• Gartner predicts that around 33% of people laid off due to AI could be rehired by 2029
• Those rehired employees, presumably filling similar roles, will command higher salaries
• Further predictions point to 75% of organizations making cost savings from AI productivity being overtaken by competing companies with a stronger modernizing philosophy

People laid off from their roles due to a corporate refocusing on AI could soon find themselves rehired – or at least, their former roles being advertised, new Gartner research has claimed.

It predicts that by 2027, 75% of organizations who expected to make cost savings by focusing on AI productivity over human endeavor will be overtaken by companies who reinvested those savings in modernization and training.

Social media plays a significant, multifaceted role in adolescents’ development, influencing how they communicate, learn, socialize, and express themselves.

The benefits, however, are accompanied by risks that can undermine youngsters’ character as well as their cognitive and social development.

The potential problems include excessive screen time, social media addiction, cyberbullying, misinformation, radicalization, privacy violations, exposure to inappropriate content, sextortion, and doomscrolling.

A recent study published in Nature: Human Behaviour found that adolescents who begin using social media at an early age tend to have significantly lower academic performance. A Mashable article highlights additional issues including effects on mental health, self-harm, addiction to social media, compulsive, repetitive checking, and exposure to pornography and violent material.

Protecting minors has largely fallen to parents, schools, and self-regulation by some social media providers.

But that approach has proven ineffective and inadequate, so some governments and policymakers have stepped in and placed responsibility on social media providers.

Australia’s nationwide ban

Australia was the first country to legislate a nationwide social media ban on children younger than 16—which I wrote about in January for Communications of the ACM.

Enacted in December, the ban initially applied to 10 platforms: Facebook, Instagram, Kick, Reddit, Snapchat, Threads, TikTok, Twitch, X, and YouTube. It excluded messaging, gaming, and nonsocial platforms including Discord, GitHub, Roblox, WhatsApp, YouTube Kids, and educational tools.

The law places the responsibility for enforcement on the platform providers through age-assurance mechanisms, requiring the platforms to take “reasonable steps” to prevent those 15 or younger from creating or holding accounts.

It does not, however, apply to content consumption. Children can view publicly available posts and videos without logging in; they cannot comment or post, according to the law.

The legislation mandates that the user’s age be verified with tools such as government-issued identification, biometric or facial age-estimation tools, behavioral or inference algorithms, and self-declaration with optional checks.

Penalties for noncompliance can reach US $35.6 million.

The 10 platforms subsequently removed nearly 5 million accounts of young users.

Although the ban received widespread support, human rights organizations and digital freedom advisory groups have argued that it limits young people’s freedom of expression and access to useful information. They say the ban might contribute to social isolation and the loss of support networks, particularly among marginalized youth.

Promising early outcomes

The Australian ban is producing positive outcomes, according to a recent Time magazine article, “What the World Should Learn From Australia’s Social Media Law.”

Early findings indicate it has reduced account ownership and social media use among young children. A YouGov survey of Australians found that 61 percent of parents of children age 16 and younger reported positive changes including more face-to-face interaction, greater presence and engagement, and improved parent-child relationships. Three in five Australians surveyed called the ban effective.

The ban has encouraged social media platforms to reconsider their features. Snapchat is moving toward a friends-only experience for 13- to 15-year-olds, for example.

The law is stimulating the development of purpose-built online spaces for children younger than 16 that can support their developmental needs, offering alternatives to mainstream social media.

The longer-term impact could be more significant if “no social media account before age 16” becomes an accepted norm, making it easier for parents and schools to support delayed social media use.

Implementation struggles

Despite the early encouraging outcomes, one study found that online platforms struggle to implement age checks. Many under-16 users in Australia have continued to access platforms with little difficulty, the study said. They children have found workarounds to subvert restrictions, such as using a free VPN to bypass age checks—some of which have questionable data-collection practices.

Seven in 10 children retained their existing accounts on restricted platforms, the study found. Other teens created new accounts using incorrect age information. Some were incentivized to seek unregulated offshore platforms not subject to Australia’s law.

The workarounds prompted Australia to double the maximum fine and warn of court action against tech giants for noncompliance.

Emphasis on age verification

A number of other countries are implementing or considering social media restrictions. They include Brazil, Canada, France, Greece, Indonesia, Norway, Poland, Thailand, Türkiye, and the United Kingdom. The European Union is contemplating its own restrictions.

The countries’ mandates for age verification or age assurance shift the policy focus from whether to verify age to how to do so effectively while protecting user privacy.

