Ten Years Ago I Made 72 Predictions About 2026. Here’s the Honest Report Card — and What 2036 Actually Looks Like

By Futurist Thomas Frey

A decade-old list, graded in real time — plus the next ten years

Back in August 2016, I sat down and published a piece called “72 Stunning Things in the Future That Will Be Common Ten Years from Now That Don’t Exist Today.” I covered 3D printing, VR, drones, driverless cars, the Internet of Things, health tech, AI, and transportation. I gave myself a decade. The decade is up. Time to pay the bill.

The short version: some of it landed almost exactly right. Some of it was right in concept but wrong on timing. A few items missed completely. And one category — AI — I almost certainly undersold rather than oversold, which is the kind of mistake I find most interesting to examine.

The Solid Hits

The VR and AR predictions held up remarkably well. Theme park rides mixing physical experiences with VR — fully real and widespread. Live sports in virtual reality — done, including NFL, NBA, and soccer broadcasts. VR therapy for physical and psychological conditions — now a recognized clinical modality used in hospitals for pain management, PTSD treatment, and phobia exposure therapy. VR and AR tours in real estate — completely standard. That entire category was largely on target.

The health tech predictions also aged well in aggregate. Telehealth checkups without a doctor’s appointment — COVID accelerated that from a nice-to-have to a healthcare pillar almost overnight. AI-controlled prosthetic limbs — real, advancing rapidly, and genuinely changing lives. Ingestible data collectors with sensors — early commercial versions exist, and continuous glucose monitors have become mainstream for diabetics and increasingly popular among health-conscious people who aren’t diabetic at all. Real-time blood scanners are still evolving, but the direction was right.

The drone predictions were solid, particularly fireworks launched from drones — that specific prediction now has an entire FAA-approved industry behind it, with pyro drones appearing at major stadiums and city celebrations across the country. Bird-frightening drones for agriculture, livestock monitoring drones, and drone use in entertainment all landed as predicted. Drone racing viewed through VR headsets became a legitimate organized sport with professional leagues and broadcast deals, another clean hit.

On AI, I predicted that best-selling books and legal documents would be written by artificial intelligence, that AI would select movies, music, and menus based on personal preferences and moods, and that AI hackers would emerge as a serious threat. All of that is not just real — it’s so thoroughly embedded in daily life that most people have stopped noticing. Netflix recommendations, Spotify playlists, AI-drafted contracts and briefs — these are baseline expectations now, not futuristic concepts.

Biometric payment systems were on my IoT list, and fingerprint and face recognition payments are now so standard they barely register as technology. 360-degree video cameras at major urban intersections are common in cities worldwide. Everywhere wireless connectivity — through Starlink, expanded cellular infrastructure, and other systems — is now real and still expanding. Robotic bricklayers are operational. And a privacy bill of rights materialized, though unevenly — GDPR in Europe, CCPA in California, and an ongoing global patchwork of digital privacy regulation that continues to evolve.

 

The Partial Hits — Right Direction, Wrong Timing

Driverless cars are the most prominent partial credit. I predicted driverless car hailing apps, large fleet ownership of autonomous vehicles, and in-car work and entertainment systems — all real, but not yet common in the way I imagined. Waymo is operating in a handful of U.S. cities. Tesla’s robotaxi network is expanding. But the mass adoption I envisioned by 2026 hasn’t arrived. The technology largely works. The regulatory framework, insurance ecosystem, and public trust are still catching up.

I predicted crash-proof cars, specifically citing Volvo’s pledge to achieve that by 2020. That was not met. Advanced collision avoidance systems are now standard on most new vehicles and are saving lives — but truly crash-proof is still a work in progress. EV charging in under five minutes is not yet standard, though the technology is advancing rapidly and that milestone is genuinely within reach in the next few years.

3D printed replacement teeth and custom-fitted shoes and clothing from in-store scanners exist in prototype or limited commercial forms, but haven’t reached the mass retail ubiquity I described. Same-day dental crowns printed in-office are now common in dental practices, so the teeth prediction is closer than it looks. The clothing and shoes have the technology behind them but the consumer journey hasn’t fully standardized. These feel like 2028-2030 arrivals rather than 2026 ones.

