Have We Reached Peak Human Intelligence?

As a global average, has Human Intelligence already peaked? 

For more than a century, every generation has outperformed the last on standardised tests of literacy, numeracy and general reasoning. That upward curve is one of the quiet success stories of modern schooling. Now, however, a growing body of evidence suggests the trend has stalled and, in some places, reversed. How worried should we (society) be?

In written testimony to the US Senate this year, neuroscientist Dr Jared Cooney Horvath argued that Gen Z may be the first modern generation to underperform their parents on “basically every cognitive measure we have”, including attention, memory, literacy, numeracy and executive function.  

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Horvath links that shift to a simple timing problem. Around 2010, school systems across the developed world went all in on laptops, tablets and SaaS. At the same time, teenagers’ out-of-school lives moved onto smartphones and social apps. Since then, he argues, cognitive scores have flatlined or fallen, even as time in formal education has risen.  

The claim is provocative, and not all researchers accept “Gen Z is dumber” headlines as settled science. But it sits on top of more mainstream trend lines that are getting hard to ignore. 

What the data actually shows about falling scores 

Several large assessment programmes tell a similar story. 

In the United States, the National Assessment of Educational Progress (NAEP) long-term trend data for nine-year-olds showed a 5-point drop in reading and 7-point drop in maths between 2020 and 2022. It was the largest reading decline since 1990 and the first ever decline in maths since the assessment began in the 1970s.  

By 2024, US twelfth-grade students recorded their lowest scores on national reading and maths tests in decades. Only around one in five were proficient in maths and about a third in reading, with performance slipping even at the “basic” level.  

Internationally, the OECD’s PISA 2022 cycle reported an “unprecedented drop” across participating countries: average maths performance fell by nearly 15 points and reading by around 10 points compared with 2018.  

Covid-19 disruption and chronic absenteeism have clearly compounded the problem. No serious researcher claims touchscreens alone broke maths. But the timing and pattern of declines, particularly in high-income countries that pushed hardest on classroom tech, has shown concerning correlations between screen-based learning and worsening learning outcomes.

Screens in schools: distraction by design 

It’s also clear that “unregulated, leisure-style screen use in class is bad for learning”. Not just distracting students eyes away from learning materials, but even having a phone in a pocket can be a bigger distraction than most would believe.  

The OECD’s 2024 report Students, Digital Devices and Success found that: 

• 59% of students across OECD countries said their attention in maths lessons was diverted by other students using digital devices. 
• Students who reported being distracted by peers’ devices in at least some maths classes scored significantly lower in maths than those who were not distracted.  

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A separate analysis of PISA data reported that about 54% of students were distracted by others’ device use, and those students scored around 15 points lower in maths, roughly the equivalent of several months of learning.  

Teachers back this up on the ground. A 2024 Pew Research Center survey found that 72% of US high school teachers see cellphone distraction as a major problem in their classrooms, far higher than in middle or elementary schools.  

US school leaders share the concern. New federal data from the National Center for Education Statistics shows 77% of public schools now prohibit students from using cell phones during class, and more than half of leaders say phones hurt academic performance.  

The effect is not just about attention in the moment. Recent reviews of “digital age” memory and screen use suggest that constant device multitasking erodes the ability to store and retain information deeply and may weaken sustained attention to detail.  In other words, excessive smartphone use out side of school time can hinder performance in school.

EBN analysis: For employer audiences, the interesting line here isn't that “phones distract teenagers” - we already knew that. It is the suggestion that years of device-mediated learning look to be changing the underlying habits of attention and memory that later show up in the workplace. 

The global phone backlash 

Policymakers have noticed. UNESCO and other observers report that at least 79 education systems worldwide now restrict or ban smartphone use in schools, citing concerns about distraction, learning loss and privacy.  

Recent moves include: 

• Chile, which passed a law banning smartphones and smart devices during class in elementary and middle schools from 2026, following evidence that digital distractions were disrupting learning.  
• Bolivia, which began its 2026 school year with a nationwide ban on cellphones in classrooms across public and private schools, explicitly framing the policy as a way to boost focus and reduce the pull of entertainment apps.  
• France, where phone bans in lower secondary schools are already in place and lawmakers are debating an extension to high schools, building on early evidence of calmer atmospheres and more social interaction in phone-free campuses.  

Several US states, including Florida, Indiana, Ohio and Virginia, have passed or are drafting “phone-free schools” laws, while New York’s governor has signalled support for a statewide ban.  

Yet the story is not simply “screens out”. Estonia, one of Europe’s top performers in PISA maths, science and creative thinking, has taken the opposite tack. Rather than banning devices, it is rolling out personal AI accounts for older students as part of a national “AI Leap” initiative, arguing that the key is structured use and a focus on higher-order thinking, not memorisation.  

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The debate is shifting from “tech or no tech” to “what kind of tech, under what rules, serving which cognitive goals”.  In an increasingly digital world, banning tech could be harmful to a digital education - policy making in this area is no easy feat.

AI as the ultimate cognitive offload 

If smartphones take up too much cognitive bandwidth, throwing AI into the mix risks making thinking almost totally unnecessary.

Cognitive scientists call this “cognitive offloading”: using external tools to reduce mental effort. In the same way a calculator saves us from having to our sums in our head, or on a piece of paper, search engines and now AI is taking it to a whole other level.

A recent review of smartphone use concluded that heavy reliance on phones for information retrieval, navigation and everyday decisions encourages people to depend on devices rather than internal cognitive processes, diminishing intrinsic memory and problem-solving capacity over time.  

