2026 is the year of tangibility. The gap between technological promise and real-world impact will narrow across AI, infrastructure and marketing. Potential becomes proof. Hype becomes measurable value. Systems get stress-tested. Infrastructure catches up to ambition. And leading companies are the ones building durable foundations: efficient infrastructure, fresh data, credible governance, human trust at scale.
Founders, partners and sector experts across our constellation share what they believe will define the next year of economic dualities, regulation and realignment, infrastructure innovation and tangible outcomes.
TLDR
- AI value becomes measurable. Enterprises will finally show clear ROI from generative AI, agentic systems and automation.
- Infrastructure becomes the real moat. From data centers to developer tooling and physical AI models, the technical foundation of AI becomes the story.
- Fresh, governed data becomes the competitive edge. Right-time pipelines, unified teams and compliant context determine which AI systems scale and which stall.
Infrastructure is the battleground and the opportunity
2026 is the year AI could hit the wall — and efficiency becomes the new competitive frontier.
AI is changing the world but the weight of AI on global infrastructure needs is heavy. 2025 was a year of opulent spending, with large firms trying to outspend each other and Nvidia reaping the rewards in growth and valuation. What’s been overlooked is the technical path required to support such a disruption. In coming years the focus will shift: efficiency, developer tooling and cost reduction will dominate.
What must be considered is the barrier to entry that high infrastructure costs introduce to AI startups and the potential impact on longer-term business economics. I believe 2026 will bring a wave of technologies designed to simplify and reduce costs associated with developing AI businesses — developer tools that improve management of AI and data infrastructure, and infrastructure solutions that solve for efficiency and performance at the chip level.
With predictions that global AI data center demand could reach 327 GW by 2030, the industry can’t brute-force its way forward anymore. The race for efficiency will define the next wave of innovation and separate the survivors from the tourists.
M13 Managing Partner
Karl Alomar
The year asymmetry between AI investment and value ends
Over the last few years, there has been an undeniable asymmetry between enterprise investment in AI and return in value. Lots of money has gone into AI; insufficient value has come out.
In 2026, that asymmetry will change: enterprises will utilize generative AI for internal productivity gains and external customer-facing use cases. Agentic AI adoption will be slower but no less impactful. By the end of the year, companies will be able to point to tangible gains in ROI and demonstrate AI's real world value - and still only be benefiting from a fraction of AI's full potential.
The era of asymmetry is ending. 2026 will be the year that companies see tangible gains in ROI that demonstrate AI's real world value.
Luminos.AI
CEO Andrew Burt
Stale data gets exposed: the AI agent stack forces data to grow up
AI agents are about to expose a truth: models are powerful, but stale data makes them dumb. By 2026, enterprises will shift from batch and ad-hoc integrations toward right-time, unified pipelines that continuously hydrate AI systems with trustworthy context. This reshapes org charts. Data, ML, and application teams converge around shared declarative pipelines instead of handoffs. The downstream effect? A widening performance gap. Companies that deliver fresh, governed data to agents will automate entire workflows; companies that don’t will struggle with hallucinations, compliance issues, and operational drag. Fresh data (not bigger models) becomes the real differentiator.
Estuary Co-founder
Dave Yaffe
The next leap in AI comes from physical models, not bigger LLMs
The march toward AGI has advanced rapidly through LLMs but large language models are hitting natural limits. They’ve processed nearly every written word produced by humanity. While synthetic data represents some room for continued improvement, future foundational model advancement may focus more on efficiency and reliability gains.
The next major step will probably come from physical AI models: systems that learn from the real world rather than text using sensors and cameras to learn how the real world works, much like a human being does through experience. The major advantage over LLMs is the nearly limitless amount of data they can process to continue to learn concepts related to science, medicine and human-to-human interactions, an area of weakness in LLMs.
2026 is the year the path toward AGI via physical models begins in earnest.
