For those who know the story of Elizabeth Holmes and Theranos, it may seem hard to remember a time when the company was unstoppable.

Read more: AI Promised the World. It’s Not Delivering.

While her name is now permanently associated with fraud and deception, the truth of the matter is that for a time, the company founded by a 19-year-old Holmes in 2003 seemed poised to change the world. Their promise to revolutionise the healthcare industry by providing fast, accurate and painless blood tests caught the attention of many and led to the company’s peak valuation of nine billion dollars in 2014. Combining the potentially paradigm-shifting technology with Holmes’ captivating public persona, the company seemed poised to change the world. 

Despite claims that they could do a full range of blood tests from a pinprick of blood, the company never developed the technology and instead engaged in a variety of deceptive practices to hide this fact. Of course, as is often the case, Theranos’s secret eventually broke and led to the downfall for a company which had once been praised for its “phenomenal rebooting of laboratory medicine”.¹ Indeed, Theranos and Holmes now serve as a prime example of a company both overpromising and underdelivering—or in this case, failing to deliver at all. 

There was only one problem. It was all a lie. 

One of the most interesting facts about Holmes and Theranos comes not from their downfall, but from the origin of the company. While Holmes may have lied about plenty regarding the company, her stated motivation for creating Theranos seems noble on its face: their attempts to create a blood testing process which used minimal amounts of blood stemmed from Holmes fear of needles—a fear which many can relate to. Unfortunately, at the beginning of the venture, Holmes was told by multiple experts in the field that her hope of creating a full suite of tests which worked from a pinprick of blood was not viable²—advice she ignored, and which would later be proven correct. This, I think, is the most interesting part of the Theranos story: despite knowing that the reality of their dream was impossible, the company continued to sell an impossible promise. 

Another Impossible Promise

On August 8, 2025, OpenAI unveiled the long-awaited next-generation version of their large language model chatbot GPT-5 to the public, claiming it could provide “PhD-level” abilities.³ The world’s richest and most controversial man, Elon Musk, took the claim a step further, hyping up his company’s AI Grok as being “better than PhD level in everything”. In May of the same year, Mark Zuckerberg touted the ability for AI chatbots to replace human relationships and friendships.⁴ Zuckerberg has also made similarly lofty claims about Meta’s other technologies, arguing that in the future, anybody who doesn’t own and use AI glasses will “be at a disadvantage”.⁵

Increasingly, AI is being integrated into every aspect of our daily lives, with its loudest proponents claiming that it will solve all our problems. In the fast-food industry, the owners of KFC, Pizza Hut and Taco Bell claimed that they were adopting an “AI-first mentality”⁶(though the company is reportedly rethinking the approach after a customer used the AI to order 18,000 glasses of water).⁷ Interested in learning a new language? Duolingo believes that AI can help the process, with the CEO claiming AI can make employees “four or five times” as productive⁸ (though once again, their adoption of the technology has led to a significant backlash from customers who doubt its effectiveness⁹). Keen to play some games to relax? EA—the publisher of a wealth of large franchises including EA FC(formerly FIFA) and Battlefield—recently announced a 50-billion-dollar sale, relying heavily on the promise of AI to streamline development costs (though gamers and developers alike are less than thrilled). Everywhere you look, AI promises the world. But promises aren’t reality—and there are plenty of good reasons to be suspicious of those with a vested interest in the success of AI. 

The Unfortunate Truth

As a media scholar (and one of the PhD-level people that OpenAI is aiming to replace), I am deeply sceptical of AI. Many of my doubts stem from fundamental issues with how the technology works. While the title “artificial intelligence” implies a level of thought, and the term “large language model” (LLM) seems to indicate an understanding of language, the reality is that these tools neither think nor understand the meaning of words. 

A full explanation of the ways they work is beyond the scope of this article, but on the most basic level, the ways that LLMs and generative AI view language is more akin to a complex math equation. Your prompt is one side of the equals sign and the technology attempts to “solve” for the most likely response. In addition to this process being extremely power intensive (and having negative environmental impacts¹⁰), it is also the reason that despite the hyped improvements in more recent models, AI continues to suffer from widespread “hallucinations”¹¹—where the chatbot either regurgitates inaccurate information or invents entire falsehoods. Indeed, CEO of Open AI Sam Altman has admitted that hallucinations are not an engineering flaw for LLMs but a “mathematically inevitable”.¹² 

Is AI Making Us Dumber?

The issues caused by these hallucinations are significant and may further exacerbate societal issues rather than solve them. A recent report indicated that 45 per cent of AI responses based on news articles contained “significant” errors—with a whopping 81 per cent of responses having some form of issue.¹³ In this age of misinformation, relying on AI seems like a recipe for disaster. More importantly, current research points towards AI having a negative effect on its users, “eroding critical thinking skills”.¹⁴ Furthermore, while it is often thought of as neutral, numerous studies¹⁵ have exposed biases in AI models¹⁶—an unsurprising reality when one acknowledges the potential biases of their creators which may filter in.  

I could go on and on about the issues with AI (and indeed, some of my poor friends have had to endure my rants on the topic in the past). Ultimately however, all these criticisms can be summed up in one sentence. That is, the reality of AI falls drastically short of the promise its creators espouse. 

With all this in mind, I should acknowledge that I am sympathetic to those that want to believe the promise of AI. The world we live in is fundamentally broken in so many ways with political polarisation, environmental destruction and unspeakable injustice occurring daily. And that’s not even acknowledging the more mundane tasks that it could help with. The promise of a “magic bullet” technology that can ease any of the issues we face—just like the promise of a needle-free blood test—is enticing. And it is true that this technology can help in certain situations. As a tutor to international students, machine learning can be a helpful tool in translating complex ideas discussed in our courses (though it still has imperfections that need correcting). My friends who work in software engineering are adamant that it can help make the tedium of coding less strenuous (which is understandable considering coding, like LLMs, also treats language as a sort of math). AI-assisted live transcription is also potentially revolutionary for the hard of hearing. But these are individual solutions for individual problems—and we should not be forced to swallow all the issues with these AI models in order to benefit from them. 

