AI has attracted unprecedented ranges of capital and a spotlight. And questions are rising concerning the so-called AI bubble: Are too many startups chasing the identical concepts? Are valuations working forward of actual adoption? And can all this funding repay — or pop?
GeekWire polled a handful of Seattle-area enterprise capitalists about whether or not they suppose an AI bubble exists, and the way startups ought to put together as they plan for 2026.
Taken collectively, the buyers paint an image of a market that’s overheated in locations, however removed from damaged. They see clear indicators of extra in AI — particularly in early-stage personal corporations the place valuations typically outpace actual traction. However they largely reject the concept of a catastrophic bubble, and most argue that the know-how itself is already delivering actual worth.
They differ on the small print: Some see the most important extra in knowledge middle buildouts. Others level to narrative-driven startups elevating at enormous valuations with out actual buyer traction. One investor places AI’s full affect 10 to twenty years out. One other sees speedy alternative as corporations rethink their software program spending, making longtime distributors susceptible.
Their recommendation to startup founders: ignore the hype, deal with actual buyer issues, construct sturdy income and environment friendly companies, and be prepared for some market cooling.
Learn their full responses under.
Sabrina Albert (Wu), accomplice at Madrona
“There’s clear froth in elements of the AI market, particularly in early-stage personal valuations the place corporations are priced nicely forward of fundamentals, which inserts a traditional ‘bubble’ definition. Within the public markets, the strongest AI corporations are backing valuations with outsized earnings and development, so it doesn’t appear like a standard bubble there.
Essentially the most pronounced exuberance is within the personal markets, notably at seed and Sequence A, the place many buyers are attempting to get in earlier on AI publicity. In consequence, capital is chasing startups with restricted traction and valuations that value in outcomes which will take years of execution to justify.
Startups ought to deal with sturdy enterprise fundamentals early on. Construct repeatable income by annual or multi-year contracts, clear up actual buyer issues, and differentiate by integrating deeply into the shopper tech stack to create actual product and firm flywheels. Lengthy-term success comes from delivering measurable worth and defensible development over time.”
Cameron Borumand, common accomplice at Fuse
“Many components are at play right here. You’ve gotten a brand new and genuinely transformative know-how in AI. Over the long run, it can radically reshape how practically each trade operates. On the identical time, historical past tells us that new applied sciences are usually overestimated within the brief time period and underestimated in the long run. Essentially the most profound, absolutely realized impacts of AI should be 10-to-20 years away.
Within the close to time period (the subsequent few years), I anticipate some pullback within the public markets as buyers come to phrases with the truth that true ‘enterprise readiness’ for AI will take time. This doesn’t recommend something catastrophic — simply that the roughly 21 % year-over-year development we’ve seen within the Nasdaq is unlikely to be sustainable and should revert nearer to the 30-year common of round 10 %. After a couple of significant pullbacks, pundits will inevitably declare that AI is overhyped. In actuality, this could merely signify a normalization after a unprecedented, AI-fueled run within the public markets.
Late-stage personal markets will see some overly hyped corporations — this occurs in each growth cycle. The winners shall be larger than ever, however the losses will even be larger than ever. When you might have corporations like Anthropic rising from $1 billion to a projected $9 billion of income in 2025, it’s clear that AI is already delivering actual, materials affect on the earth.
For startups, there’s no higher time to be constructing than now. M&A markets are again, prospects have finances, and expertise needs to work on fascinating initiatives. With that mentioned, there’s a number of noise, so it’s finest to go deep and actually deal with a core buyer drawback. Many of the development we’ve seen up to now is within the infrastructure layer — the subsequent few years shall be concerning the subsequent technology of AI-powered purposes.”
Chris DeVore, founding managing accomplice at Founders’ Co-op
“Sure, a major quantity of capital being deployed globally in AI (and notably within the knowledge middle buildout) is sort of actually being misallocated. Particularly in startups, outdoors a couple of presumed winners (OpenAI, Anthropic, Cursor), the priority is much less overcapitalization and extra the costs at which financings are being achieved relative to the precise money flows and margin potential of the businesses being financed.
That mentioned, in contrast to some current bubbles I can consider (crypto, metaverse, and so on.) there are precise infants within the bathwater this time. LLMs are remarkably succesful instruments even at their present state of growth, and can stay core to many software program growth and data work duties lengthy after rationality has returned to the monetary panorama.
