It has been three years almost since ChatGPT launched and kicked off a massive wave of AI innovation.
And every single year, venture capitalists have predicted really strong enterprise AI adoption.
But a recent MIT survey in August found that 95 of enterprises weren't getting a meaningful return on their investments.
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It's been three years, like I mentioned, since OpenAI released ChatGPT and with 95 of companies saying they're not seeing a huge return on investment from AI initiatives.
Now I personally think that that could be companies doing it wrong or they're underreporting, or maybe they don't know that every single one of their employees is currently using AI and seeing a lot of productivity gains.
Regardless of all of that, I think the question that a lot of people are asking is when will enterprise recognize AI, the real value from AI, adoption and integration?
So there was a big survey done recently by TechCrunch.
They surveyed 24 enterprise focused venture capitalists and an overwhelming consensus points to this next year 2026, as the year when AI meaningfully breaks through.
That means it's going to deliver measurable value.
It's going to earn larger budgets and allocations.
Venture investors have essentially been making these predictions for a few years.
So I'll, you know, say, take everything with a grain of salt.
And here's why they believe, though, that 2026 is going to be different.
So Kirby Winfield, who is the founding general partner of Ascend, says that enterprises are starting to accept that large language models are not a cure-all.
Just because a company like Starbucks can use Cloud to write internal CRM software doesn't mean it should.
The focus is going to shift towards custom models fine-tuning evaluations observability, orchestration and data sovereignty.
Okay, that's an interesting statement. insight.
Molly Alter, who's a partner at Northstone, said that a subset of enterprise AI startups will evolve from product companies into AI consulting businesses.
Many begin with a focused product like customer support or coding.
Once they have enough workflows running on their platform, they can deploy internal teams to build additional use cases for customers.
In effect, specialized AI products will increasingly become general purpose AI implementation partners.
And I personally believe that you know, a lot of times we're like oh, you know like, what AI tools do you use for XYZ?
I'm a huge believer that it's not going to you know in the near future.
It's not really going to be what AI tools, but just like all the software you currently use is going to have AI built in.
It already, like a large portion of it does, but I think we're going to see further integrations there.
So it's not like, you know, what specific AI tools, just what tools do you use?
Do they have AI in them?
If they're a good tool, if they have a lot of, you know, customers, if they've or successful, they're going to use more and more AI.
Alexander von Tobel, who's the founder and managing partner at Inspired Capital, said '2026 will be the year AI begins to reshape the physical world, especially in infrastructure, manufacturing and climate monitoring.
We're moving from reactive systems to predictive ones, where failures can be detected before they happen'.
Marcy Vu, who's a partner at Greycroft, said, We are particularly excited about voice AI.
Voice is a more natural, efficient, and expressive way for humans to interact with machines.
After decades of typing and staring at screens, speech opens the door to rethinking interfaces, products and experiences, with voice as the primary mode of interactions.
I 100 will agree with Marcy on this.
Ever since AI voice came out on ChatGPT and a lot of other tools.
It's one of my favorite ways to interact with AI models, especially if I'm driving or doing something where I need to be hands-free.
The voice mode is incredible.
And sometimes it's a lot more natural for me to learn about a topic by talking to it than having to sit there and type my messages back and forth.
Now, of course, like if I'm in an environment where I need to be quiet for some reason or I don't want people to hear the whole conversation, I'll do that.
But oftentimes, if I'm in my office, if I'm driving, having a conversation is much faster and more natural.
And I think I therefore get better responses.
Lone Jeff, who is the managing director of Insight Partners, said we are closely watching how frontier model labs approach the application layer.
Many assumed labs would focus only on training models and leave application to others.
Instead, we may see them ship turnkey applications directly into production across finance law, health care and education.
This is very interesting.
We're seeing open AI, right?
They come up with Sora and it's like an entire beyond just the video model.
They came out with an entire social media platform.
So we're seeing some of these bigger companies.
You know, you could look at Anthropix Cloud, where they created Cloud Code, which is, you know, a direct competitor to GitHub and a lot of other players.
So we're seeing, like these, actual applications being built by the AI providers, which is interesting because I think it's very easy for them to see who their biggest consumers are right.
They, you know, Cloud could see that the biggest use case was developers using their code.
There's a whole bunch of different software companies tools that were using clod to help with their coding tools, and so they just built their own, so i do think this is an interesting direction.
Tom hendrickson, who's a general partner at open ocean, said if i had to describe quantum computing in one word for 2026, it would be momentum.
Confidence and quantum advantage is growing as companies publish clearer roadmaps.
That said, meaningful software breakthroughs still depend on further hardware advances.
So when all of these people were asked what areas they were looking to invest in in the coming year, Emily Zhao, who's a principal at Salesforce Ventures, said we're focused on two frontiers AI moving into the physical world and the next phase of model research.
I thought that was interesting.
Michael Stewart, who's a managing partner at M12, said further data center technologies are a major focus over the past year.
We've invested in what we think of as token factory infrastructure.
This includes cooling compute, memory and networking innovations that improve efficiency and sustainability.
John Lair, who is the co-founder and general partner at Workbench, said Really, looking at these very defensible regulated industries, things that are not easily disrupted
Aaron Jacobson, who's a partner over at NEA, said we are reaching the limits of how much energy current GPU infrastructure can consume.
We're interested in both software and hardware that dramatically improve performance per watt, including better GPU management, efficient chip optical networking and thermal innovations.
This is incredibly interesting.
When asked all of these companies because this is one of the biggest questions out there is about startups and their moats they were all asked you know, how do you determine whether an AI startup has a moat?
Rob Biederman, who's a managing partner at Asymmetric Capital Partners, said in AI, defensibility comes less from the model and more from economics and integrations.
We look for companies embedded in enterprise workflows with access to proprietary or continuously improving data and strong switching costs.
Jake Flammenberg, who is a partner at Wing Venture Capital, said.
Molly Alter, who is a partner at North Zone, said vertical AI companies tend to build stronger moats than horizontal ones.
Data moats are especially powerful where each new consumer improves the product.
Workflow moats also matter, particularly in industries with consistent processes like manufacturing construction, healthcare or legal.
Harsha Kappar, who is the director of Snowflake Ventures, said the strongest moats come from helping enterprises reason over their existing data in trustworthy ways.
We look for startups that combine technical depth with domain expertise and deliver insights directly within the governed data environment.
There's a lot going on in the year 2026.
I will make sure to keep you guys updated on all the latest companies, everyone that does raise money, what they're doing, what's happening.
Thank you so much for tuning into the podcast today.
As always, make sure to go check out Delve.com, the sponsor of today's episode.
Thank you so much, and I hope you have a fantastic new year.