No Silver Bullet?

The reality is, there is no one solution that will solve all our problems. AI cannot create. Every response it gives is based on the existing work of talented artists, writers and experts who it often fails to properly credit. Working as a tutor, I have seen firsthand its negative effects—seeing students inadvertently turn in assignments with invented information and incorrect sources. In seeing AI as the solution to their problems, they have only created more—and greater—problems. 

This, more than anything, is the danger of AI. Proponents like Zuckerberg and Altman want you to believe that it can enhance—or even replace—human connection, but the opposite is true. If you want to learn, create or connect, you can’t do so through AI. You should go to the source, read what others are saying and listen to the experts who have dedicated their lives to solving these problems. Step outside the tech bubble these companies want to trap you in and connect with the real world.

The truth is, no one machine can save the world, nor can any one individual. So don’t give in to the promise of the technology. Connect with reality. Connect with others.  

Article supplied with thanks to Signs of The Times

About the Author: Ryan Stanton is a PhD Graduate from the University of Sydney. A Media and Communications scholar, he is constantly torn between wanting to believe the promise of new technologies and being disappointed by the reality. 

Feature image: Canva

For years, shopping online followed a predictable pattern. You searched, compared, skimmed reviews, opened too many tabs, got distracted, then either bought something or gave up.

It was clunky, time-consuming and mentally draining, but at least the rules were clear. Ads were ads. Advice lived somewhere else.

That separation is disappearing fast.

AI shopping assistants are moving from the sidelines into the centre of the buying journey. Tools like ChatGPT, Gemini, Perplexity and Microsoft Copilot are no longer just helping people research purchases. They are recommending products, surfacing prices, inserting “Buy” buttons and, in some cases, letting users complete a purchase without ever leaving the conversation.

This shift is happening faster than most people realise. Advances in generative AI, changing consumer expectations and growing frustration with traditional online shopping are converging. Add in a generation comfortable outsourcing decisions to algorithms, and the result is a retail landscape that looks fundamentally different to the one we grew up with.

For professionals, retailers and leaders, the urgency is real. This is not just a new marketing channel. It’s a rewiring of how trust, influence and decision-making work in commerce.

Trend 1: Advice and Advertising Are Merging

The first shift is subtle, and that’s what makes it powerful. The line between genuine advice and paid promotion is becoming increasingly blurred.

Modern AI assistants don’t just answer questions. They suggest products, rank options and increasingly prompt users to buy. Microsoft Copilot now embeds shopping recommendations directly into conversational responses. Other platforms have experimented with sponsored answers that sit alongside organic suggestions, often without clear visual distinction.

Unlike traditional advertising, these prompts don’t feel like ads. They feel like guidance. When a recommendation arrives in a conversational tone, supported by what looks like reasoning, people lower their scepticism. The persuasive power comes not from interruption, but from integration.

For consumers, this creates a new challenge. How do you tell the difference between impartial advice and a commercial nudge? One practical habit is emerging: ask the AI why it recommended something. Does it explain trade-offs? Does it offer alternatives? Or does it funnel you toward a single “best” option? Real advice explains choice. Advertising pushes outcomes.

For businesses, this trend rewrites influence. Visibility alone is no longer enough. Products must be defensible, explainable and competitive when placed side by side in an AI-generated comparison. If your offering can’t survive transparent scrutiny, AI will expose that quickly.

Trend 2: Transparency Will Be Forced, Not Volunteered

At the moment, regulation in this space is lagging behind reality. There are few clear rules forcing AI shopping tools to disclose what is paid, what is sponsored and what is genuinely impartial.

That lack of clarity matters for two reasons. First, consumers deserve to know when bias or commercial influence is present. Second, accountability becomes murky when AI systems get things wrong.

A recent example highlighted this risk when an AI travel assistant confidently advised tourists to visit a hot spring in Tasmania that simply does not exist. The issue wasn’t just the hallucination. It was the absence of clear responsibility. Who is accountable when an AI invents reality with confidence?

As AI increasingly shapes purchasing decisions, transparency will become unavoidable. Disclosure around sponsorship, data sources and limitations will be demanded by regulators, journalists and consumers alike.

For leaders and organisations, this is an opportunity to move early. Systems that explain recommendations, acknowledge uncertainty and clearly separate advice from advertising will earn trust long before regulation forces compliance.

Trend 3: AI Is Compressing Hours of Shopping Into Minutes

Despite the risks, the consumer upside of AI-powered shopping is undeniable. These tools are dramatically reducing friction.

Tasks that once took hours now take minutes. Comparing prices across retailers. Summarising thousands of reviews. Tracking historical discounts. Monitoring price changes. In some cases, completing a purchase without opening a single browser tab.

Australian consumers are leading this shift. Research shows a significant majority of Australians have interacted with AI while shopping in recent months, well above the global average. More tellingly, more than half of those users have made purchases based on generative AI recommendations.

This is no longer experimental behaviour. It’s habitual. Many households are already using AI to stretch budgets, find better deals and automate parts of the shopping process.

For businesses, this fundamentally changes discovery. Where search engine optimisation once dominated, answer engine optimisation now matters just as much. If an AI model cannot easily surface, explain and justify your product, it effectively disappears from consideration.

