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Gen AI Will Accelerate the Innovation Adoption Cycle

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For many Americans, saving money at the grocery store was once a Sunday evening ritual. Out came the scissors and spreadsheets to clip coupons from the Sunday papers stuffed with dozens and dozens of circulars. And a week’s worth of shopping excursions were planned to get the best deals.

Couponing started with Coca-Cola’s hand-written free drink offers in 1887, and the early adopters were working-class and Great Depression-era families who needed to stretch their dollars. After the Great Depression, consumers continued their habit of saving money through coupon clipping, and brands continued to oblige.

It’s also a skill that even made some people pretty famous.  Super Couponer J’aime Kirlew built a whole cable show around her couponing pursuits. She offered her followers tips on how to save a bundle fifty cents and a dollar at a time. And she created converts with her claim of once getting $2,000 worth of groceries for $100. It’s hard work, she said, sometimes requiring six hours of clipping and organizing. But the savings were real, and it made her a role model for super savers with the same ambitions.

Try explaining any of that to a Gen Z.

Of course, they love deals just as much. But why, they ask, would anyone spend six hours cutting and organizing paper rectangles when browser extensions auto-apply codes at checkout?

And why plan elaborate store routes when price comparison happens instantly in-app? Why stockpile products in basements when alerts for flash sales and same-day deliveries eliminate the hassle and need to have room to store a dozen rolls of aluminum foil? To a Gen Z, physical coupons seem as antiquated as printing MapQuest directions.

But people, including Gen Zs, still want to save money. Still hunt for deals. Still seek the satisfaction of paying less, getting a deal. That behavior hasn’t changed.

What’s changed is the technology that supports how they save money on the products they want to buy. Coupon distribution has plummeted from 330 billion in 2010 to just 50 billion last year. People want to save money, but brands and stores have found better ways to do it and still drive sales. Even Kirlew herself has moved on. She recently described saving $225 at a store that was closing and feeling like she was “couponing” without scanning a single piece of paper. The ritual of saving has transformed from a manual weekend hobby into invisible algorithms that do all of the work in the background.

That’s the story of innovation: behavior endures, and the tools that power it transform radically. And the early adopters of that transformation have typically followed a generational cycle.

Until now.

The Great Misconception About Gen Z

We often describe Gen Z as fundamentally different. The truth is they really aren’t. They work, shop, save, pay, travel, split bills, watch movies, go out to eat and strive to stay healthy like every person their age across the generations that came before them.

They didn’t start the digital revolution. That credit goes to millennials. It was they who made the leap from analog to digital, from desktops to laptops to smartphones. They moved from CDs to MP3s, landlines to smartphones, desktop banking to mobile apps. Millennials were digital natives-in-training who normalized mobile as a digital companion.

Gen Z came of age after that shift had already happened. The first-born Gen Zers were eleven when the App Store launched on the iPhone. They weren’t literally born with a smartphone in hand, but they came of age with those devices squarely in their palms.

For them, the phone isn’t an accessory or digital companion. It’s the control center for life. They don’t “go online” because they live there, on those devices. According to PYMNTS Intelligence, Gen Z completes more than 425 digital activities per month, 34% more than every other generation. They’ve collapsed the distinction between physical and digital entirely.

What they do isn’t new. What’s new is how they go about their day-to-day. Just as Kirlew’s paper coupons were replaced by browser extensions that auto-apply codes, every generation’s “go-to” tools simply reflect the best technology available at the time. What remains constant across millennia are the underlying human behaviors that define the daily grind.

How Innovation Used to Work (and Why That’s About to Change)

For decades, innovation more or less followed a predictable relay race. Baby Boomers were the first mass adopters of credit cards in the 1970s. Gen X, and younger baby boomers, normalized ATMs. Online shopping took off in the 2000s. Millennials took us from analog to digital across every category. Gen Z made mobile the center of everything.

The pattern was always the same: invention, adoption, integration, invisibility. One generation would break new ground. The next would scale it. The one after wouldn’t think of it as new, it was just part of the landscape.

FinTechs understood this cycle and built for it. In the 2010s, they designed mobile-first financial tools for a generation that never had to unlearn kludgey analog habits.  They created apps that turned phones into wallets and budget managers.  Gen Z demanded seamless, friction-free experiences.  FinTechs delivered tools that turned banking into swiping and shopping into streaming.

But that innovation wasn’t only the property of Gen Z. The feedback loop created a flywheel that lifted every generation. The Gen Xers and the Boomers haven’t just been dragged kicking and screaming into the digital world. Rather, they’ve been systematically developing their digital fluency in earnest since the start of this decade through everyday necessity and convenience.

