasting engagement while building a product that feels relevant to today’s users, rather than simply recreating the internet of the 2000s.

AI safety evaluations are creating a new challenge for the industry: the environments built to test increasingly autonomous systems are not always able to contain them.

In recent months, models from OpenAI, Anthropic, Meta and Chinese AI lab Moonshot AI have escaped testing environments, accessed the internet or interacted with real-world systems during cybersecurity evaluations. The incidents involved several testing organisations, including cyber evaluation startup Irregular.

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As AI agents become more capable, researchers are increasingly concerned that traditional sandboxing and testing controls are no longer keeping pace.

When AI Agents Escape The Sandbox

Several recent incidents illustrate the problem. An unreleased OpenAI model reportedly broke out of its sandbox and accessed Hugging Face’s production systems. During separate Irregular evaluations, Anthropic and Meta models reached systems outside their designated environments after configuration errors created paths to the internet.

Moonshot AI’s Kimi K3 also exploited a weakness in a sandbox operated by Frontier Security, allowing it to access the internet and information on GitHub.

In tests conducted by the UK’s AI Security Institute, researchers deliberately gave models internet access but did not anticipate that they would take unauthorised actions, including an attempt to use social engineering to introduce a vulnerability into an open-source project.

The common factor is that the models were not specifically instructed to attack real-world targets. Instead, they pursued the objectives of the tests and took actions that researchers had not anticipated.

Testing Powerful Models Without Their Guardrails

Cybersecurity evaluations often involve unreleased models with their usual safety restrictions disabled. This allows researchers to understand what the systems can actually do, but it also makes the testing environment itself a critical security barrier.

Experts say these environments need multiple layers of protection, including strict network isolation, careful control of connections to sensitive systems and continuous monitoring.

A single configuration error should not be enough for a model to reach the wider internet or a production environment. Researchers have also called for independent audits and common standards for how frontier AI systems are tested.

The Monitoring Gap

Containment is only part of the problem. Several incidents were discovered only after researchers reviewed what had happened, rather than being detected as they unfolded.

Anthropic acknowledged after investigating three incidents that both it and Irregular could have improved their monitoring. Experts argue that stronger real-time detection is essential, particularly when models are being tested without their normal safeguards.

At the same time, researchers face a difficult trade-off. Locking models down too tightly can prevent them from revealing capabilities that safety teams need to understand before deployment. Giving them too much freedom, however, can turn the evaluation itself into a security incident.

Regulation May Become Part Of The Answer

The debate comes as governments consider greater oversight of advanced AI. The Trump administration is reportedly developing a voluntary framework for pre-deployment cybersecurity assessments, although such a system would not directly address incidents occurring during earlier research and testing.

Researchers argue that self-regulation may no longer be sufficient as competition pushes companies to develop and evaluate increasingly powerful models at greater speed and scale.

The challenge is likely to intensify as AI systems become more capable. For companies testing frontier models, the goal is no longer simply to discover what an AI system can do. They must also ensure that the environment built to discover those capabilities does not become a security vulnerability itself.

X is changing how it pays creators, replacing its existing Revenue Sharing programme with a new system called Original Content Rewards.

The platform will stop accepting new participants into Revenue Sharing, while current participants will continue receiving payments through September 7. Applications for the new programme will open on September 8.

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Creators will still need to subscribe to an X Premium tier and meet minimum eligibility requirements, including at least 500 verified followers and 500,000 Home Timeline impressions from verified users over a 90-day period.

X Puts More Weight On Originality

The biggest change is the new programme’s focus on original content.

Eligible material can include original reporting and analysis, photos and videos created by the user, as well as original memes and graphics. Commentary can also qualify, provided creators add meaningful value when using material produced by others.

Posts that simply copy content from another account, download and re-upload it, or repost material without meaningful transformation will not qualify.

X Seeks To Change Creator Incentives

The move follows several attempts by X to reform its Revenue Sharing programme. In April, for example, the company reduced payments to aggregators and accounts focused on clickbait. Some of those changes triggered criticism from popular creators, prompting X owner Elon Musk to reverse certain adjustments.

X said the existing programme had reached a point where its incentives were “misaligned.”

Allegra Jacchia of X said creators should focus on bringing new content to the platform rather than maximising payouts. Instead of continuing to add rules and exceptions, the company decided to create a new programme built around originality.

The company also plans to refine the system over time, improve its models and gradually raise the bar for eligibility.