Trend 4: The Weekly Grocery Shop Is Being Rewritten

AI-driven shopping is not confined to screens. It is reshaping physical retail too.

Smart carts and supermarket apps already allow shoppers to scan items as they go, track their total in real time, receive personalised discounts and pay without lining up. But the bigger transformation is happening quietly in the background.

Experts predict supermarkets will become smaller and more focused on fresh food. Pantry staples like toilet paper, nappies and cleaning products will increasingly be reordered automatically and delivered to homes without conscious effort.

In practice, in-store shopping becomes about choice, quality and freshness, while AI handles repetition behind the scenes. Two shoppers standing in the same aisle may see different specials because the system understands their habits, preferences and household needs.

AI is also changing how decisions are made in the moment. A shopper considering a new pair of headphones can take a photo, upload it to an AI assistant and instantly receive a comparison across models, prices and stores, including historical data showing whether a discount is likely soon.

For retailers, loyalty will be driven less by location and more by usefulness. The brands that win will be the ones that integrate seamlessly into consumers’ decision-making systems.

Trend 5: Trust Becomes the Ultimate Competitive Advantage

As AI takes on more of the buying journey, trust becomes the scarce resource.

These systems are persuasive by design. They speak with confidence. They explain reasoning. They feel personal. That makes over-reliance a real risk.

Consumers will increasingly judge platforms not by how clever they are, but by how transparent and controllable they feel. Can users understand why something is being recommended? Can they override it? Can they see alternatives?

For professionals building or deploying these tools, the goal should not be to remove humans from the loop, but to keep them meaningfully informed. Trust grows when people feel empowered, not nudged.

Brands that over-optimise for persuasion may win short-term sales, but they risk long-term credibility. Restraint, clarity and honesty will prove more valuable than cleverness.

What This All Means

AI-powered shopping is not a future scenario. It is already reshaping how people research, decide and buy. The five trends are clear. Advice and advertising are merging. Transparency will be demanded. Shopping is becoming faster and more automated. Physical retail is being re-engineered. And trust is becoming the defining differentiator.

The challenge for leaders and professionals is not technical. It is behavioural. Understanding how people make decisions when AI is in the room, and designing systems that support rather than exploit that reality.

The question is no longer whether AI will influence what we buy. It already does. The real question is whether we build a shopping ecosystem that is helpful, honest and human, or one that quietly nudges us while pretending not to.

The difference will come down to the choices being made now, while the rules are still being written.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

Not long ago, humanoid robots sat firmly in the category of “cool demo, wildly impractical.” They dazzled on conference stages, tripped over their own feet on YouTube, and then quietly disappeared back into research labs. That phase is ending fast.

Humanoid robots are moving from spectacle to systems. From factories and hospitals to aged care facilities and, eventually, our homes, they are inching closer to everyday life. Goldman Sachs estimates there could be more than 13 million humanoid robots in use globally by 2035. That’s less than a decade away. While most of these robots will appear in workplaces first, the ripple effects will be felt across households, cities and entire industries.

The drivers are converging rapidly. Advances in AI vision, balance and hand dexterity are accelerating. Labour shortages are intensifying as populations age and fewer people enter physically demanding roles. Cultural expectations are shifting around convenience, care and the value of time. And younger generations are far more comfortable sharing space with machines than any before them.

For leaders and professionals, the question is no longer whether humanoid robots will matter, but how quietly and quickly they will reshape expectations. 

1. From Sci‑Fi Spectacle to Quiet Utility 

The first major shift is psychological. Humanoid robots are not arriving with dramatic flair or cinematic ambition. They’re slipping in through side doors, doing the dull jobs no one wants to talk about at dinner parties.

We already live with robots, even if we don’t think of them that way. They vacuum our floors, mow our lawns and assist surgeons. In fact, more than 80 percent of prostate surgeries are now performed using robotic systems. COVID accelerated this trend, particularly in agriculture and logistics, where closed borders and labour shortages forced rapid adoption.

Humanoid robots represent the next logical step because they fit into environments built for humans. Factories, warehouses and hospitals don’t need to be redesigned when the robot has two legs, two arms and can use existing tools. That’s why companies like BMW, Hyundai and Tesla are already trialling humanoid robots on factory floors for repetitive and physically demanding tasks. Hyundai has publicly stated it plans to deploy humanoid robots in US factories from 2028.

China offers a glimpse of what early adoption looks like at scale. Humanoid robots are already working as tour guides, retail assistants, warehouse staff and service workers, with some even assisting in policing and security roles. Dedicated robot training centres allow machines to learn by observing humans rather than being painstakingly programmed line by line. 

The implication is clear. Early adoption will be quiet and practical rather than flashy. Organisations that treat humanoid robots as boring infrastructure rather than futuristic mascots will extract far more value from them. 

2. Cobots, Not Job Stealers 

It’s impossible to discuss humanoid robots without confronting workforce anxiety. Elon Musk has said Tesla aims to build up to 100,000 humanoid robots per month within five years. Numbers like that naturally raise concerns about job losses.

But the reality is more nuanced. Humanoid robots are particularly good at jobs humans increasingly struggle to fill. Dirty, dangerous and repetitive work. Heavy lifting. Night shifts. Tasks that lead to injury, burnout or high turnover.

Robots are already being used for warehouse picking, post‑surgery rehabilitation support and repetitive assembly. Deloitte predicts physical AI and humanoid robots will play a major role in addressing labour shortages, especially as populations age and healthcare demand grows. 

Rather than replacing humans, most experts expect robots to change the nature of work. This is where the idea of “cobots” becomes critical. Collaborative robots that work alongside humans, taking on physical or repetitive tasks while people move into supervision, creativity, problem‑solving and decision‑making roles.