M13 Partner
Rob Smith
Systems of action become intelligent through enterprise world models and embodied AI
LLMs have reached the limits of what can be learned from static text, revealing gaps in causal reasoning, multi-step planning and real-world reliability. The next frontier is embodied AI and enterprise world models. These systems learn from interaction data generated by sensors, robots, people and operational workflows, capturing how work actually gets done inside organizations.
Embodied AI grounds models in the physical and procedural realities of the enterprise. World models act as simulation engines that mirror a company’s processes, constraints, exceptions and decision pathways, encoding the same tacit knowledge humans built through experience. Together, they unlock complex agentic decision making and make true systems of action possible: agents that can predict outcomes, test strategies in simulation and autonomously execute multi-step workflows.
In 2026, intelligence shifts from “models that know things” to “models that understand and act within environments.” The winners will leverage world modeling, not model size, to automate knowledge work.
M13 Principal
Morgan Blumberg
Real AI adoption: Doctors moving as fast as software
AI will transform every industry but none more than healthcare, where a decade of digital health hype has mostly fallen flat. That’s finally changing. OpenEvidence is already used by 40% of U.S. physicians just 18 months after launch — doctors have never adopted new technology at this speed. Vinod Khosla 's prediction that AI will perform 80% of the doctor’s work stops sounding theoretical in 2026. Non-clinical busy work will be fully eliminated and, more importantly, we will see real strides in care models delivered by AI. AI nurses and AI doctors - digital twins of our favorite clinician – will become prevalent in 2026 allowing for personalization at scale. Physicians will work at the top of their license and high quality coverage across the population will increase. Consumers already trust AI for healthcare, and will see top down directives from health systems and large care providers.
One thing is certain: every AI model will require living, breathing, continuously generated human data to keep getting better.
M13 General Partner
Latif Peracha
Futureproofing goes mainstream as AI and crypto hit energy, finance and healthcare
I am looking forward to the theme of futureproofing in 2026. The world has woken up to the fact that AI is real, even if most use cases to date focus on our insular tech world. Similarly, crypto continues to gain adoption, although on a quieter note. 2026 is the year where we see AI and crypto expand into the real world to solve complex problems that affect society - beyond just the tech world. Rather, the next wave of adoption will come from SMBs and historically non-tech forward industries (e.g., energy/industrials, financial services, healthcare), and the opportunity is to facilitate that adoption that obfuscates complexity.
M13 Principal
Mark Grace
CHROs, not engineers, are AI workforce architects
In 2026 AI will no longer be a tool. Companies will embed AI in their strategy as part of what it truly is: a new architecture for how work gets done. The best ones will design agentic workflows from the ground up, deciding which tasks are owned by people, which are executed autonomously by AI systems, and how the two reinforce each other. Doing this well demands a different kind of leadership profile: close enough to the work to understand the nuances of product, operations and customer feedback and experienced enough to architect workflows and decide where human oversight is essential. And it requires a shift in ownership. AI’s impact is organizational, not just technical. These are not engineering questions, they are people questions. CHROs and talent leaders will become stewards of the AI transformation, defining how work gets done in truly AI-native companies.
M13 Partner
Matt Hoffman
Digital marketing changes with the first ChatGPT ad
The first paid ad unit will appear in ChatGPT as OpenAI joins the ranks of the other major ad networks. In many ways, ads have always been inevitable, and recently the company has made inroads to make it a reality, as evidenced here, here and here. As eyeballs and searches continue to accelerate towards OpenAI - which will soon eclipse 1B active users - OpenAI ads will be among the most valuable inventory online. And if you’re planning to fund $1.4T in capex over the next decade, high margin ad revenue really helps. I do not believe OpenAI is looking to copy its predecessors’ ad formats so the second part of my prediction is that the first ChatGPT ad unit will look very different from banners or native ads.
M13 Partner
Brent Murri
From fandom to fulfillment: cultural commerce is the next infrastructure play
Entertainment is the new storefront. Sports docuseries, gaming, collectibles, anime, and micro-dramas are replacing the old commerce funnel with fandom flywheels. In 2026, community is the distribution channel. Success won’t be measured by clicks, but by cultural engagement: retention, shared identity, and participatory behavior.
