Now, for the 8th consecutive year, I’m pleased and excited to share our predictions for the tech industry in the coming year.
As always, before we dust off the crystal ball, you can see what we predicted last year. Tough year as only went 5-4 on our 9 tech-specific predictions and fell right on our faces with the bonus (non-tech) prediction.
Now to the predictions!
AI-native software navigation takes over: By year-end, most B2B SaaS platforms will have embedded Gen AI tools as part of their dashboards. Natural language prompts will quickly become the default navigation tool, and many will see them replace traditional menus and search functions entirely.
Robots will be performing enough “main street” tasks that the average urban dweller will encounter at least one per week in the ordinary course of their day: Autonomous robotics development for dozens of high-leverage use cases, taking place largely behind the scenes for years now, finally hits a sophistication inflection point allowing for scaled deployments across a number of sectors and applications. People will begin seeing these products performing regular tasks in retail, restaurants, universities, hospitals, office buildings, construction sites, and elsewhere.
Big agentic “every solution for every customer” AI companies will see accelerating churn: As enterprise customers grow frustrated with the amount of in-house customization required, and the time and cost of implementation and employee training. This is not to say that AI adoption will slow, rather that enterprise customers will rotate into products that sit within a traditional SaaS framework, purpose-built for their sectors and use cases – i.e., those that come off the shelf capable of solving their companies’ most pressing problems, pre-trained on their industries’ data, with simple and intuitive UIs designed for non-technical personnel to quickly grasp and easily incorporate into their daily workflows.
Companies across the spectrum, from Fortune 500 to 5-person law firms, will begin one of the largest restructurings in corporate history, as they adapt to new AI-powered automation: As AI rapidly replaces rote functions now performed by low-skill and entry-level white collar workers (data entry, scripted/call-center customer service, generic form/document creation, etc.), corporations across all sectors and sizes will have two key problems to address on the fly: 1) How best to re-task and/or retrain these workers to work with and maximize the effectiveness of new AI tools and 2) How to replace the training that entry level workers in sectors like law and finance currently get from performing these rote tasks (e.g., how do you teach first-year legal associates how to draft documents when you don’t need them to draft any of your documents?).
A new breed of cybersecurity company will emerge and rapidly scale in response to a massive increase in the volume and sophistication of spam, phishing, deep-fake, and other predatory AI bots: This should hopefully be self-explanatory, but we would just add 1) If you think the central plot point of HBO’s original Mountainhead was far-fetched, well, we respectfully (and fearfully) disagree, 2) Don’t think twice, think 10 times before you click on any emailed link. We’re way (way) past the days of Nigerian princes offering commissions for moving their money, 3) Royalty-free product/company name idea for you founders: “Bot or Not” (no one under 40 will get the joke but trust us, this will crush with the average middle-aged corporate decision-maker).
Social media influencers will resign in large numbers as AI-created content takes over and replaces them: AI doesn’t do true creativity (or really anything close to it), but it’s great at repackaging generic media into other generic media, and it is considerably less expensive than most of these folks.
Anthropic will not IPO in 2026: On the one hand, Anthropic appears (from a 20,000-foot level, anyway) to have a far more sound/sustainable business model than its LLM peers (high-quality enterprise revenue, real growth, and some light at the end of the burn tunnel). On the other hand, it would be crazy to think public markets will readily embrace its current $350 billion valuation (let alone one that generates a real return for those who participated in that round). But even if it did, why would they subject themselves to the administrative burden and intense quarterly scrutiny of public markets when they can continue to essentially pick any raise and valuation numbers they want and watch the BigTech/BigVC crowd trip over themselves to fill the round with no questions asked?
OpenAI will raise at least one down-round and have to drastically pare down spending and product expansion plans: The current $500 billion valuation is already 6x the largest ever startup exit (before baking in even a modest 3-5x return to VC backers). Will someone eventually top Facebook’s now 13-year-old record? Of course. Will it be by 25x? Absolutely, unequivocally, no.
OpenAI’s revenue size is impressive, but the quality isn’t (60-70% small consumer subscriptions), the company was already forecasting 2026-2029 total burn of $115B before announcing an additional $1.4 trillion in hardware spending commitments, and that burn forecast is based on truly fantastical revenue projections (for context, their projected 2030 revenue is almost double the entirety of 2024 U.S. business software spend).
To be clear, though, they still have a great product with a lot of promise, they just need to start running the company like a real business instead of a science fiction fantasy (and pick a lane or two to dominate, rather than throwing billions at every idea that pops into someone’s head), so a harsh reality check will be a good thing for the company, long-term.
We will hit new public market highs in the first half of the year: Bubbles don’t pop when everyone is talking about bubbles popping, they pop when everyone throws in the towel on predicting a top and goes into full FOMO buying mode. Plus, markets like it when interest rates are in a downward cycle and the most recent Fed “dot plot” indicates another 50-100 basis points of cuts in 2026.
The bubble will burst in the second half of the year and take down the economy with it: Direct AI spending alone has accounted for 70% or so of GDP growth this year, and that doesn’t account for all of the secondary spending by those reaping the benefits of this boom. How bad a recession we end up in is anyone’s guess, though.
On the one hand, this boom is being financed by cash-rich public tech companies (who can easily absorb any losses), and private equity and private debt funds. So, banks have minimal direct exposure, and the average American has essentially none.
On the other hand, 50% of consumer spending (the other pillar of GDP growth) comes from the 10% of Americans who are going to take this AI crash full in the face, so… fingers crossed?
Bonus (Non-Tech) Prediction: The U.S. will make the semifinals of the World Cup for the first time: We’re not counting the inaugural event in 1930 when there were only 13 teams and 3 rounds).
World Cup hosts pretty much always outperform, including the 1994 U.S. team, which was made up entirely of college players (MLS didn’t start play until 1996) who not only inconceivably made the Round of 16, but barely lost (1-0) to eventual champs, Brazil.
For you younger readers, it’s hard to explain just how shocking this was at the time. In 1994, not only did we not have a professional soccer league or any professional soccer players, you couldn’t even find soccer on TV (from anywhere). It wasn’t just a relatively unpopular sport in the U.S.; it basically didn’t exist.
Well, now, we have a thriving domestic league, incredibly high-level play in all manner of development leagues and academies, and a national team full of regulars on top European clubs.
Is this still a reach? For sure. Completely crazy? No. Make us proud, fellas.
There you have it, folks, our 2026 predictions are laid out and Happy New Year!
