University of Kwazulu-Natal

Beyond The Hype Predictions That Could Define 2026

Bonisiwe Shabane
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beyond the hype predictions that could define 2026

For Americans who felt 2025 was a ceaseless storm of norm-challenging change, there may be balm in the celebrations of the republic’s 250th birthday on July 4. But more soberly, 2026 will also be marked by Supreme Court decisions that could upend the very foundation of our democracy. Will work insecurity grow as AI matures from loud infancy into a tricky “technolescence”? What will memes have to teach us? And what about that new musical genre bubbling out of Asia? Bruin experts cast a light on the path ahead.

UCLA Anderson School of Management macroeconomist Clement Bohr predicts the economy will remain largely “frozen” out of the gate but will see improvements as the year progresses on the back of fiscal and monetary... His overall general outlook is “rosy, with stimulations from the Big Beautiful Bill working through, if — and it’s a big if — administration polices remain stable and predictable.” Bohr, an adjunct professor of global economics and management, is monitoring talk of an artificial intelligence bubble — just seven AI-fueled companies account for a third of all Wall Street wealth. But Bohr believes the tech giants are so flush with cash that even if some spending is kept off balance sheets through “special vehicles” created by often-veiled private credit concerns, the companies “can ride... “Right now, these giants generate about $60 billion a year in AI-related revenue,” Bohr says. “But by 2030, to keep up with rising chip power and costs, that will have to be between half a trillion and a trillion dollars.”

A leading researcher behind the internationally cited UCLA Anderson Forecast, Bohr is most concerned about the forthcoming Supreme Court decision as to whether a president can replace board members of the long-independent Federal Reserve... “Economics is a social science, not a hard science, but one certainty that unites all economists is that subjecting federal money policy to political rather than business cycles, typically lowering interest rates for election... (Turkey’s hastily lowered interest rates resulted in 87% inflation; its interest rates are now around 38%.) “We have not hit the Fed’s inflation target for five years, and even a slight signal about loss... 2026 will see AI boost research across many areas, especially biomedicine. But there will be a price to pay and a need to consider the toxic side effects as it grows from loud infant into hungry teen, says Ramesh Srinivasan, professor of information studies at... It’s not just land, water, electricity and overexcited marketing that are key factors, but also AI’s social justice and social-psychological effects.

Can we keep up with the rapid changes, with governments willing or capable of shielding us from the dark side of this new wave of technology? Says Srinivasan: “We may start to find out in 2026.” The conversation around artificial intelligence has long been a deafening chorus of hype, promising a future of boundless, world-altering potential. But as we enter 2026, that chorus is fading. A new, more sober tone is taking its place. The era of “AI evangelism,” as experts at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) call it, is over.

In its place comes a necessary reckoning: the era of “AI evaluation.” This is not a sign of failure, but of maturation. The coming year will be defined not by speculative promise, but by a demand for rigor, transparency, and a long-overdue focus on actual utility. The central question is shifting from a wide-eyed “Can AI do this?” to a clear-eyed “How well, at what cost, and for whom?” Here, we cut through the noise to explore five of the most surprising and impactful predictions from Stanford’s leading thinkers. These insights reveal an industry confronting its real-world limits and capabilities, setting the stage for more meaningful—and measurable—progress.

Contrary to predictions of a dramatic crash, Stanford HAI Senior Fellow Angèle Christin foresees a course correction. The “manic tone” of AI advertisements will give way to a pragmatic realism. We are beginning to understand AI not as a magic bullet, but as a powerful tool that is brilliant for some tasks and problematic or only moderately useful for others. This new realism will be enforced by hard data. Evidence of the “tremendous environmental costs” of the current AI buildout is becoming undeniable, and studies are showing how AI can misdirect or deskill its users in certain contexts. Christin notes that the true impact will be a mixed bag of “some efficiency and creativity gain here, some extra labor and tedium there.” For investors and developers, this means the game is no...

The pace of technological change is accelerating at a dizzying rate, driven largely by advancements in artificial intelligence. According to Gartner, 82% of technology leaders agree that the pace of change within their organizations is accelerating rapidly, reflecting the speed of AI innovation itself. While the market is saturated with discussions about AI, the most significant and transformative shifts are often the most misunderstood. This article cuts through the noise to reveal five surprising, counter-intuitive, and impactful takeaways from Gartner's 2026 planning guides. These insights challenge conventional wisdom on everything from workforce planning and AI governance to the very nature of data analysis and cybersecurity. Together, they offer a clearer, more strategic picture of the technological landscape ahead.

The common assumption is that AI-driven productivity gains will lead to smaller teams. However, the opposite is more likely: the efficiency AI brings will actually increase the demand for more software engineers. This phenomenon is an example of the Jevons Paradox, where increased efficiency in using a resource leads to greater overall consumption of that resource. Just as a more fuel-efficient car can lead to more driving, higher developer productivity leads to a greater demand for AI-empowered software. Gartner forecasts that the enterprise application software market will grow at a compound annual growth rate (CAGR) of 13.9% through 2028. This explosion in demand for new software is projected to outstrip the productivity gains from AI, requiring more engineers, not fewer.

As resource efficiency improves, it stimulates demand and expands the scope of resource utilization instead of reducing overall usage. For the seventh straight year, we’ve sifted through the forecast landscape to bring you the Prediction Consensus, a synthesis of what analysts, thought leaders, and industry experts expect for the year ahead. This year, we analyzed over 2,000 individual predictions from a wide variety of sources including Morgan Stanley, Goldman Sachs, the IMF, The Economist, Deloitte, Microsoft, Gartner, and dozens more. By mapping where these forecasts overlap, we’ve distilled the noise into 25 high-conviction themes displayed in our “Bingo Card” format, with the number of dabs reflecting the volume of supporting predictions. If 2025 was a year of adjustment—markets recalibrating to higher rates, geopolitics reshuffling around a second Trump administration and tariffs, and AI moving from hype to deployment—then 2026 is shaping up as a year... The consensus mood is cautiously optimistic but shot through with uncertainty.

Morgan Stanley describes 2026 as “The Year of Risk Reboot,” a period where market focus shifts from macro anxieties to micro fundamentals, creating fertile ground for risk assets. The policy backdrop is unusually supportive: fiscal stimulus, continued (if slower) monetary easing, and deregulation form what analysts call a “policy triumvirate” rarely seen outside of recessions. PLUS: What I got right (and wrong) about 2025 As 2024 came to a close, I noted here that two big stories were beginning to crowd out everything else in tech: the rapid development and diffusion of artificial intelligence, and the shifting policies... Twelve months later, those stories did indeed define the year here at Platformer. On the product side, this year saw the first consumer agents, deep research, Google’s AI mode, OpenAI’s hardware ambitions, Sora, and the Atlas browser, among other key developments.

Meanwhile, AI policy got both looser and more restrictive. Frontier AI labs eagerly made deals with the US military, reversing long-held policies against building weapons of war, and began leaning into adult content, from erotica in ChatGPT to Grok’s sexbot companion. On the other hand, amid rising evidence that chatbots were fueling a new mental health crisis, AI companies placed new restrictions on teen use and added parental controls. All that took place against the backdrop of the new Trump administration, whose impact on the tech world was felt almost immediately. The year began with Meta’s surrender to the right on speech issues, a move that included changing its policies to allow for more dehumanizing speech against minority groups. It also killed its DEI program, a move followed by many of its peers, and shut down systems that once prevented the spread of misinformation.

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