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The footage was real, verified, and delightful: a security camera clip of a coyote bouncing on a backyard trampoline in Los Angeles. Days after the video went viral, near-identical kangaroos, bears, and rabbits began circulating too, all generated by AI. Millions shared them, believing theyd captured another glimpse of animals behaving hilariously. It was an amusing mix-up, but it was also a warning. AI-generated video tools have moved far beyond producing surreal or obviously manipulated clips. They are now convincingly imitating the formats we instinctively trust most: CCTV, dashcams, police bodycams, wildlife cameras, and handheld eyewitness footage. These are the clips that shape public understanding during protests, disasters, violence, and emergencies. And the fake ones are becoming indistinguishable from the real thing. AI-generated realism has already entered the news cycle At Storyful, we verify thousands of real-world videos for newsrooms and brands worldwide. This year we ran a test: we fed real breaking-news headlines from our own platform into one of the newest AI video models. In seconds, we got clips that mimicked the texture and perspective of eyewitness reporting. Not glossy AI experiments, news-like footage that could plausibly land in a newsroom inbox during a breaking story. Side by side with the original real clips, even trained journalists needed to slow down and scrutinize the details. Consider this example, inspired by a verified authentic video posted to social media in the wake of heavy monsoon rains in India: Firefighters Save Man Clinging to Pole Amid Raging Indian Floods A man was rescued on Tuesday, September 16, in Indias Uttarakhand state after spending more than four hours clinging onto an electricity pole as deadly floodwaters raged around him, local media reported. Real: And this fully synthetic video, created by prompting OpenAIs video generator app Sora with the title of the first video. Fake: This is no longer a theoretical future. It is happening right now. Guardrails are already slipping. Tutorials circulate openly on Reddit explaining how to remove the watermark on videos created by one of the most popular AI-video generators, OpenAIs Sora. Restrictions on certain AI prompts can be bypassedwhen they existor models can be run locally without curbs on highly realistic content. And because these tools can create fake CCTV or disaster footage on demand, the question isnt whether AI can generate convincing videos of things that never happened. Its how far will a convincing fake spread before anyone checks it? Why AI-generated videos feel believable The most significant shift in AI-generated video is not just its appearance, but also its behavior. Real eyewitness footage contains the rough edges that come with real life: a shaky hand, the camera pointed at the ground before the action begins, long stretches of nothing happening, imperfect angles and missed details. AI does not yet replicate these moments. It goes straight to the action, framed center-perfect, lit cleanly, and paced like a scene built for maximum impact. It offers the moment we expect to see, without the messy human lead-up that usually surrounds it. The reason is simple. Most models are still trained heavily on cinematic material rather than chaotic, handheld user-generated content. They understand drama better than they understand reality. That gap is what allows verification teams to spot the differencefor now. As models evolve and prompt-writing improves, these behavioral tells will fade. The training data for these video foundation models includes both shaky bystander videos and slick documentaries, allowing them to ably imitate their style and sense of realism. Public confidence is already eroding The Reuters Digital News Report finds that 58% of global audiences fear they can no longer tell real from fake online. That fear used to apply mainly to politics and propaganda. Now it applies to harmless backyard videos. This marks a deeper psychological shift. Once a viewer starts doubting everyday videos, they dont toggle that skepticism on and off. If they question a dog rescue, they will question a protest. If they question a prank, they will question a war zone. Trust doesnt collapse in a single dramatic moment. It erodes drip by drip, through thousands of small uncertainties. And as AI-generated video becomes abundant, authentic footage becomes scarce. How to tell when a video is AI-generated AI detection tools can be a useful part of your workflow, but they are not a replacement for human verification. According to Storyfuls analysis, current tools achieve 6575% accuracy under ideal conditions, but that accuracy drops below 50% within weeks of a new AI model release. These are the signals Storyful’s verification teams use daily, cues the public can learn to recognize quickly. AI starts at the climax.Real footage almost always includes dead time or fumbling before the action. Subjects sit perfectly in the center of the frame.Eyewitnesses rarely capture the chaos of breaking news like cinematographers. Motion is too smoothReal user-generated content stutters, shakes, refocuses, and slips. Timestamps, signage, and license plates break down under scrutinyAI often approximates these details instead of rendering thm accurately. Disaster