For organisations, the real opportunity lies in redesigning jobs, not eliminating them. Professionals who focus on skills like judgement, empathy, oversight and systems thinking will become more valuable, not less.

3. Impressive, Fallible and Still Learning

The technology behind humanoid robots has advanced rapidly, particularly in vision systems, balance and hand dexterity. Some recent demonstrations have been so realistic that audiences questioned whether they were watching a robot or a human in disguise.

At the same time, viral clips of robots face‑planting, freezing mid‑task or dropping objects are not anomalies. They are part of the learning curve. This is what early‑stage intelligence looks like in physical form.

Robots perform best in controlled environments like factories and warehouses. Homes are far more challenging. Pets move unpredictably. Children run. Objects shift. Lighting changes. Most humanoid robots today still rely on some level of human supervision or remote assistance for complex tasks.

This phase closely mirrors the early days of self‑driving cars. Highly impressive in certain contexts, unreliable in others. The risk is not that robots will fail, but that humans will assume they won’t.

Organisations that succeed will design systems that assume occasional failure and build safeguards accordingly. 

4. The Home Robot Will Sell Time, Not Wow 

When humanoid robots enter homes, affordability and accessibility will dominate the conversation. Today, a humanoid robot like Neo costs around $20,000. By 2035, that figure is expected to fall closer to $10,000 as manufacturing scales and components become cheaper. 

But ownership won’t be the starting point for most people. Early home robots will be aimed at wealthy households, aged care facilities and people with mobility needs. LG has already demonstrated prototype home robots capable of folding laundry and preparing simple meals, while projects like Tombot, a robotic puppy designed to support people with dementia, show how emotionally intelligent design can support care settings. 

For most households, the first exposure will likely be shared robots in apartment buildings, hotels or assisted living environments rather than owning one outright. Leasing models and robot‑as‑a‑service offerings will play a significant role in improving accessibility.

The real appeal is not novelty. It’s time. Even saving 30 to 60 minutes a day by offloading repetitive tasks changes how people live, work and rest.

5. Trust Will Matter More Than Life-like Design

Safety, privacy and psychological trust will ultimately determine whether humanoid robots are accepted into daily life. Most are designed to be lightweight, slow and compliant, stopping when they encounter resistance.

Privacy is a genuine concern. Robots rely on cameras and sensors to navigate spaces, raising questions about data storage, access and ownership. There is also the risk of over‑trust. Robots that look human can trigger emotional responses even when people know they are machines.

Experts agree humans will remain in the loop for a long time, particularly in homes and healthcare settings. Acceptance will depend less on realism and more on whether people feel in control of the technology.

There is also a genuine fear response to consider. An estimated 20 percent of the population experiences some degree of robophobia. Ignoring that reality would be a mistake. 

What This All Adds Up To

Humanoid robots are not coming to replace us, impress us or entertain us. They’re coming to quietly reshape how work gets done, how care is delivered and how time is reclaimed.

The trends are clear. Practical utility over spectacle. Collaboration over replacement. Rapid progress with real limitations. Time as the killer feature at home. Trust as the deciding factor everywhere. 

The future won’t arrive with a dramatic unveiling. It will arrive task by task, shift by shift, home by home. The robots are learning fast. We should too.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

When news broke that Disney had signed a landmark agreement with OpenAI, the reaction across the creative industries was mixed.

At a time when much of Hollywood is resisting artificial intelligence, launching legal challenges, or warning of creative collapse, Disney chose a very different path.

Rather than treating AI as an existential threat, Disney treated it as a question.

How could this technology help us tell better stories? How might it expand creativity rather than diminish it? And how do we engage with it early, thoughtfully, and on our own terms?

The agreement allows OpenAI to work with Disney’s vast library of characters and storytelling assets across emerging AI animation and generative video tools. It is an extraordinary move, not just because of the scale of the deal, but because of what it signals.

Disney is once again choosing partnership over protectionism. Exploration over resistance. Curiosity over certainty.

To understand why this decision matters so much, you need to see it not as a one off, but as the latest chapter in a pattern that stretches back more than a century.

This is not a company dabbling in disruption. Disney is a company that has always believed the future belongs to those willing to rethink first.

Walt Disney built an empire not by predicting the future, but by being relentlessly curious about what might be possible.

Long before Disney became synonymous with global entertainment, Walt Disney was an outsider. He was not backed by powerful studios, nor was he working within accepted industry rules. His success came from repeatedly asking questions others dismissed as impractical or reckless.

What if animation could carry emotional weight? What if stories could live across multiple platforms? What if entertainment could be experienced as a place, not just a performance?

These were not safe questions.

In the 1930s, when Disney decided to create Snow White and the Seven Dwarfs, industry insiders openly mocked the idea. Feature length animation was considered commercial suicide. Cartoons were short, disposable novelties. No one believed audiences would sit through ninety minutes of illustrated storytelling.

Disney nearly bankrupted his company bringing Snow White to life. He invested in new animation techniques, new camera technology, and unprecedented levels of artistic detail. What he was really investing in, however, was a belief that curiosity about emotional realism would be rewarded.

It was. Snow White did not just succeed. It created an entirely new category of cinema.

That same pattern repeated in the 1950s, when television emerged as a disruptive force. Hollywood studios panicked. Cinema attendance declined. Executives treated television as a threat to be resisted.

Disney Again Went The Other Way.

Rather than rejecting television, he partnered with ABC to create a weekly television series. On the surface, it was entertainment. In reality, it was something far more strategic. The show helped finance, promote, and emotionally prepare audiences for Disneyland, a physical place that did not yet exist.

Television was not competition. It was infrastructure.