For infrastructure investors, this convergence of product and entertainment creates opportunity. Platforms that power identity, community and interoperability become the true value layer. Examples:
- Participatory commerce tools that turn fans into buyers and creators into collaborators. Think tokenized loyalty, embedded social checkout and UGC-as-conversion pipelines.
- Community and discovery infrastructure that routes cultural signals into commerce outcomes.
- Media ops stacks for creators and brands to launch and scale like showrunners.
- AI-native orchestration layer for modern brands to automate product sourcing, supply chain ops, fulfillment and marketing.
Cultural commerce is rising. Infrastructure makes it possible and ownable.
M13 Co-founder and Partner
Carter Reum
When algorithms mediate attention, your story becomes your strategy
In 2026, brands won’t just need media: it becomes media, and media now means more than reporters and press coverage. Media is every surface where people form an opinion about and begin to trust you: WSJ, LinkedIn, a podcast, an event hallway, even ChatGPT. We’ll run comms like editorial franchises built on consistent narratives, recurring formats and distribution across owned and earned channels. That’s because algorithmic intermediaries now shape what gets seen and by whom, and they reward clarity and consistency above everything else.
The shift means vanity metrics stop mattering. Consistency beats volume, and narrative clarity means discoverability. Success becomes far more precise to measure: better deal flow, stronger retention, deeper participation. And that’s freeing. When original content is table stakes, the real differentiator becomes human judgment: the relationships we build, the conversations we spark, and the trust we earn in all the places algorithms can’t reach.
M13 Partner
Christine Choi
New York overtakes Silicon Valley
In 2026, New York will emerge as the leading AI startup hub. Vertical AI startups in key categories want to be where their customers are, and New York is a great place to build in some key verticals like fintech, advertising, media, governance, compliance and commerce. As the platform shifts matures, it’s less important to be where the foundational technologies were invented and more important to be where they are getting consumed.
M13 Partner
Anna Barber
AI governance gets teeth
- State AI enforcement starts. We'll see the first wave of meaningful state AI enforcement actions, transforming AI governance from theoretical frameworks to operational necessities as companies scramble to comply.
- AI consolidation. Strategic acquirers and PE firms will begin to systematically roll up the AI companies that raised significant capital the past few years but failed to achieve sustainable unit economics, creating value through consolidation rather than innovation.
- The AI media takeover. AI platforms will become the new foundation that struggling traditional media companies need to reinvent their business models (such as through licensing royalties, production workflows, content creation and distribution), evolving from litigation targets to the infrastructure that studios can’t survive without. Media companies in turn will slowly cede control of the entire media ecosystem.
M13 Partner
Win Chevapravatdumrong
AI filters. Humans choose.
As AI becomes the first line of defense for screening and sorting, in-person interactions will only grow in importance. We are social creatures first and foremost. The last mile of pattern recognition still depends on face-to-face encounters that activate intuition and gut judgment. These are the human capital variables that algorithms cannot solve (yet). They are the pattern recognition je ne sais quoi people recognize when they meet truly special founders or investors.
M13 Partner
Sarah Tomolonius
GLP-1 access and coverage remain a 2026 battleground
GLP-1 prices continue to come down as the government and pharmaceutical companies announce price cuts and new programs that will increase affordability and access for consumers. Coverage and pricing for employer groups remains uneven but is likely to improve as we move into 2026. Questions remain around eligibility and coverage, particularly for Medicare and Medicaid members, and the neverending news cycle is creating confusion across the board. Access is improving, but affordability and consistent coverage remain major hurdles. One thing is clear: treating obesity as a chronic disease, rather than a lifestyle choice, is the key to progress.
Form Health founder and CEO
Evan Richardson
2026 is the year of tangibility. The gap between technological promise and real-world impact will narrow across AI, infrastructure and marketing. Potential becomes proof. Hype becomes measurable value. Systems get stress-tested. Infrastructure catches up to ambition. And leading companies are the ones building durable foundations: efficient infrastructure, fresh data, credible governance, human trust at scale.