and wildlife clips look too composed.Real life is uncertain. AI often looks staged. These cues wont hold forever, but right now they offer critical protection. Authenticity is now an asset Tech platforms can add more guardrails to their video generator tools, regulators can update frameworks, detection tools can improve, and so can our own critical faculties. And as newsrooms help audiences navigate through the morass of fakery, the most impactful way they can rebuild trust is to be transparent. Audiences no longer trust sources say. They want to see how a journalist or a newsroom knows something is real. More news organizations are adopting verification-forward formats, including BBC Verify and CBS News Confirmed, which integrate open-source and forensic checks into reporting, examining provenance, imagery, metadata patterns, and geolocation when relevant. Storyful Newswire equips all of our partners with these basic but essential details about every video on our platform. This transparency is becoming the primary differentiator in an environment where AI-generated video is cheap, fast, and everywhere. The more AI-generated footage floods the ecosystem, the more credibility belongs to organizations that make showing their work a key part of the story. The internet’s most unforgettable videos were never perfect. They were unpredictable, flawed, and human, the kinds of moments AI still struggles to imagine. AI-generated footage can now mimic the visual language of truth. But it cannot yet reproduce the randomness of real life. What’s at stake when it does isn’t simply misinformation. It’s the public’s ability to trust what it sees in the moments that matter most. James Law is Editor in Chief of Storyful, a news agency used by 70 percent of the top 20 global newsrooms specializing in verifying breaking news and viral video.
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E-Commerce
We live in a world of increasing change. The international order is shifting and political certainties are evaporating day by day. Technological shifts are changing how we experience the world and interact with others. And in the workplace, AI is poised to unleash what might be the most revolutionary set of changes humanity has experienced since the first hunter-gatherers settled down to grow crops and build cities. But while change is everywhere, we still find it hard to manage. The statistics around organizational change have always been brutal. For at least the last quarter century, corporate transformation efforts have failed at a remarkable rate: only three out of ten are brought to something approaching a successful conclusion. The age of AI will make things even more challenging. We will need to adapt more rapidly and more comprehensively, and we will need to manage multiple layers of continuous change at any one time. How will we cope? Many different factors contribute to making change hard, but one in particular stands out: change is tiring. At the human level, constant transformation depletes our energy, attention, and commitment. At the organizational level, this depletion translates into stalled initiatives, institutional resistance, and a diminishing capacity for further adaptation. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity? ","dek":"Faisal Hoques books, podcast, and his companies give leaders the frameworks and platforms to align purpose, people, process, and techturning disruption into meaningful, lasting progress.","subhed":"","description":"","ctaText":"Learn More","ctaUrl":"https:\/\/faisalhoque.com","theme":{"bg":"#02263c","text":"#ffffff","eyebrow":"#9aa2aa","subhed":"#ffffff","buttonBg":"#ffffff","buttonHoverBg":"#3b3f46","buttonText":"#000000"},"imageDesktopId":91420512,"imageMobileId":91420514,"shareable":false,"slug":""}} To make the process of change navigable for real humansrather than the compliant ideals who often appear in strategy deckswe need to rethink how we understand change. We need to find the stable foundations that persist amidst the maelstrom of transformation. The adaptation fallacy The standard response to the reality of ever-increasing change is to insist that individuals and organizations simply adapt to it. Everything flows, as the ancient Greek philosopher Heraclitus is reported to have said. The world is in flux, nothing is fixed, and we should all get used to the idea that the stability of the past was just a temporary illusion. This ancient wisdom has become something of a cliché, the It is what it is of the business world. It is offered up as a slogan to hold onto, a manifesto that distils the increasingly rapid change of the Fourth Industrial Revolution. But it doesnt do much to help people stay afloat. Human beings are not infinitely malleable. There is a psychological and physical toll to constant, chaotic change that compounds in two distinct ways. The first is the sheer quantity of simultaneous initiativesthe burden of switching between half a dozen transformation efforts at once. People find themselves juggling competing priorities, each with its own vocabulary, metrics, and demands on their attention. It becomes hard to see the big picture because the parts never stay still long enough to focus. The cognitive overhead of keeping track of everything crowds out the close attention that each single initiative requires. The