Parents and grandparents didn’t ask for peer-to-peer apps. But they use them now because the youngest generation showed them it was easier and better.

The comfort with digital interfaces now exists across generations. A lot of credit goes to Apple, which created devices that are easy for everyone to use — compared to PCs/Windows, which really weren’t. Everyone needs IT support for computers, yet hardly anyone does for mobile devices or most of what we do online.

Once behavior crosses the generational chasm, it becomes routine. Why go back?

But as they say, that was then.

AI Changes Everything: The End of Generational Innovation Cycles

Gen AI and Agentic AI are breaking the traditional innovation adoption pattern. They don’t rely on generational adoption because they will be embedded inside the apps, systems and platforms people already use.

Gen AI and agents will improve the ways we engage with existing apps by creating intelligent, invisible flows. New AI-native apps will be developed that will offer new ways to complete complex tasks. Activities that used to require multiple apps and domain-specific knowledge will collapse into a single prompt.

Intent will take a fast track to execution without all the friction in the middle.

In investing: “Round up my purchases and invest in a low-risk fund unless I’m spending more than usual.” AI will monitor, decide and execute based on context.

In education: “Explain this algebra concept with visuals and examples from last week’s lesson.” AI personalizes curriculum in real time based on individual learning patterns.

In shopping: “I’m trying to find the best dog bed for a Border Collie, recommendations on several brain puzzles to keep her mentally stimulated and the best training tips from the top breeders in the world.” AI will find and buy the bed and the puzzles and produce summarized training tips in less than a minute.

The infrastructure is already here: APIs, data centers, tokens, real-time rails, digital identity, risk engines, cloud platforms. AI will connect the dots and make the system intelligent. It doesn’t create new rails because it doesn’t need to. It just moves people and apps across existing ones faster, smarter and with less effort.

Some of this is already taking shape, though these are early days.

Voice Becomes the Great Equalizer

In the next chapter of this story, the user interface may not always be a screen. But it will always be a sentence, a written or spoken prompt. Voice will become the most powerful interface of this distributed connected economy — not because it’s new, but because it removes the need to learn how to use something new to get a better outcome. When the system understands what you mean, you don’t need to know how to ask perfectly.

In this future, AI becomes the operating system, voice becomes the interface and the mobile device as we know it becomes more optional than essential. OpenAI and others are already designing AI-native devices that don’t look like phones, don’t behave like apps and don’t sit behind screens. They live in your environment, listen, adapt and respond.

You’ll say what you need, and AI will orchestrate the response across systems. Typing becomes a backup plan. Navigation across apps becomes unnecessary. The entire system becomes anticipatory, ambient, context-aware.

AI will work equally well for everyone because it eliminates the learning curve that has traditionally created generational adoption patterns. An 80-year-old can say, “Help me manage my medications and remind me when to take them” just as easily as a 20-year-old can ask for investment advice or travel planning.

From Generational Shift to Universal Access

AI will change the rhythm and the pace of innovation and how quickly new experiences are adopted. For the first time, innovation won’t trickle down from the young. It has the potential to touch everyone because it will become part of everything that is already a native digital or mobile experience.

Gen Z will demand it because they expect technology to anticipate their needs. Millennials will embrace it because they’re comfortable with digital solutions that solve real problems. Gen X will welcome the simplicity because they value efficiency over complexity. Boomers will adopt it because it removes friction rather than adding it. Seniors, who are living longer and more active lives, will find that it makes access to important things easy and intuitive, and preserves their independence.

The traditional innovation relay race, where young early adopters pull older generations forward over time, will be upended.

The New Innovation Economy

This shift has important implications for how businesses think about innovation, adoption and market penetration. The traditional model of targeting young early adopters and waiting for generational pull-through becomes obsolete when innovation is embedded and access becomes voice-activated.

Companies that understand this will build for universal access from day one, rather than assuming that to the youth go all of the innovation spoils. They’ll focus on solving universal human needs like health, wealth, convenience and connection rather than generation-specific preferences. They’ll design for conversation rather than navigation, for orchestration rather than operation.

The winners will be those who recognize that digital fluency already exists across generations, and the missing piece (intuitive, intelligent interfaces) is finally here and getting better every day.

Everyone gets to be an early adopter from day one.

The future of innovation isn’t generational. It’s conversational.

Just ask.