An article on think tank New America’s website, “Age Assurance and Verification,” describes some methods:

• Age gating and screening. Users self-attest their age by checking a box or inputting a birth date.
• Age estimation. Several techniques are available, including profiling the user’s online activity and scanning the user’s face.
• Age verification. One way is providing a government-issued identification document. Other approaches include digital identity systems, digital wallets, and third-party verification.

Reliable age verification is technically challenging and raises privacy concerns, as outlined in “The Age-Verification Trap,” written by Cinderpoint consultant Waydell D. Carvalho and published in February in IEEE Spectrum. Carvallo says platforms need to balance age verification with protecting users’ personal information.

IEEE’s contributions

IEEE is working on initiatives to provide a safer online environment for children. To help developers build age-appropriate social media platforms and websites, the IEEE Standards Association (IEEE SA) has published two guidelines.

The IEEE Standard for Online Age Verification (IEEE 2089.1-2024) provides a framework for designing, specifying, evaluating, and deploying verification systems. The standard includes requirements for privacy protection, data security, and information management specific to the age-assurance process. It also provides procedures for verifying a user’s age or age range with a high degree of accuracy.

Based on the 5Rights Foundation’s Principles for Children, the other standard (IEEE 2089-2021) provides practical steps to qualify online products and services for children. It requires systems to present information in an age-appropriate way and to uphold the rights established for youngsters in the U.N. Convention on the Rights of the Child.

IEEE SA also offers an online age-verification-certification program, which assesses systems for compliance with the IEEE 2089.1 standard. The program certifies that organizations implement robust processes before granting access to age-restricted products and services, prioritizing children’s safety, privacy, autonomy, and rights.

As outlined in The Institute article “IEEE Makes Strides to Improve Online Safety for Kids,” certification is based on six key indicators: accuracy, frequency of assurance, counter-fraud measures, authenticity, frequency of authenticity checks, and birth date confidence.

Indonesia used key provisions from the two IEEE guidelines to inform its child-protection regulation, which was signed into law last year.

IEEE’s ethically aligned design framework prioritizes human well-being, transparency, accountability, privacy, and protecting vulnerable populations including children.

Calls for platform reforms

Although social media bans would be globally significant policy responses, deeper structural issues remain largely unaddressed. Platform architecture and features contribute to social media harm.

The focus needs to shift from constraints on account provisioning and content moderation to safer platform design.

Meta in August agreed to pay $17.1 billion to settle a lawsuit brought by U.S. states. The suit said Meta designed its social media to be addictive to children, and the company concealed internal research showing Instagram’s addictive effects on teenagers. As part of the settlement, Meta agreed to implement child-safety measures such as setting daily time limits and disabling Facebook and Instagram push notifications during school hours.

The company still faces other lawsuits that could have far-reaching implications, pressuring other tech companies to design safer social media platforms.

Architecture-driven features such as infinite scrolling, algorithmic recommendations, addictive platform design, data-driven engagement, and personalized advertising to minors are other contributing factors to social media addiction.

IEEE Senior Member Katina Michael, professor at the University of Sydney business school and founding editor in chief of IEEE Transactions on Technology and Society, shared her perspective: “Social media bans may offer a short-term response to growing concerns, but they are not a long-term solution,” she says. “IEEE 2089.1-2024 advocates for socio-technical systems that are designed to promote human well-being, safety, and flourishing. Rather than relying on prohibition alone, we should focus on better design, building digital platforms that embed ethics, accountability, transparency, and human values from the outset.”

Collective responsibility

Protecting children online would require a combination of policy measures, improved platform design, digital literacy, parental involvement, and cultural change.

Building a safe, secure, and inclusive digital ecosystem that supports adolescents’ cognitive, social, and emotional development would require collaboration among technology companies, platform providers, content creators, parents, educators, policymakers, and young people themselves.

Professional organizations such as IEEE can continue contributing through standards development, education, certification while promoting trustworthy and responsible digital technologies.

Grand View Research puts the enterprise agentic AI market at $24.5 billion by 2030.

On the other hand, MarketsandMarkets estimates the AI agents’ market size at $52.62 billion over the same horizon.

Both start from a mid-single-digit-billion base and both land on a compound growth rate near 46%. When two credible forecasters agree that closely on the slope and differ by more than a factor of two on the destination, the interesting information is in what each of them is counting.

The Forecasts Agree on the Slope and Not on the Size

A forecast range is a decent proxy for how well a category has been defined, and agentic AI is currently defined differently by everyone measuring it.