second is the exhausting length of individual change processes that can stretch over many months, or even years. The reasons for the change, once vivid and urgent, become abstract and distant. Champions move on, new people arrive who werent part of the original vision, and maintaining momentum becomes harder with each passing quarter. The demand that team members adapt to the new reality addresses neither problem. The flux pushes and pulls them in different directions with no coherence, giving them no stable ground to stand on. Expecting people to get used to it amounts to expecting people not to be human. Leaders who demand adaptation without addressing the underlying human experience are not solving the problem. They are adding to it. The other Heraclitus Heraclitus has some real wisdom that can help here, but we need to move past the most common versions of his sayings. Heraclitus most famous aphorism is usually rendered as You cannot step into the same river twice. The idea is that when you step into the river, the water flows on and so it is not the same when you take your next step. Panta rhei. Everything flows. But there is another version of this saying that comes closer to capturing what Heraclitus actually meant: We step and do not step into the same river twice. The difference is small, but it matters. Yes, the water flows. Yes, the river is never the same from one moment to the next. But the river itself remains. The river has an identity that persists through its constant flow. There is an important lesson here for organizations seeking to manage change. Recognizing that things flow is important. But we also have to identify and spotlight what it is that persists through that change. Finding, defining, and celebrating the order that underlies the chaos is essential if we do not want to be swept away. The task is not to eliminate fluxthat is neither possible nor desirablebut to identify and preserve the stability that gives change its meaning. Purpose, identity, strategic clarity: these define the organization and give it its identity. They provide the stable vessel that allows people to float happily along on the flowing water rather than being pulled under by the constant motion. Providing this stability is the leaders responsibility. The constants that allow people to navigate change do not maintain themselves. They must be deliberately established, clearly communicated, and actively protected. What leaders must do If change fatigue is not a failure of individual resilience but a failure of organizational design, then leaders must take responsibility for building organizations in which change happens more easily. Here are five principles that can help provide stability in a changing world. Be discerning about what you change. Not every transformation deserves equal energy. The familiar danger of chasing shiny objectsconstantly running from one initiative to the nextundermines the efforts that actually matter. Every proposed change should be tested against the organizations strategic purpose. If it doesnot clearly advance the core mission, it should not be adding to the cognitive burden on your teams. Communicate the why, not just the what. Much of change fatigue comes not from the pace of change itself but from the cognitive burden of not understanding how changes connect. When people cannot see how a new process, tool, or structure contributes to an outcome, changes feel arbitrary and exhausting. Often, even C-suite executives are not fully aligned on precisely why things matter. That confusion cascades downward, multiplying fatigue at every level. Leaders must articulate the purpose behind each initiative and show how it fits into a coherent whole. Build a unified narrative. When organizations pursue multiple change initiatives simultaneously, a unified story smooths the cognitive burden by holding the pieces together. Rather than experiencing six disconnected transformations, people can understand themselves as participating in a single journey with multiple dimensions. The narrative does not eliminate the work, but it reduces the sense of fragmentation. Create systemic anchors that survive turnover. Long-term change efforts may see key leaders depart before the work is complete. If the change depends entirely on individual champions, it will falter when those individuals leave. There must be a process coregovernance structures, documentation, embedded practicesthat can survive personnel changes and maintain momentum independent of any single person. Co-design the change with the humans who must live with it. Change fatigue intensifies when transformations are handed down fully formed, only to collide with realities about which leaders were unaware. Co-design reverses this logic. Frontline staff know the constraints they face; customers know what the change feels like on the receiving end. When the people involved help shape the new way of working that will affect them, compliance turns into ownership, and the change arrives already adapted to the world it must survive in. Principles in practice A clear illustration of these principles being put into successful practice comes from Gold Coast Mental Health and Specialist Services in Queensland, Australia, which undertook a sustained transformation to support the adoption of a Zero Suicide approach. The case is instructive