Founders, partners and sector experts across our constellation share what they believe will define the next year of economic dualities, regulation and realignment, infrastructure innovation and tangible outcomes.
TLDR
- AI value becomes measurable. Enterprises will finally show clear ROI from generative AI, agentic systems and automation.
- Infrastructure becomes the real moat. From data centers to developer tooling and physical AI models, the technical foundation of AI becomes the story.
- Fresh, governed data becomes the competitive edge. Right-time pipelines, unified teams and compliant context determine which AI systems scale and which stall.
Infrastructure is the battleground and the opportunity
2026 is the year AI could hit the wall — and efficiency becomes the new competitive frontier.
AI is changing the world but the weight of AI on global infrastructure needs is heavy. 2025 was a year of opulent spending, with large firms trying to outspend each other and Nvidia reaping the rewards in growth and valuation. What’s been overlooked is the technical path required to support such a disruption. In coming years the focus will shift: efficiency, developer tooling and cost reduction will dominate.
What must be considered is the barrier to entry that high infrastructure costs introduce to AI startups and the potential impact on longer-term business economics. I believe 2026 will bring a wave of technologies designed to simplify and reduce costs associated with developing AI businesses — developer tools that improve management of AI and data infrastructure, and infrastructure solutions that solve for efficiency and performance at the chip level.
With predictions that global AI data center demand could reach 327 GW by 2030, the industry can’t brute-force its way forward anymore. The race for efficiency will define the next wave of innovation and separate the survivors from the tourists.
M13 Managing Partner
Karl Alomar
The year asymmetry between AI investment and value ends
Over the last few years, there has been an undeniable asymmetry between enterprise investment in AI and return in value. Lots of money has gone into AI; insufficient value has come out.
In 2026, that asymmetry will change: enterprises will utilize generative AI for internal productivity gains and external customer-facing use cases. Agentic AI adoption will be slower but no less impactful. By the end of the year, companies will be able to point to tangible gains in ROI and demonstrate AI's real world value - and still only be benefiting from a fraction of AI's full potential.
The era of asymmetry is ending. 2026 will be the year that companies see tangible gains in ROI that demonstrate AI's real world value.
Luminos.AI
CEO Andrew Burt
Stale data gets exposed: the AI agent stack forces data to grow up
AI agents are about to expose a truth: models are powerful, but stale data makes them dumb. By 2026, enterprises will shift from batch and ad-hoc integrations toward right-time, unified pipelines that continuously hydrate AI systems with trustworthy context. This reshapes org charts. Data, ML, and application teams converge around shared declarative pipelines instead of handoffs. The downstream effect? A widening performance gap. Companies that deliver fresh, governed data to agents will automate entire workflows; companies that don’t will struggle with hallucinations, compliance issues, and operational drag. Fresh data (not bigger models) becomes the real differentiator.
Estuary Co-founder
Dave Yaffe
The next leap in AI comes from physical models, not bigger LLMs
The march toward AGI has advanced rapidly through LLMs but large language models are hitting natural limits. They’ve processed nearly every written word produced by humanity. While synthetic data represents some room for continued improvement, future foundational model advancement may focus more on efficiency and reliability gains.
The next major step will probably come from physical AI models: systems that learn from the real world rather than text using sensors and cameras to learn how the real world works, much like a human being does through experience. The major advantage over LLMs is the nearly limitless amount of data they can process to continue to learn concepts related to science, medicine and human-to-human interactions, an area of weakness in LLMs.
2026 is the year the path toward AGI via physical models begins in earnest.
M13 Partner
Rob Smith
Systems of action become intelligent through enterprise world models and embodied AI
LLMs have reached the limits of what can be learned from static text, revealing gaps in causal reasoning, multi-step planning and real-world reliability. The next frontier is embodied AI and enterprise world models. These systems learn from interaction data generated by sensors, robots, people and operational workflows, capturing how work actually gets done inside organizations.
