How AI, Hype and Fear Built a Profitable Perception Economy

the business of selling the future

By Howard Mabhugu

HARARE – IN modern markets, the future itself has become a product. Artificial Intelligence is currently its most successful version. In less than three years, AI transformed from a technical industry discussion into a global psychological event. Governments are restructuring policy around it, corporations are reorganizing around it, investors are pouring billions into it, and workers increasingly fear being displaced by it. Startups now attach the term “AI” to products at extraordinary speed because in today’s digital economy, the label itself carries commercial value.

But beneath the headlines, funding rounds, viral demonstrations, and apocalyptic predictions lies a more uncomfortable reality: AI is not only a technological revolution. It is also a perception economy. The current AI industry increasingly resembles a modern-day gold rush. Historically, gold rushes were never only about gold itself. They created secondary economies built around speculation, urgency, fear, attention, and dreams of future wealth. Some people mined gold while others sold maps, tools, and visions of prosperity. The AI boom is functioning similarly.

Since the launch of OpenAI’s ChatGPT in late 2022, major technology companies entered an aggressive race to secure infrastructure, researchers, and strategic positioning in artificial intelligence. The scale of investment became extraordinary, revealing how valuable AI had become not only as technology, but as narrative power. In March 2024, Microsoft hired Inflection AI co-founder Mustafa Suleyman alongside much of the company’s staff in a deal reportedly valued at approximately $650 million. By 2025, Meta escalated the race further through its multi-billion-dollar investment into Scale AI, strengthening its long-term AI positioning. Google DeepMind later recruited Windsurf leadership and researchers after OpenAI’s acquisition attempt reportedly collapsed.

These deals revealed something deeper about the modern AI economy: the world’s largest technology companies are no longer competing only for products. They are competing for intelligence itself. Machine learning researchers, infrastructure engineers, alignment specialists, and optimization experts have become some of the most valuable workers in the global economy. Compensation packages increasingly resemble those associated with elite athletes and entertainment stars. In the AI era, human expertise itself has become infrastructure.

At the same time, AI evolved into one of the most commercially powerful marketing terms in the world. Across industries, products are increasingly rebranded as “AI-powered” regardless of whether they meaningfully incorporate advanced machine learning systems. Consumers now encounter AI banking, AI productivity suites, AI customer support, AI scheduling assistants, AI cameras, and AI business automation almost everywhere they look. Some of these systems genuinely rely on advanced language models and predictive architectures. Others are little more than conventional automation wrapped in futuristic branding. For ordinary consumers, the distinction is often unclear. The result is what many analysts describe as the “AI-fication” of products: attaching AI branding to technologies primarily to signal relevance, innovation, or future readiness rather than genuine technical transformation.

This pattern is not unique to AI. During the dot-com era, companies rushed to attach “.com” to their identity. During the cryptocurrency boom, organizations inserted “blockchain” and “Web3” into products regardless of necessity or technical depth. AI appears to be following a similar trajectory, though at a far larger scale because AI affects not only markets, but human anxiety itself. That anxiety has become economically valuable. Headlines warning that “AI will replace workers,” “AI will eliminate industries,” or “AI may surpass humanity” generate significantly more attention than nuanced discussions about workflow automation or productivity enhancement. Fear spreads quickly because it compresses complexity into emotionally simple narratives. Millions of people now experience AI primarily through emotional storytelling rather than technical understanding. In the modern economy, fear has become one of technology’s most profitable business models.

Companies benefit from this environment because predictions of unavoidable disruption attract investment, increase valuations, accelerate media attention, and strengthen market positioning long before technologies fully mature. The contradiction is rarely discussed openly: many corporations publicly warn society about the dangers of AI while aggressively accelerating its commercialization behind the scenes. The same companies warning workers about disruption often benefit financially from the fear surrounding that disruption. AI companies are not only selling software. They are selling protection from irrelevance.

Much of today’s AI infrastructure still depends heavily on invisible human labor. Companies such as Scale AI built billion-dollar businesses around data labeling, moderation systems, and human-assisted model training. Behind many AI products are engineers validating outputs, contractors reviewing datasets, specialists correcting hallucinations, and teams monitoring safety systems. The machine appears autonomous from the outside, but beneath the interface, human labor remains deeply embedded within the process. A junior designer refreshing LinkedIn after hearing AI can generate logos in seconds experiences the AI economy very differently from a venture capitalist discussing automation on a podcast.

Even many celebrated AI breakthroughs are less about replacing humans entirely and more about accelerating human workflows inside structured systems. This distinction became particularly visible in 2026 after Mozilla discussed its collaboration involving Anthropic’s cybersecurity-focused model, Claude Mythos Preview. Mythos was introduced as an experimental specialized variant of Anthropic’s Claude systems designed to assist with vulnerability discovery, security analysis, and large-scale code inspection workflows. Unlike mainstream consumer AI products focused on general conversation, Mythos operated within restricted research environments and human-supervised security pipelines. Mozilla later revealed that Mythos-assisted workflows contributed to identifying hundreds of Firefox vulnerabilities, with some reportedly existing inside Firefox systems for more than a decade. Online reactions rapidly transformed the story into evidence that AI systems had surpassed human cybersecurity researchers entirely. Mozilla’s actual explanation was far more nuanced. The system operated within structured engineering review environments involving human verification, oversight processes, controlled tooling, and deployment safeguards. The AI accelerated vulnerability discovery, but human teams remained essential to validating, interpreting, and deploying fixes. Yet nuance rarely spreads as quickly as mythology because narratives travel faster than operational reality.

The AI race is no longer just about building intelligence. It is about controlling humanity’s imagination of the future. Some companies are building genuinely transformative systems. Others are selling emotional proximity to the future. That distinction may become one of the defining economic realities of the AI era. Because beneath the excitement surrounding artificial intelligence lies something deeper than technology itself: a population trying to secure relevance in an uncertain future. Workers fear economic displacement. Students fear choosing obsolete career paths. Businesses fear becoming irrelevant. Investors fear missing the next technological revolution. Entire societies fear falling behind competitors in an accelerating digital economy. AI is not spreading through society purely because people understand it. It is spreading because people fear exclusion from whatever comes next.

History suggests technological revolutions rarely eliminate humanity itself. Instead, they redistribute power, reshape labor markets, redefine valuable skills, and alter social behavior over time. Electricity transformed labor. The internet transformed communication. Smartphones transformed human attention. AI will likely transform decision-making, creativity, productivity, and economic power in similar ways.

But understanding AI requires separating the technology from the mythology surrounding it. The breakthroughs are real. The innovation is real. But so is the business of manufacturing urgency, fear, and future identity around those breakthroughs. The companies shaping artificial intelligence are not simply building tools. They are shaping how societies imagine power, relevance, labor, creativity, and survival in the decades ahead. And in an economy increasingly driven by attention, speculation, and fear, controlling the narrative of the future may become just as valuable as building the future itself.

Howard Mabhugu is a software developer, blockchain developer, and tech podcaster who explores the intersection between technology and society, using his voice to spark meaningful and thought-provoking conversations around digital culture and innovation.

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