Grand View Research tracks enterprise deployment specifically. The firm projects this enterprise deployment’s growth from $2.6 billion in 2024 to $24.5 billion by 2030 at a 46.2% compound rate. MarketsandMarkets draws a wider boundary around agent software generally that runs from $5.26 billion in 2024 to $52.62 billion in four years at 46.3%. Same six years, near-identical growth rate, two different universes.

Convergence on the rate is the stronger signal. Absolute market sizes are hostage to definitions, while growth rates tend to survive them.

Whether shared infrastructure genuinely removes rebuild cost is testable, and the test is uncomfortable for the category. If the claim holds, the share of agent budgets going into integration work should be falling. Most evidence on enterprise deployment points the other way.

Where the Spend Actually Lands

Follow agent budgets and they break into four layers: data, execution, identity and payments. Only one of them has a settled standard.

Gartner produces the largest figures in circulation on the demand side. It projects that machine customers will control roughly $30 trillion of purchases by 2030, with AI agents commanding $15 trillion in business-to-business purchases as soon as 2028. McKinsey’s narrower estimate, covering consumer commerce mediated by agents, lands between $3 trillion and $5 trillion by 2030.

The supply side looks less like new money than money changing hands. Gartner puts $234 billion of enterprise application software spend at risk from agentic AI, which describes displacement rather than creation.

Payments is where finance enters. Stripe and Tempo launched the Machine Payments Protocol in March 2026 with more than 100 integrated services, Mastercard shipped Agent Pay for Machines in June, and Coinbase contributed x402 to the Linux Foundation in April. Four standards, four sets of incumbents, no consolidation.

Market venues took the opposite route. Binance exposed market data and trading to compliant agents through an MCP endpoint on August 20, 2026 rather than building a proprietary connector, a bet that the connection layer is now commodity infrastructure and the competition happens elsewhere.

“AI agents are becoming another way people interact with financial markets, but they need the same reliable data, infrastructure and controls that users and developers expect today,” says Jeff Li, VP of Product at Binance. “That makes it easier to create AI-driven financial applications without having to recreate the underlying infrastructure each time.”

Whether shared infrastructure genuinely removes rebuild cost is testable, and the test is uncomfortable for the category. If the claim holds, the share of agent budgets going into integration work should be falling. Most evidence on enterprise deployment points the other way.

The Adoption Curve Measures Intent, Not Deployment

The protocol numbers are the most current data the category has and they are easy to misread.

Anthropic counted more than 10,000 active public MCP servers in December 2025 and roughly 97 million monthly software development kit downloads by March 2026 against about 100,000 in the month of launch. A May census found 15,926 repositories carrying the mcp-server topic on GitHub. In contrast, 9,652 latest-version records sat in the official registry.

Then the correction. Stacklok’s 2026 survey of senior technical leaders found 29% of software organizations running MCP in limited production and 12% in broad production, so roughly 41% in production of any kind, with security ranked as the leading barrier ahead of cost and legacy integration complexity.

That security concern is documented rather than speculative. Only 8.5% of MCP servers implement the OAuth 2.1 standard the specification makes mandatory for remote deployments, and 53% expose credentials through hard-coded configuration values.

Downloads and repository counts measure how many engineers tried something. Production deployments measure how many finished, and the distance between those two numbers is the category’s actual maturity. A widely circulated claim of 78% enterprise production adoption was later withdrawn by the team that published estimates in that range.

The Same Analysts Are Forecasting the Failures

The firms producing the growth curves are also producing the attrition numbers, which is the most useful thing about them.

Gartner predicts that more than 40% of agentic AI projects will be canceled by the end of 2027 on escalating costs, unclear business value or inadequate risk controls. It also estimates that of the thousands of vendors describing themselves as agentic, only around 130 are real, with the rest rebranding assistants, robotic process automation and chatbots.

The payments layer carries a matching caution. Chainalysis recorded more than 100 million cumulative x402 transactions on Base across three quarters as of the first quarter of 2026, while noting that much of that growth came from memecoin farming and that mass adoption remains distant. CoinDesk reported in March 2026, citing Artemis, that daily volume on the protocol was running near $28,000 across roughly 131,000 transactions, an average payment of about $0.20, and that roughly half of observed transactions appeared to be self-dealing or wash trading.

Both readings can be true at once. A standard can be settled, well engineered and adopted by the largest platforms in software, and still be waiting for the demand that justifies the build.

The Number Worth Watching

The forecasts describe a destination and the field data describes a starting line, and the two sit further apart than the headline figures suggest.

What settles the argument is not download growth or registry entries. It is the share of deployments that survive their first budget review, and that number will not be published for another year.