That deal helped fund Disneyland’s construction and made Walt Disney himself a household name. At a time when business leaders remained largely invisible, Disney became the face of his vision. Not as a corporate executive, but as a guide, a storyteller, and a trusted presence in people’s homes.

Again, Curiosity Reshaped The Rules.

Disneyland itself was another audacious experiment. Walt Disney rejected the idea of building an amusement park. He disliked the chaos, the noise, and the transactional nature of existing parks. Instead, he imagined something different.

A theme park. A place where architecture, psychology, storytelling, and movement worked together to create a coherent emotional experience.

Buildings were deliberately designed to feel welcoming rather than overwhelming. Pathways controlled anticipation and discovery. Attractions were not rides, but experiences. Guests could spend an entire day immersed in story without stepping onto a single attraction.

It was entertainment designed around humans, not hardware.

Since opening in 1955, more than one billion people have visited Disneyland. That number alone tells a powerful story about the enduring appeal of human centred design driven by curiosity.

Crucially, Disney’s culture did not fossilise after Walt’s death.

When the company acquired Pixar in 2006, it faced a choice. Absorb Pixar and impose corporate discipline, or protect the very culture that made Pixar special.

Disney Chose Protection.

Pixar’s creative model rewarded questioning, dissent, and rethinking. Hierarchy mattered less than ideas. Disagreement was not seen as disloyalty, but as a necessary ingredient for excellence. Some of Pixar’s most successful films emerged precisely because creators were encouraged to challenge assumptions rather than conform to them.

This was curiosity embedded at scale.

Under Bob Iger’s leadership, that philosophy continues. Listening to an interview with Iger recently, I was struck by his admission about how Disney evaluates new ideas. The first question is not about cost. It is not about risk mitigation.

The First Question is Simple: Can we make this great?

That mindset explains why Disney’s response to artificial intelligence looks so different to many of its peers.

Where others see loss of control, Disney sees creative leverage. Where others fear displacement, Disney sees expansion. Where others hesitate, Disney experiments.

The OpenAI partnership echoes the ABC television deal of the 1950s. In both cases, Disney encountered a new technology that unsettled an industry. In both cases, it chose engagement over retreat.

This does not mean blind optimism. Disney has learned from missteps, including the difficult early years of Disneyland Paris. But even those moments reinforced a deeper truth. Curiosity must be paired with accountability. Experimentation must be paired with learning.

That balance is what allows curiosity to endure.

Walt Disney once said that Disneyland would never be finished, as long as there was creativity left in the world. He was not talking about a park. He was talking about a posture.

A refusal to believe the story is ever complete. A willingness to revisit assumptions. An understanding that relevance is not preserved through protection, but through exploration.

The OpenAI partnership is not a departure from Disney’s identity. It is proof that the identity still holds.

In a world obsessed with prediction, Disney continues to bet on curiosity. And history suggests that is a very good bet indeed.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

How Agentic Commerce is about to Redefine Retail Forever

Shopping as we know it is about to change – again. The era of agentic commerce is dawning, where AI agents shop, compare, and buy on our behalf. Fueled by generative AI, real-time data, and seamless payment integration, these digital “assistants” are evolving from simple chatbots into autonomous consumers.

The drivers are clear: advances in large language models, the integration of payment systems like PayPal and Venmo within ChatGPT, and growing consumer comfort with automation. Retailers, meanwhile, face both opportunity and existential threat as control over the customer journey begins to shift.

To understand what’s next, let’s explore five key trends reshaping the future of retail and commerce in the age of AI agents.

1. From Search to Conversation: Shopping Becomes Dialogic

Consumers are moving from search bars to conversations. Walmart’s recent partnership with OpenAI epitomises this shift: shoppers can now ask ChatGPT to “plan a taco dinner” or “restock pantry essentials,” receive curated suggestions, and check out – all within the chat.

• Why it matters: Search-based discovery is giving way to contextual dialogue, making shopping more intuitive and personalised. Instead of typing keywords, consumers describe goals or moods and AI agents translate that into purchases.
• Implications: Retailers must now optimise for AEO (Answer Engine Optimization) visibility rather than SEO. The “storefront” of the future may not be a website at all, but a conversation inside an AI ecosystem.
• What to do: Brands should develop “agent-friendly” data schemas and product metadata so their items can be discovered, compared, and purchased via conversational agents.

2. The New Buyer Is a Bot: Agentic Commerce Arrives

Agentic commerce describes a world where AI agents act as autonomous shoppers – buying groceries, managing loyalty points, and even negotiating prices.

• Why it matters: Instead of manually browsing and comparing, users will set rules (“buy detergent when it’s 20% off” or “reorder coffee every three weeks”), and agents will execute these automatically. Research shows that most consumers are interested in AI tools that can make purchases when prices drop.
• Implications: Shopping becomes anticipatory rather than reactive. But as agents gain autonomy, questions of liability, consent, and trust loom large. For instance, who’s responsible if your AI buys something you didn’t intend to or don’t want?
• What to do: Retailers should pilot transparent AI-agent interfaces that let customers review, approve, or override agent decisions to maintain confidence and control.

3. The Frictionless Checkout: Payments Go Invisible

PayPal’s integration with ChatGPT represents a crucial step toward invisible commerce – a world where transactions happen without leaving the conversation. Using OpenAI’s Agentic Commerce Protocol, PayPal now allows direct in-chat payments and merchant listings without extra integration work.

• Why it matters: Payments are no longer the end of the funnel – they’re built into the interaction. This eliminates friction and allows “chat-to-checkout” in seconds.
• Implications: Traditional payment gateways and checkout pages may fade. Trust, fraud prevention, and dispute resolution will instead be embedded directly in conversational layers.
• What to do: Businesses should align with emerging open protocols to make their products agent-accessible and compatible with cross-platform AI ecosystems.