The founder and investor problem in moments like the present one is the way to make selections that can look sensible ten years from now, not simply within the present second. Are there methods to use LLMs to create sturdy enterprise worth in segments of the financial system that aren’t prone to be overcapitalized or competed to zero by the near-term flood of {dollars}? The one various technique is to attempt to decide winners within the capital wars and pay regardless of the market calls for for these belongings, however historical past means that’s a really low odds proposition for even the most effective gamers.
The recipe for fulfillment in occasions like this isn’t that completely different from another time: decide a buyer phase that you simply perceive higher than anybody else, interact deeply with these prospects to know what issues you’ll be able to uniquely clear up with LLMs that had been too exhausting or costly to resolve beforehand, construct rapidly and iteratively to indicate worth to these prospects, and preserve that tempo of transport and studying for so long as you’ll be able to.
Which will sound easy, nevertheless it’s exceptional how few founding groups are capable of pull it off, and that why startups are so exhausting, and so enjoyable.”
Sheila Gulati, managing director at Tola Capital
“Broadly, I don’t suppose we’re in an AI bubble proper now. Comparable issues existed after we launched the Azure platform about fifteen years in the past. Again then, individuals had been initially anxious about racing to a zero-margin enterprise.
At present’s huge AI infrastructure buildouts will form the operational software program layers that drive real-world efficiency — compute orchestration, knowledge pipelines, reminiscence programs, and large-scale inference effectivity. Worth is shifting towards packaging and deploying intelligence throughout enterprise workflows.
Enterprise software program startups ought to place themselves within the rising TAM of delivering full, end-to-end options and new methods of doing issues the place people collaborate with AI brokers. Successful startups will embody each the rising IT TAM and economics of a portion of the labor market as nicely.
We at the moment are seeing unprecedented malleability of CIO budgets. The deeply entrenched software stack can now shift to new gamers that are constructed with AI from the bottom up. The market alternative is huge, and corporations ought to set their sights on constructing the brand new megacaps, not minor characteristic corporations.”
Andy Liu, co-founding accomplice at Unlock Enterprise Companions
“Sure, we’re in an AI bubble, however not in the best way most individuals suppose.
Capital and valuations are working nicely forward of fundamentals, notably for corporations with out clear buyer pull, sturdy differentiation, or credible/affordable paths to profitability. We’re seeing a rising hole between narrative-driven AI corporations the place ‘AI’ is essentially a positioning train, and value-driven AI corporations that use the know-how to ship measurable, repeatable worth for patrons.
The bubble appears most pronounced on the early and development phases the place AI storytelling can briefly substitute for traction and lift capital at lofty valuations. Some robust corporations will emerge from this cycle, however there shall be significant drawdowns, recaps, or shutdowns as many startups fail to develop into these expectations.
Looking forward to 2026, my recommendation to founders is easy:
- Construct actual companies, not decks. Merchandise at the moment will be constructed rapidly with actual income earlier than elevating capital.
- Prioritize effectivity, buyer ROI, and unit economics.
- Use AI to create actual leverage, not excuses for burning capital.
2026 goes to be an unbelievable second to construct. The price of experimentation and constructing merchandise has collapsed, and founders not want instructional credentials (CS levels or an MBA) to create actual merchandise and income. The subsequent technology of sturdy AI corporations shall be constructed by small groups who focus much less on hype and extra on environment friendly execution. We’re positively excited to see extra groups constructing unbelievable merchandise this upcoming 12 months.”
Annie Luchsinger, accomplice at Breakers
“From my perspective, what we’re seeing is much less an AI bubble and extra a traditional enterprise cycle taking part in out round a genuinely transformative platform shift. Enterprise has at all times tailored to new normals alongside main know-how inflections (cloud, cellular, social), and AI is the fastest-moving one we’ve seen up to now.
The distinction this time is pace, scale, and capital availability. AI adoption is going on at a quicker clip and at a a lot bigger scale than prior platform shifts, all whereas private-market capital has reached historic highs. As these forces collide, pricing, timelines, and investor conduct evolve.
Capital transferring forward of fundamentals isn’t new. There shall be some shakeouts, however that doesn’t imply underlying worth creation isn’t occurring. Corporations with actual know-how, actual distribution, and actual prospects will endure.”