 



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Frontiers broadens AI‑driven integrity checks with dual integration

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Image: Shutterstock.com/EtiAmmos

Frontiers has announced that external fraud‑screening tools – Cactus Communications’ Paperpal Preflight, and Clear Skies’ Papermill Alarm and Oversight – have been integrated into its own Artificial Intelligence Review Assistant (AIRA) submission-screening system.

The expansion delivers what the companies describe as “an unprecedented, multilayered defence against organised research fraud, strengthening the reliability and integrity of every manuscript submitted to Frontiers”.

AIRA was launched in 2018, making Frontiers one of the early adopters of AI in submission checking. In 2022, Frontiers added its own papermill check to its comprehensive catalogue of AIRA checks, with the aim of tackling the industry-wide problem of manufactured manuscripts. The latest version, released in 2025, uses more than 15 data points and signals of potential manufactured manuscripts to be investigated and validated by a human expert.

Dr Elena Vicario, Head of Research Integrity at Frontiers, said: “Maintaining trust in the scholarly record demands constant innovation. By combining the unique strengths of Clear Skies and Cactus with our own AI capabilities, we are raising the bar for integrity screening and giving editors and reviewers the confidence that every submission has been rigorously vetted.”

Commenting on the importance of the partnership, Nikesh Gosalia, President, Global Academic and Publisher Relations at Cactus Communications, said: “This partnership with Frontiers reflects the confidence leading publishers have in our AI-driven solutions. Paperpal Preflight is a vital tool that supports editorial teams and existing homegrown solutions in identifying and addressing potential issues early in the publishing workflow.

“As one of the world’s largest and most impactful research publishers, Frontiers is taking an important step in strengthening research integrity, and we are proud to collaborate with them in this mission of safeguarding research.”

Adam Day, Founder and CEO of Clear Skies, added: “Clear Skies is thrilled to be working with the innovative team at Frontiers to integrate AIRA with Oversight. This integration makes our multi-award-winning services, including the Papermill Alarm, available across the Frontiers portfolio.

“Oversight is the first index of research integrity and recipient of the inaugural EPIC Award for integrity tools from the Society for Scholarly Publishing (SSP). As well as providing strategic Oversight to publishers, our detailed article reports support human Oversight of research integrity investigations on publications as well as journal submissions.”



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Australia’s China AI quandary is a dealmaker’s opportunity

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It is not surprising that reactions to Chinese ambassador Xiao Qian’s suggestion that Australia and China cooperate more on artificial intelligence as part of an expanded Free Trade Agreement have been hawkish. However, it highlights the need for Australian organisations to broaden their view on the AI world.

It would take a dramatic shift in policy position for Australia to suddenly start collaborating with China on AI infrastructure such as data centres and the equipment that runs them. But it would be wrong to assume that advances in capability will always come from America first.

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Joint UT, Yale research develops AI tool for heart analysis – The Daily Texan

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A study published on June 23 in collaboration with UT and Yale researchers developed an artificial intelligence tool capable of performing and analyzing the heart using echocardiography. 

The app, PanEcho, can analyze echocardiograms, or pictures of the heart, using ultrasounds. The tool was developed and trained on nearly one million echocardiographic videos. It can perform 39 echocardiographic tasks and accurately detect conditions such as systolic dysfunction and severe aortic stenosis.

“Our teammates helped identify a total of 39 key measurements and labels that are part of a complete echocardiographic report — basically what a cardiologist would be expected to report on when they’re interpreting an exam,” said Gregory Holste, an author of the study and a doctoral candidate in the Department of Electrical and Computer Engineering. “We train the model to predict those 39 labels. Once that model is trained, you need to evaluate how it performs across those 39 tasks, and we do that through this robust multi site validation.” 

Holste said out of the functions PanEcho has, one of the most impressive is its ability to measure left ventricular ejection fraction, or the proportion of blood the left ventricle of the heart pumps out, far more accurately than human experts. Additionally, Holste said PanEcho can analyze the heart as a whole, while humans are limited to looking at the heart from one view at a time. 

“What is most unique about PanEcho is that it can do this by synthesizing information across all available views, not just curated single ones,” Holste said. “PanEcho integrates information from the entire exam — from multiple views of the heart to make a more informed, holistic decision about measurements like ejection fraction.” 

PanEcho is available for open-source use to allow researchers to use and experiment with the tool for future studies. Holste said the team has already received emails from people trying to “fine-tune” the application for different uses. 

“We know that other researchers are working on adapting PanEcho to work on pediatric scans, and this is not something that PanEcho was trained to do out of the box,” Holste said. “But, because it has seen so much data, it can fine-tune and adapt to that domain very quickly. (There are) very exciting possibilities for future research.”



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