The smart IoT household items — smart beds, smart plates tracking nutrition, smart mailboxes — have partial implementations but haven’t reached the seamless mass-market penetration I expected. Eight Sleep’s smart mattress is a real product used by hundreds of thousands of people. Continuous glucose monitors track what you eat and how your body responds. The infrastructure is forming; the widespread daily use hasn’t quite arrived.

The Misses

Hyperloop — ultra-high-speed tube transportation — was prediction number 64, and I said it was something “the only thing lacking is a few people capable of mustering the political will to make it happen.” A decade later, most hyperloop ventures have quietly folded or dramatically scaled back ambitions. Virgin Hyperloop shut down its passenger program. The technology proved far more expensive and complex than its promoters suggested, and the regulatory and infrastructure challenges were even more formidable than I acknowledged. That one missed.

Electric cars winning the Daytona 500 and Indy 500 hasn’t happened. Electric racing series exist and are growing — Formula E is real and exciting — but the major traditional races haven’t converted. That was probably too specific a prediction, conflating the trajectory of EV adoption with the far more conservative pace of change in established motorsport institutions.

Personal drone transportation — unmanned aviation for individual people — I listed as prediction 57, and while eVTOL air taxis are being tested and certified, they are not yet common by any definition. This one needed more time, and the honest timeline is probably closer to 2028-2032 for meaningful urban deployment.

Self-retrieving shoes and robotic follow-behind luggage were creative ideas that haven’t materialized in any practical sense. Some prototype robotic luggage exists. Nobody is calling their shoes by name yet.

What I Undersold

The AI section is where I was least bold, not most bold. I predicted AI-written documents and AI content recommendations — which happened exactly as described. But I completely missed the civilizational magnitude of what large language models would become by 2026. I didn’t predict that AI would write code well enough to replace junior programmers, that it would generate photorealistic images on demand, that it would hold multi-hour conversations indistinguishable from human interaction, or that the entire global economy would be reorganizing itself around AI adoption in real time. My AI predictions were right but timid. The future was much bigger than the list.

 

What 2036 Actually Looks Like

The lesson from grading the 2016 list is that transformation usually arrives on schedule — just unevenly distributed. Things that seemed far off are already here for some people. Things that seemed imminent took longer than expected. With that humility established, here is where the next decade is heading.

By 2036, humanoid robots will be genuinely common in warehouses, hospitals, and manufacturing settings, and will be beginning to appear in homes. The Optimus, Figure, and other platforms being tested today will have completed their first commercial deployments and will be in their second and third hardware generations. The workforce disruption this creates will be the dominant political and economic story of the late 2020s and early 2030s.

Autonomous vehicles will have finally crossed into genuine mass adoption in most major cities. The regulatory and insurance frameworks that have delayed deployment in 2026 will have been resolved by necessity — too many people will have used autonomous ride services in too many cities for the holdouts to maintain their position. Owning a personal car will begin to feel unnecessary for urban residents in the way owning a horse began to feel unnecessary after World War I.

AI will be so embedded in daily professional life by 2036 that describing it will feel like describing oxygen. Every knowledge worker will have AI systems that know their work style, priorities, communication patterns, and professional history. The question won’t be whether to use AI but how to maintain the distinctly human judgment and creativity that AI cannot replicate. That will be the skill that commands premium compensation.

Personal health monitoring will have crossed a threshold where most chronic disease is managed in real time rather than treated after the fact. Continuous monitoring of blood glucose, cardiac rhythms, inflammation markers, and hormonal levels — all via non-invasive wearables — will give individuals and their physicians a real-time biological picture that makes today’s annual physical look like guesswork. Personalized drug dosing and AI-driven treatment recommendations will be standard practice.

Space will have moved from aspiration to infrastructure. The first permanent human presence on the Moon — research teams, not tourists — will be underway. Orbital data centers, powered by solar energy and cooled by space vacuum, will be handling a meaningful portion of global AI compute. The idea that all of civilization’s intelligence runs on Earth will already seem like a transitional phase rather than a permanent condition.

The honest summary of grading the 2016 list is that the direction was right more often than not — the technologies I pointed to were real and consequential. The errors were mostly in the magnitude and timing. I was too conservative on AI and too optimistic on autonomous vehicles and hyperloop. If that pattern holds for the 2036 projection — and it probably will — then the next decade will be bigger than this column describes in some areas, and slower than it describes in others. That’s the nature of forecasting. The future always surprises on the upside in unexpected places, and disappoints in the ones you were most confident about.