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After a banner year for new AI applications, companies, and ideas, it’s almost impossible not to talk about artificial intelligence in this moment. While specific news stories come and go, there are a few fundamentals that won’t be changing in the near term.
At M13, we believe AI represents a true paradigm shift. As with the dawn of the internet, the rise of mobile, and the rise of cloud computing, this technology will usher in a fundamental change in the way software products are built and how we do our work. While to the average consumer AI may feel like an uncertain landscape, in ten years, it will just be another part of how we live our lives.
At our most recent annual general meeting, M13 shared our point of view on the AI wave: what it does, why it's having such a moment right now, and where we aim to invest.
What does AI actually do?
To anticipate how AI will change products and services we currently use, it’s useful to review AI’s core functions.
First, it predicts, looking forwards. AI is very good at parsing complex datasets to figure out what is most likely to happen next. The implications here span underwriting, investment management, inventory management, pricing, hiring models, and more.
Second, it infers, looking backwards. AI can assess complex data to answer questions about why something happened. We can apply this to areas from business intelligence (why did a customer make a certain purchase?) to medical diagnosis (why did a patient exhibit certain symptoms?).
Third, it generates. Especially in this era of widespread generative AI use, AI can create art, text, and video, with tremendous potential impact on marketing, sales, education, training, new product design, and more.
When you put these three functions together, you get automation. This function looks like AI agents that work alongside humans on things like customer services and sales, outreach, coding, personal CRM, and other exciting applications.
Why now?
AI is not a new technology, but 2023 did mark a new inflection point. There are a few reasons for this.
One is that foundational models have become usable out of the box for lay users. Open-source models trained on a large volume of information can accept real language queries, and we’ve seen the release of APIs built on top of these models that developers can use to more easily build new applications.
Technology advancements have also accelerated, making it cheaper to train models—according to Ark Invest, the cost of training a new model is declining each year by 70%. Training a new model is now within reach for your average company, or even your average independent developer.
Continued strong investment has also driven the AI wave. During a difficult time for fundraising, AI has remained a bright spot in the venture world. As a result, there’s been a steady stream of new AI product launches, keeping AI at the forefront of our attention. One year out from the launch of chatGPT, 6 in 10 US adults report being familiar with the technology.
News cycles have also played a role. Scott Belsky, who spoke at our 2023 Future Perfect conference, pointed out that if you’ve used an Adobe product in the last 15 years, you’ve already used artificial intelligence—you might just not have been thinking about it. Today, we see stories of AI plastered all over our newsfeeds, making it top of mind for consumers and CEOs alike and further driving trials for AI products.
Finally, large enterprises are taking notice and prioritizing AI in their strategic planning. Earnings call mentions of “generative AI” alone jumped 75X from Q4’22 to Q3’23 as executive interest in the area skyrocketed. Across Fortune 500 companies, 80% of surveyed CEOs said that they believe AI will increase efficiency and 75% said they believe it will automate manual operations in their business in the near term.
We’re seeing measurable economic impact of this technology. It takes developers 50% less time to code when they use GitHub Copilot. Knowledge worker productivity is projected to increase fourfold with the use of AI. These are real bottom line impacts. While there may be some speculation involved in how AI investing is rolling out, the excitement is driven by real impact.
Our approach to investing in AI
The AI tech stack includes infrastructure, orchestration, and application layers. We’re most interested in investing in the latter two.
Generally, we're looking for areas where AI technology offers a massive performance boost—10X improvement, not 10%. Where does it hugely surpass human performance? Where can business be built using proprietary access to data? And what new infrastructure companies will be needed to support the development of this entire ecosystem?
We believe this shift in technology positions startups at the application layer to compete with incumbents as they have the opportunity to build from the ground up on genAI. We are particularly excited about companies that can interact with end users using natural language and act as an interaction layer on top of traditional data structures. In time, we believe focused vertical solutions, especially those with access to proprietary data, will have the capabilities to fully automate workflows.
We have invested behind this thesis in the relationship management category with Hearth.ai, the document interaction category with Humata, and tax automation category with Workmade.
We believe for certain use cases developing a smaller, proprietary foundational model has advantages when coupled with an end-to-end customer solution. One such company is our portfolio company Norm Ai, building AI legal guardrails starting with regulatory compliance. Norm’s AI agent presents context-aware compliance checks that determine what marketing materials and disclosures may be problematic with which regulations. We believe that eventually Norm will be able to interact with AI agents conducting financial transactions, ensuring those agents comply with all relevant laws, policies and guidelines.
We realize the shifts in the way technology will be built will require new developer tools to support data curation, model training, fine tuning and observability. We are excited to watch this landscape evolve and support the tools that will build the software of the future.
As early-stage investors, the quality of a team is one of the most vital things we assess—and one reason we’ve been so excited to invest in AI is that this space draws some truly amazing founders. We’re seeing top minds coming out of universities teaming up with serial successful founders because they’re so excited about this technology, and former founders are getting back in the ring to see what they can build.
We’ll continue to share our perspective on particular aspects of the AI technology wave, and would love to talk to founders building at the application and orchestration layer.