Embodied AI grounds models in the physical and procedural realities of the enterprise. World models act as simulation engines that mirror a company’s processes, constraints, exceptions and decision pathways, encoding the same tacit knowledge humans built through experience. Together, they unlock complex agentic decision making and make true systems of action possible: agents that can predict outcomes, test strategies in simulation and autonomously execute multi-step workflows.
In 2026, intelligence shifts from “models that know things” to “models that understand and act within environments.” The winners will leverage world modeling, not model size, to automate knowledge work.
M13 Principal
Morgan Blumberg
Real AI adoption: Doctors moving as fast as software
AI will transform every industry but none more than healthcare, where a decade of digital health hype has mostly fallen flat. That’s finally changing. OpenEvidence is already used by 40% of U.S. physicians just 18 months after launch — doctors have never adopted new technology at this speed. Vinod Khosla 's prediction that AI will perform 80% of the doctor’s work stops sounding theoretical in 2026. Non-clinical busy work will be fully eliminated and, more importantly, we will see real strides in care models delivered by AI. AI nurses and AI doctors - digital twins of our favorite clinician – will become prevalent in 2026 allowing for personalization at scale. Physicians will work at the top of their license and high quality coverage across the population will increase. Consumers already trust AI for healthcare, and will see top down directives from health systems and large care providers.
One thing is certain: every AI model will require living, breathing, continuously generated human data to keep getting better.
M13 General Partner
Latif Peracha
Futureproofing goes mainstream as AI and crypto hit energy, finance and healthcare
I am looking forward to the theme of futureproofing in 2026. The world has woken up to the fact that AI is real, even if most use cases to date focus on our insular tech world. Similarly, crypto continues to gain adoption, although on a quieter note. 2026 is the year where we see AI and crypto expand into the real world to solve complex problems that affect society - beyond just the tech world. Rather, the next wave of adoption will come from SMBs and historically non-tech forward industries (e.g., energy/industrials, financial services, healthcare), and the opportunity is to facilitate that adoption that obfuscates complexity.
M13 Principal
Mark Grace
CHROs, not engineers, are AI workforce architects
In 2026 AI will no longer be a tool. Companies will embed AI in their strategy as part of what it truly is: a new architecture for how work gets done. The best ones will design agentic workflows from the ground up, deciding which tasks are owned by people, which are executed autonomously by AI systems, and how the two reinforce each other. Doing this well demands a different kind of leadership profile: close enough to the work to understand the nuances of product, operations and customer feedback and experienced enough to architect workflows and decide where human oversight is essential. And it requires a shift in ownership. AI’s impact is organizational, not just technical. These are not engineering questions, they are people questions. CHROs and talent leaders will become stewards of the AI transformation, defining how work gets done in truly AI-native companies.
M13 Partner
Matt Hoffman
Digital marketing changes with the first ChatGPT ad
The first paid ad unit will appear in ChatGPT as OpenAI joins the ranks of the other major ad networks. In many ways, ads have always been inevitable, and recently the company has made inroads to make it a reality, as evidenced here, here and here. As eyeballs and searches continue to accelerate towards OpenAI - which will soon eclipse 1B active users - OpenAI ads will be among the most valuable inventory online. And if you’re planning to fund $1.4T in capex over the next decade, high margin ad revenue really helps. I do not believe OpenAI is looking to copy its predecessors’ ad formats so the second part of my prediction is that the first ChatGPT ad unit will look very different from banners or native ads.
M13 Partner
Brent Murri
From fandom to fulfillment: cultural commerce is the next infrastructure play
Entertainment is the new storefront. Sports docuseries, gaming, collectibles, anime, and micro-dramas are replacing the old commerce funnel with fandom flywheels. In 2026, community is the distribution channel. Success won’t be measured by clicks, but by cultural engagement: retention, shared identity, and participatory behavior.
For infrastructure investors, this convergence of product and entertainment creates opportunity. Platforms that power identity, community and interoperability become the true value layer. Examples:
- Participatory commerce tools that turn fans into buyers and creators into collaborators. Think tokenized loyalty, embedded social checkout and UGC-as-conversion pipelines.