4. AI-Powered Customer Experience: The Age of Anticipation

The customer experience is evolving from reactive to predictive and proactive. McKinsey’s “Next Best Experience” model shows that AI-powered personalisation can boost satisfaction by up to 20% and reduce service costs by 30%. These systems detect when a customer needs help before they even ask.

• Why it matters: The next frontier isn’t personalisation at scale; it’s personalisation in real time, driven by data and generative content. Agentic AI goes further by testing and refining communications autonomously, learning with every interaction. Consider how Yelp’s new AI receptionist and host bots can answer calls, take bookings, and even chat with other bots to coordinate reservations.
• Implications: Companies should integrate predictive and conversational AI tools into their customer service stack—not just to improve efficiency, but to build anticipatory trust.

5. Retail’s Identity Crisis: Losing the Interface

While AI agents simplify the shopper’s life, they threaten to disintermediate retailers. As the Wall Street Journal notes, brands like Walmart and Etsy have jumped onto ChatGPT integration for exposure, but they risk ceding control over customer experience, data, and loyalty.

• Why it matters: When AI assistants become the primary point of discovery, brand identity competes with algorithmic preference. Retailers’ lucrative ad and search ecosystems (which are worth billions annually) could erode as discovery shifts “upstream” into AI chats.
• What to do: The winners will be those who co-create with AI platforms, ensuring their products and brand values are reflected accurately in conversational interfaces. Think API partnerships, branded agent personalities, and data-sharing agreements rather than banner ads.

Some concluding thoughts

The rise of agentic commerce marks a profound shift – from browsing to briefing, from searching to conversing, and from paying to being paid for by your AI.

As consumers hand over more decisions to digital intermediaries, trust, transparency, and control will define the next decade of retail. The question for brands is no longer whether AI will reshape shopping but who will own the relationship when it does.

To stay relevant, leaders must design for an audience of two: the human and the algorithm.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

With 31% of Australians now renting, the dream of home ownership is slipping out of reach for millions. Futurologist Professor Rocky Scopelliti says this shift isn’t just economic, it’s cultural.

“We’ve reached a point where housing isn’t just dividing people economically. It’s dividing our sense of identity,” he explains.

Many young Australians feel like they’re “renting their future” rather than owning it, leading to what Scopelliti calls Australia’s quarter-life crisis the collision between expectation and reality.

The Quarter-Life Crisis Explained

Young adults are entering the workforce with degrees, debts, and digital skills but facing an unstable future. “They’re entering adulthood with housing insecurity, job automation, and delayed independence,” says Scopelliti.

To change course, he believes Australia must invest in adaptability through education reform, AI literacy, and fairer housing policies.

How AI and Automation Deepen the Divide

Artificial intelligence is reshaping the job market and not always for the better. According to Rocky, early career roles once used to save for a home deposit are now being automated.

“Entry-level and clerical roles, once the first step to saving for a deposit, are now among the most vulnerable,” he notes.

Generations burdened with student debt, millennials and Gen Z, are seeing traditional milestones like home ownership and family life slip further away.

Adapting to a Faster Future

Despite the challenges, Rocky remains optimistic. “Hope isn’t cancelled, it’s just under renovation,” he says.

He believes the best response to uncertainty is agency. Australians, he suggests, should focus on adaptability, digital skills, and policies that promote equity in housing and work.

“Live deliberately, not defensively. The future isn’t happening to us we’re still writing it together.”

A Final Thought

As Rocky reminds us, “The best thing about the future is that it hasn’t happened yet.” In the words of Back to the Future’s Doc Brown: “Your future is whatever you make it so make it a good one.”

Article supplied with thanks to Sonshine.

Feature image: Canva

Artificial intelligence (AI) is no longer just a buzzword. It’s transforming workplaces across the globe.

 Futurologist Rocky Scopelitti shares his insights on how AI is reshaping jobs, industries, and the way we work.

AI once sparked fear and skepticism. But Scopelitti says the conversation is shifting. “We are shifting into a mindset of acceptance…people are now asking questions about how to make the most of this tool.”

Instead of resisting, workers are experimenting with platforms like ChatGPT and Gemini. Curiosity is replacing caution.

A Workforce in Transition

The workplace faces two massive shifts at once. First, an aging workforce. By 2030, one in six people worldwide will be over 60. Second, the arrival of AI natives. “We are now starting to see the first generation of AI natives coming into the workforce.” These young professionals will only know a workplace shaped by AI.

AI as a Teammate, Not a Threat

Older workers prefer human collaboration. Younger workers lean on AI tools. But most people want a balance.“A vast majority across all age groups actually prefer an even mix of human and AI collaboration.” Scopelitti encourages viewing AI as a “co-teammate” rather than an intruder. This mindset shift is critical for growth.

The Liberation of Work

AI isn’t just about automation. It’s about liberation. “We’re being liberated of mundane tasks so we can focus on human creativity and critical thinking.” This frees time for meaningful, higher-value work. It also helps close skill gaps in industries like healthcare, education, and construction.

Industries Feeling the Impact

Healthcare is a prime example. “Sixty percent of healthcare workers’ activities are administrative…if you could automate 20%, that frees up skills for patient care.” AI can also help teachers, improve access for people with disabilities, and support lifelong learning in the workplace.

Embracing the Future

Australians are proving quick to adopt. Scopelitti notes the trend is clear. “It liberates us of the mundane stuff…and frees us up for the stuff that we love doing.” While fears remain, AI is already reshaping how we work. The challenge is to welcome it as a partner, not a replacement.