Emerging work on AI assistants suggests a similar pattern. A 2025 article in Frontiers in Psychology argues that delegating more tasks to AI can either free up mental bandwidth for complex thinking or encourage “cognitive laziness”, depending on how systems are used and what kinds of tasks are offloaded.  

In other words, if students and early-career workers use AI to explore ideas, debate alternatives and check reasoning, it may aid deeper learning. If they use it to avoid struggle entirely, it can actually hollow out the very skills employers say they need most.  

From classroom trends to candidate pools 

Employers are already seeing signs of strain. Surveys of hiring managers and HR leaders consistently highlight gaps not in technical knowledge, but in areas like communication, collaboration, critical thinking and attention to detail. A 2024 analysis cited by HR Daily Advisor found recent graduates ranking lower than other workers on these soft skills, including strategic and critical thinking.  

The National Association of Colleges and Employers reports a persistent disconnect between how students rate their own career-readiness competencies and how employers rate them, especially on critical thinking, professionalism and teamwork.  

On the demand side, the World Economic Forum’s Future of Jobs 2023 report puts “analytical thinking”, “creative thinking” and other high-order cognitive skills at the top of employers’ priority lists, and estimates that around 44% of workers’ core skills will be disrupted between 2023 and 2027.  

So we have a workforce where: 

• Basic academic and cognitive scores are declining for incoming cohorts in many countries. 
• Employers say they cannot find enough people with the exact cognitive skills most at risk of digital erosion. 
• AI tools are arriving that make it tempting to outsource those very skills at an even higher rate.

For talent leaders, alarm bells should be ringing. Campus recruiting, early-career programmes and leadership pipelines need to be fed with sharp young talent ready to learn the ropes and grow professionally... but are they becoming a dying breed?

The automation temptation 

Against this backdrop, automation has a clear commercial appeal. Forecasts tied to the World Economic Forum suggest AI and related technologies could displace tens of millions of roles globally by 2030, with a heavy impact on routine cognitive work such as data processing, basic coding and standard content production.  

A growing body of commentary notes that AI’s early impact is particularly strong on entry-level white-collar roles, the very roles traditionally used to grow future managers and leaders.  

If the incoming talent pool looks less prepared on core cognitive dimensions, the business case to “automate instead of hire and train” becomes even stronger: 

• Why invest in multi-year development of attention, reasoning and writing skills if AI can deliver all/most of the output immediately? 
• Why build large (and expensive) graduate intakes if entry-level tasks are the first to be automated? 

In the short term, those decisions can look rational. Over time they risk hollowing out the mid-career and senior layers that depend on people who have done the hard cognitive miles early on. For sectors already struggling with leadership succession, that is a serious structural risk. 

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What employers and EB leaders can do now 

If the trend lines point to a smaller share of candidates with strong, self-developed cognitive skills, what can employers do that is not simply “hope schools fix it”? 

A few practical levers are emerging. 

1 - Hire for cognitive habits, not just credentials 

If formal test scores and degrees are less reliable signals, selection needs to probe how candidates actually think: 

• Use work samples and case exercises that require sustained attention, reasoning and writing, not just AI-prompting. 
• Make it explicit when AI use is allowed or not, so you can see candidates’ unaided capabilities as well as their tool use. 
• Include behavioural questions that surface habits around focus, deep work and distraction management. 

This is already happening quietly in sectors like consulting and professional services. Expect it to spread. 

2 - Treat cognitive skills as trainable infrastructure 

Many employers still treat critical thinking, structured writing and attention control as “nice to have extras” rather than core hiring or on-the-job training areas. 

Given the data, that seems outdated. Instead: 

• Build foundational programmes in reasoning, evidence use, long-form writing and quantitative thinking into early-career pathways. 
• Teach “AI-native” employees how to use tools as amplifiers rather than crutches, with explicit norms about when to switch them off.  

There is a branding upside. A credible promise that “you will leave this company sharper than you arrived” is attractive in a world where people worry about their skills being commoditised. 

3 - Acknowledge digital and AI hygiene  

Younger workers know their phones are a problem. Teachers, doctors and now politicians are talking about it in public.  

Employers who can say, concretely, “here is how we protect your focus and help you build real depth while using modern tools” will stand out: 

• Clear policies on notification culture and meeting overload. 
• Guardrails on AI use in sensitive tasks. 
• Manager training on protecting focus time and modelling non-performative busyness. 

This is increasingly part of wellbeing and productivity, but it is also a cognitive-health issue. 

4 - Advocate upstream without oversimplifying 

Finally, big employers have a voice in education debates. Using that voice to call simply for “more devices” or “pure tech bans” misses the nuance emerging from the research. 

The evidence to date suggests: 

• Moderate, structured use of digital tools tied tightly to pedagogy can support learning. 
• Excessive or leisure-style device use in class is consistently linked with distraction and lower performance. 
• Unguided reliance on digital tools, including AI, encourages cognitive offloading, which can either support or erode skills depending on design.  

Responsible employer advocacy will reflect that nuance, pushing for environments that build long-term cognitive capacity rather than maximising screen exposure for its own sake. 

The long view 

Whether or not “peak human intelligence” has already passed, the combination of falling scores, saturated screens and ubiquitous AI is reshaping the supply side of the talent market. 

If large employers respond primarily by automating entry-level work, they may get short-term efficiency at the cost of long-term cognitive depth in their organisations. 

The alternative is harder and more expensive. It involves hiring for raw potential, training for thinking, and designing work and technology use so that people’s minds get sharper over time, not duller. 

That choice, more than any eventual verdict on Gen Z’s test scores, could decide whether the next generation of leaders is equipped to tackle the problems AI cannot solve for them. 

Takeaways

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