- Community and discovery infrastructure that routes cultural signals into commerce outcomes.
- Media ops stacks for creators and brands to launch and scale like showrunners.
- AI-native orchestration layer for modern brands to automate product sourcing, supply chain ops, fulfillment and marketing.
Cultural commerce is rising. Infrastructure makes it possible and ownable.
M13 Co-founder and Partner
Carter Reum
When algorithms mediate attention, your story becomes your strategy
In 2026, brands won’t just need media: it becomes media, and media now means more than reporters and press coverage. Media is every surface where people form an opinion about and begin to trust you: WSJ, LinkedIn, a podcast, an event hallway, even ChatGPT. We’ll run comms like editorial franchises built on consistent narratives, recurring formats and distribution across owned and earned channels. That’s because algorithmic intermediaries now shape what gets seen and by whom, and they reward clarity and consistency above everything else.
The shift means vanity metrics stop mattering. Consistency beats volume, and narrative clarity means discoverability. Success becomes far more precise to measure: better deal flow, stronger retention, deeper participation. And that’s freeing. When original content is table stakes, the real differentiator becomes human judgment: the relationships we build, the conversations we spark, and the trust we earn in all the places algorithms can’t reach.
M13 Partner
Christine Choi
New York overtakes Silicon Valley
In 2026, New York will emerge as the leading AI startup hub. Vertical AI startups in key categories want to be where their customers are, and New York is a great place to build in some key verticals like fintech, advertising, media, governance, compliance and commerce. As the platform shifts matures, it’s less important to be where the foundational technologies were invented and more important to be where they are getting consumed.
M13 Partner
Anna Barber
AI governance gets teeth
- State AI enforcement starts. We'll see the first wave of meaningful state AI enforcement actions, transforming AI governance from theoretical frameworks to operational necessities as companies scramble to comply.
- AI consolidation. Strategic acquirers and PE firms will begin to systematically roll up the AI companies that raised significant capital the past few years but failed to achieve sustainable unit economics, creating value through consolidation rather than innovation.
- The AI media takeover. AI platforms will become the new foundation that struggling traditional media companies need to reinvent their business models (such as through licensing royalties, production workflows, content creation and distribution), evolving from litigation targets to the infrastructure that studios can’t survive without. Media companies in turn will slowly cede control of the entire media ecosystem.
M13 Partner
Win Chevapravatdumrong
AI filters. Humans choose.
As AI becomes the first line of defense for screening and sorting, in-person interactions will only grow in importance. We are social creatures first and foremost. The last mile of pattern recognition still depends on face-to-face encounters that activate intuition and gut judgment. These are the human capital variables that algorithms cannot solve (yet). They are the pattern recognition je ne sais quoi people recognize when they meet truly special founders or investors.
M13 Partner
Sarah Tomolonius
GLP-1 access and coverage remain a 2026 battleground
GLP-1 prices continue to come down as the government and pharmaceutical companies announce price cuts and new programs that will increase affordability and access for consumers. Coverage and pricing for employer groups remains uneven but is likely to improve as we move into 2026. Questions remain around eligibility and coverage, particularly for Medicare and Medicaid members, and the neverending news cycle is creating confusion across the board. Access is improving, but affordability and consistent coverage remain major hurdles. One thing is clear: treating obesity as a chronic disease, rather than a lifestyle choice, is the key to progress.
Form Health founder and CEO
Evan Richardson
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The views expressed here are those of the individual M13 personnel quoted and are not the views of M13 Holdings Company, LLC (“M13”) or its affiliates. This content is for general informational purposes only and does not and is not intended to constitute legal, business, investment, tax or other advice. You should consult your own advisers as to those matters and should not act or refrain from acting on the basis of this content. This content is not directed to any investors or potential investors, is not an offer or solicitation and may not be used or relied upon in connection with any offer or solicitation with respect to any current or future M13 investment partnership. Past performance is not indicative of future results. Unless otherwise noted, this content is intended to be current only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in funds managed by M13, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by M13 is available at m13.co/portfolio.