After a banner year for new AI applications, companies, and ideas, it’s almost impossible not to talk about artificial intelligence in this moment. While specific news stories come and go, there are a few fundamentals that won’t be changing in the near term.
At M13, we believe AI represents a true paradigm shift. As with the dawn of the internet, the rise of mobile, and the rise of cloud computing, this technology will usher in a fundamental change in the way software products are built and how we do our work. While to the average consumer AI may feel like an uncertain landscape, in ten years, it will just be another part of how we live our lives.
At our most recent annual general meeting, M13 shared our point of view on the AI wave: what it does, why it's having such a moment right now, and where we aim to invest.
What does AI actually do?
To anticipate how AI will change products and services we currently use, it’s useful to review AI’s core functions.
First, it predicts, looking forwards. AI is very good at parsing complex datasets to figure out what is most likely to happen next. The implications here span underwriting, investment management, inventory management, pricing, hiring models, and more.
Second, it infers, looking backwards. AI can assess complex data to answer questions about why something happened. We can apply this to areas from business intelligence (why did a customer make a certain purchase?) to medical diagnosis (why did a patient exhibit certain symptoms?).
Third, it generates. Especially in this era of widespread generative AI use, AI can create art, text, and video, with tremendous potential impact on marketing, sales, education, training, new product design, and more.
When you put these three functions together, you get automation. This function looks like AI agents that work alongside humans on things like customer services and sales, outreach, coding, personal CRM, and other exciting applications.
Why now?
AI is not a new technology, but 2023 did mark a new inflection point. There are a few reasons for this.
One is that foundational models have become usable out of the box for lay users. Open-source models trained on a large volume of information can accept real language queries, and we’ve seen the release of APIs built on top of these models that developers can use to more easily build new applications.
Technology advancements have also accelerated, making it cheaper to train models—according to Ark Invest, the cost of training a new model is declining each year by 70%. Training a new model is now within reach for your average company, or even your average independent developer.
Continued strong investment has also driven the AI wave. During a difficult time for fundraising, AI has remained a bright spot in the venture world. As a result, there’s been a steady stream of new AI product launches, keeping AI at the forefront of our attention. One year out from the launch of chatGPT, 6 in 10 US adults report being familiar with the technology.
News cycles have also played a role. Scott Belsky, who spoke at our 2023 Future Perfect conference, pointed out that if you’ve used an Adobe product in the last 15 years, you’ve already used artificial intelligence—you might just not have been thinking about it. Today, we see stories of AI plastered all over our newsfeeds, making it top of mind for consumers and CEOs alike and further driving trials for AI products.
Finally, large enterprises are taking notice and prioritizing AI in their strategic planning. Earnings call mentions of “generative AI” alone jumped 75X from Q4’22 to Q3’23 as executive interest in the area skyrocketed. Across Fortune 500 companies, 80% of surveyed CEOs said that they believe AI will increase efficiency and 75% said they believe it will automate manual operations in their business in the near term.
We’re seeing measurable economic impact of this technology. It takes developers 50% less time to code when they use GitHub Copilot. Knowledge worker productivity is projected to increase fourfold with the use of AI. These are real bottom line impacts. While there may be some speculation involved in how AI investing is rolling out, the excitement is driven by real impact.
Our approach to investing in AI
The AI tech stack includes infrastructure, orchestration, and application layers. We’re most interested in investing in the latter two.
Generally, we're looking for areas where AI technology offers a massive performance boost—10X improvement, not 10%. Where does it hugely surpass human performance? Where can business be built using proprietary access to data? And what new infrastructure companies will be needed to support the development of this entire ecosystem?
We believe this shift in technology positions startups at the application layer to compete with incumbents as they have the opportunity to build from the ground up on genAI. We are particularly excited about companies that can interact with end users using natural language and act as an interaction layer on top of traditional data structures. In time, we believe focused vertical solutions, especially those with access to proprietary data, will have the capabilities to fully automate workflows.
We have invested behind this thesis in the relationship management category with Hearth.ai, the document interaction category with Humata, and tax automation category with Workmade.
We believe for certain use cases developing a smaller, proprietary foundational model has advantages when coupled with an end-to-end customer solution. One such company is our portfolio company Norm Ai, building AI legal guardrails starting with regulatory compliance. Norm’s AI agent presents context-aware compliance checks that determine what marketing materials and disclosures may be problematic with which regulations. We believe that eventually Norm will be able to interact with AI agents conducting financial transactions, ensuring those agents comply with all relevant laws, policies and guidelines.
We realize the shifts in the way technology will be built will require new developer tools to support data curation, model training, fine tuning and observability. We are excited to watch this landscape evolve and support the tools that will build the software of the future.
As early-stage investors, the quality of a team is one of the most vital things we assess—and one reason we’ve been so excited to invest in AI is that this space draws some truly amazing founders. We’re seeing top minds coming out of universities teaming up with serial successful founders because they’re so excited about this technology, and former founders are getting back in the ring to see what they can build.
We’ll continue to share our perspective on particular aspects of the AI technology wave, and would love to talk to founders building at the application and orchestration layer.
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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.