both for the ambition of the goalto permanently shift the culture of a whole health systemand for the care that was taken to make the change sustainable over time. From the outset, the program was framed as a system-wide approach rather than as the heroic efforts of individual practitioners. This distinction matters. When success depends on personal endurance, organizations quietly burn through their people. By treating transformation as a collective endeavor supported by organizational structures rather than individual willpower, the program avoided placing impossible burdens on staff already working in an emotionally demanding field. The new practices were institutionalized, not merely announced. Training reached more than 500 staff and was then embedded into orientation for new hires and supported by online modules, face-to-face sessions, and custom-produced materials designed with the local culture in mind. The change was designed to outlast the people who initiated itthe kind of systemic anchor that keeps momentum alive even as personnel turn over. Crucially, the service built feedback loops to prevent drift. Staff received timely data on adherence to the new pathway, followed by supervision and coaching to embed skills. This continuous improvement cycle meant that standards did not have to be constantly re-litigated; the system itself kept reinforcing what good practice looked like. Co-design was an essential component of the Gold Coast approach. The services culture change strategy explicitly integrates suicide attempt and loss survivors in leadership and planning roles, recognizing that effective prevention requires perspectives beyond those of clinicians. The result is that change is shaped by those most exposed to its failure modes. Gold Coasts transformation success did not depend on asking already-stretched professionals to simply try harder. Instead, the program leaders ensured that their teams could see the unifying structures that provided stability, meaning, and identity through change. Conclusion The 70% failure rate is not a law of nature. It is the predictable result of asking people to navigate constant change without giving them anything constant to hold onto. Purpose, identity, strategic claritythese are not luxuries to be addressed once the real work of transformation is complete. They are the vessel that keeps people afloat. Without that vessel, you are asking your people to swim through every change. And eventually, swimmers tire. Build the structures. Communicate the purpose. Shine a clear and steady light on what endures. That is how transformation succeedsnot by demanding more adaptation, but by providing stable foundations on which to build something new. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity? 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Much to the chagrin of investors, the value of Bitcoin continues to slide. As of Wednesday morning, the world’s most popular cryptocurrency was trading around $75,000 per coin. Thats down more than 10% over the past five days, down 18% over the past month, and down a whopping 34% over the past six months. It’s a far cry from October of last year, when Bitcoins price topped out at nearly $125,000. Values are now roughly where they were in early April 2025, and before that, in November 2024. From bump to slump Notably, Bitcoins value is now lower than it was when Trump took office last January, effectively giving up all of the Trump Bump gains that it and other crypto assets saw over much of 2025. That bump was real, too: Bitcoin returns were down around 12% during Q1 2025, but jumped to nearly 30% during Q2, and then 6.3% in Q3, according to data from Coinglass. The downturn seemingly took hold at some point during Q4, when returns were down 23%. Ethereum, the second-largest crypto on the market, saw a similar trajectory: It saw huge increases (37% during Q2 and 67% during Q3), followed by a big drop in Q4 (down 28%). Here are a few notable crypto slumps year to date as of this writing: Bitcoin (BTC): Down 13.86% Ether (ETC): Down 25.56% XRP (XRP): Down 15.13% Why are crypto values declining? As for whats causing the sell-off? A lot of things, but mostly, investors looking for off-ramps from riskier assets. This can partially be blamed on a government shutdown delaying the release of important economic data (the jobs report was supposed to come out on Friday, but has been delayed), geopolitical tensions rising in many parts of the world, on-again off-again tariff threats, and even the fear of increased regulation on the crypto industry, according to reporting from CNBC. The crypto markets are also caught in the maelstrom of other downturns. The stock market has been flat for the past month, with some earnings announcementsnotably Microsoftscausing fervor and worry among investors. President Trump has also named a new Fed Chair, who if confirmed will take up the position in mid-May, adding another variable of uncertainty into the mix. As a cherry on top, precious metals have seen a steep sell-off, too. Gold and silver prices had shot to the moon in recent months, last week, silver experienced its worst day ever, falling nearly 30%. The confluence of all of these factors is whats led to massive crypto volatility. This story is developing…
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