Article supplied with thanks to Sonshine.

Feature image: Canva

The pace of change in artificial intelligence is breathtaking. In just a few short years, AI has shifted from a novelty to an invisible layer in our daily lives.

From workplace emails and meeting notes to wedding vows and condolence messages, the technology is no longer just an office tool – it is shaping how we communicate, connect and even think.

The drivers of this shift are clear: rapid tech innovation, a generation raised on digital tools, and social norms bending around new possibilities. But there is an urgency here. As AI moves from helping us to think to doing the thinking for us, leaders and professionals need to ask a confronting question: what happens to our own cognitive muscles if we stop using them?

Here are 5 trends or implications to consider:

1. Outsourcing Thought: The Rise of ‘Digital Amnesia’

One of the most striking findings comes from a recent MIT study. Students using AI tools to draft essays showed a 47 per cent drop in active brain engagement compared to those writing unaided. Even more concerning, 83 per cent of AI users couldn’t remember what they had written just days later, versus only 10 per cent of students who had done the work themselves. Teachers are noticing it too. A Grade 10 English teacher in Australia observed that students relying on AI for drafts struggled to explain their arguments in class – they had outsourced the thinking, and it showed.

This isn’t limited to schools. Many professionals are letting AI write their emails, summarise meetings and even make decisions. The danger isn’t just the quality of the output, but what is happening in our heads. When we hand over the hard work of thinking, memory and reasoning to a machine, we become passive passengers in our own thought process. Like any skill, cognition is use it or lose it.

2. Homogenised Voices: When Everything Starts to Sound the Same

If you have noticed that social posts, emails and even dating profiles are starting to sound eerily similar, you are not imagining things. When millions of people use the same tools trained on the same datasets, originality gets sanded down.

AI-generated text is often competent, even elegant, but it lacks the quirks and rough edges that make human communication feel real. A University of Arizona study found that when people were told a “thoughtful” message from a friend was AI-written, they felt less connected to the sender even if the words were perfect. In an age where connection is currency, this matters.

The same risk exists in workplaces. If every presentation, report and client email starts to carry the same AI polish, it becomes harder to stand out or build trust. Ironically, in a world filled with machine-generated content, the messy fingerprints of a real human voice become a competitive advantage.

3. The Loneliness Loop: AI Companions and Emotional Skills

Seventy-two per cent of teens now use AI for companionship. Apps like Replika, with over 30 million users, offer AI “friends” and even romantic partners. On the surface, it seems harmless – a way to fill the loneliness gap so many young people report. But there is a hidden cost.

Real relationships are hard. They involve compromise, patience, missteps and making up. They require us to grow empathy, negotiation skills and emotional resilience. AI companions offer connection without any of that effort. They never argue, never need forgiveness, never ask for anything in return. They are there to serve you and you alone.

If human relationships are the training ground for emotional intelligence, what happens when a generation learns connection through algorithms that demand nothing of them? For workplaces, this could mean employees entering the workforce with technical brilliance but underdeveloped interpersonal muscles. The skills leaders prize (collaboration, empathy, conflict resolution etc) are forged in the friction of real human interaction.

4. The Education Gap: AI Literacy as a New Divide

Schools are in the middle of a live experiment. Some are embracing AI as a learning tool. Others are banning it entirely, seeing any use as cheating. But even in schools with strict bans, students are finding workarounds. Tools like Quillbot let them rewrite AI-generated content to avoid detection, creating a game of cat and mouse.

The real danger isn’t just plagiarism. It is the widening gap between students who learn how to use AI well and those who don’t. AI literacy is fast becoming as essential as reading and writing. At the same time, those who become over-reliant on AI risk losing the ability to think critically without it.

This divide won’t just shape classrooms – it will flow into workplaces. Organisations will face a new split: employees who can think with AI as a partner, and those who have been shaped by it into passive operators. It is a new kind of literacy gap, and it is opening fast.

5. Communication on Autopilot: When AI Speaks for Us

By next year, forecasts suggest more than 80 per cent of our everyday communication will be AI-assisted. Google’s Gemini platform has already rolled out a feature where the AI will call local businesses on your behalf to book appointments, gather prices and report back. It is convenient and, for many of us, a relief. But every time we hand over a conversation, we lose a little of the social skill it takes to navigate it ourselves.

This is a subtle erosion that mirrors what we have seen with other technologies. Spend years driving a car with cameras and sensors, and you realise how rusty your parking skills are the moment you switch to a basic hire car. Our ability to persuade, negotiate and build rapport is built on hundreds of small, low-stakes interactions. Automate too many of them and those muscles weaken.

AI taking over the grunt work of communication isn’t all bad. It can remove friction, save time and smooth awkward exchanges. But when it handles too much on our behalf, we risk outsourcing not just what we say, but the very human process of learning how to say it.

AI is not the enemy. Used well, it can free us to focus on the parts of work and life that require uniquely human intelligence – creativity, problem-solving, emotional connection. But the line between augmentation and abdication is thin.

The trends are clear: outsourcing thought leads to digital amnesia, homogenised voices dull connection, AI companions risk emotional skill-building, the education gap looms and communication on autopilot weakens our social muscles.

For leaders and professionals, the lesson is simple but urgent. Use AI as a tool, not a crutch. Keep your brain, your voice and your relationships actively engaged. In a world where 80 per cent of communication may soon be machine-assisted, the most valuable thing you can offer is the 20 per cent that is still unmistakably human.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

Artificial intelligence (AI) is evolving rapidly, reshaping industries and transforming daily life. Professor Rocky Scopelliti, a futurologist, discusses the latest AI advancements and how AI is changing our lives.

The Speed of AI Advancements

“The speed of change is accelerating,” says Rocky. “We’re seeing new interfaces and applications that will change how we live, work, and play.”

AI tools, like ChatGPT, help professionals streamline tasks. This growing reliance on AI is shaping everything from media to personal productivity. AI is most certainly changing our lives.

Are We Close to AI Consciousness?

One of the big questions about AI is whether it will become truly conscious. Professor Rocky explains that we still have a long way to go. “We need to understand what consciousness is—scientifically, philosophically, and technologically—before we can replicate it.”

Since experts don’t yet agree on a definition of consciousness, creating conscious AI remains a major challenge. “We need protections in place,” he warns. “We don’t want to find out by accident that we’ve developed consciousness-based AI.”

Understanding AI Agents

AI comes in different forms, known as AI agents. Rocky outlines four types:

• Reactive Agents – Follow predefined rules without learning from past experiences.
• Deliberative Agents – Plan actions based on an internal model of the world.
• Learning Agents – Improve performance using machine learning techniques, like self-driving car AI.
• Multi-Agent Systems – Networks of AIs that collaborate to solve complex problems.

These agents are already impacting industries, from chatbots to fraud detection.

Industries Most Affected by AI

“Every industry will be impacted by AI in some way,” Rocky states. Key sectors include:

• Finance – AI-driven trading, fraud detection, and investment advisory services.
• Healthcare – AI assisting in diagnostics, patient monitoring, and personalized treatments.
• Gaming – AI-powered environments and personalized gaming experiences.
• Education – AI is reshaping learning, much like how calculators changed mathematics education.

The Future of Jobs

With AI automating many tasks, people worry about job security. But Rocky offers reassurance. “AI won’t replace humans, it will work alongside us. Analysts predict AI will automate 40% of workplace tasks by 2035, but it will also create 97 million new roles by 2025.”

Australia, for example, already faces a shortage of 200,000 skilled workers in tech fields, including cybersecurity and renewable energy. “The demand for AI-related skills is huge,” he says. “We need to prepare for these new opportunities.”

Preparing for an AI-Driven Future

To stay relevant in the AI era, individuals and businesses must adapt:

• Students – Gain AI literacy to prepare for emerging careers.
• Professionals – Master AI tools to improve productivity.
• Businesses – Implement AI-driven workflows for efficiency.
• Entrepreneurs – Build AI-first companies that leverage automation.

“The key is to stay proactive in learning and developing new skills,” Rocky advises.

AI in Daily Life

AI already influences everyday experiences, from Netflix recommendations to Spotify playlists. “Entertainment is one of the most exciting areas,” says Professor Rocky. “AI can now create entire movies and personalise content in ways we’ve never seen before.”

As AI continues to evolve, it will shape everything from how we work to how we play. The key is embracing its potential while ensuring ethical and responsible development.

Article supplied with thanks to Sonshine.

Feature image: Canva

In an era where artificial intelligence (AI) is evolving at speed, its influence across nearly every part of our lives is hard to ignore.

One fascinating frontier? AI’s leap into humour—a space we’ve long thought of as uniquely human. But AI systems are now trawling vast datasets to learn what makes us laugh, creating both new possibilities and a few red flags in how we interact with machines.

The Science Behind AI-Generated Humour

Humour may be deeply human, but it follows patterns that machines can learn. By analysing data on what content people like, share, or react to with laughter, AI models are getting eerily good at figuring out what tickles our funny bone. Platforms like TikTok are a prime example—its algorithm personalises your feed so well it feels like the app gets your sense of humour better than your mates do.

Whether you love dry wit, sarcastic one-liners, or totally bizarre memes, AI isn’t just learning comedy—it’s tailoring it.

The Commodification of Comedy

But this isn’t just a cool tech trick. It’s big business. Humour keeps us on platforms longer, drives up ad revenue, and builds loyalty. Some AI chatbots—Claude, for example—are gaining a fan base not just for their intelligence but their charm.

And it works. The more human AI feels, the more time we spend with it. That’s valuable time platforms can monetise through advertising, data collection or paid services. In the race for attention, AI that can make us laugh might just win.

The Echo Chamber Effect: When Jokes Go Stale

Of course, there’s a catch. AI doesn’t actually understand comedy. It just identifies patterns in what’s worked before—and repeats them.

That’s a problem. The more AI leans on what we’ve previously found funny, the more likely it is to keep recycling the same styles of humour. And while that might work for a while, it eventually becomes stale.

Because the best comedy is surprising. It’s an unexpected turn, a weird observation, or a punchline that catches you off guard. If AI sticks too closely to what’s already worked, it risks draining humour of its most important ingredient—novelty.

Can AI Actually Be Funny?

Some tools are making headway. Take Witscript, an AI comedy assistant developed by a stand-up comedian—it produces jokes that human judges found funny around 40% of the time. That’s a solid start.

But still, humour isn’t just about timing and structure. It’s steeped in emotion, culture, irony, and shared context. AI can remix jokes, sure—but it doesn’t livein the world. It doesn’t have awkward dating stories, political gripes, or memories of a family Christmas gone off the rails.

The Future of AI and Humour

AI will almost certainly get better at making us laugh. The bigger question is whether it’ll rob humour of what makes it magical in the first place. Not because bots will replace comedians—but because our own exposure to comedy might become more predictable, polished, and… boring.

The challenge is to use AI as a tool to expand how we enjoy humour, not flatten it. If we can keep that spark of unpredictability, diversity, and silliness alive, AI won’t ruin comedy. It’ll just give us new ways to enjoy the ride.

So—can AI be funny? Yes.

But will it ever get the joke? Time will tell.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image:  Photo by Andrea De Santis on Unsplash