Artificial Intelligence Venture Capital Shaping the Future


Jeff Bartel

Chairman and Managing Director

Artificial intelligence and venture capital have become incredibly intertwined. Whether it is the benefits of artificial intelligence in vetting investments or funds driven by AI technology, it is hard to separate the two. 

Growth of VC Investments in AI

The venture capital sector is investing more in AI technology, a growing driver in almost every industry.

Artificial Intelligence and Machine Learning

Machine learning and artificial intelligence are not interchangeable terms. AI refers to computer systems that appear intelligent or demonstrate human traits and understanding of the world. You can have AI that cannot, on its own, learn. Instead, it is programmed to respond to queries or stimuli in intelligent ways.

Machine learning is a type of AI. It refers to computers that are so advanced they learn, taking in copious amounts of data and coming to conclusions that would be difficult for humans to determine. In short, machine learning makes AI capable of going beyond human abilities and is driving the sector’s growth.

Artificial Intelligence Growth by Industry

Venture capitalists are pouring increasing amounts of money into AI across various sectors due in part to the promises that machine learning and the subsequent evolutions in AI can make. From 2012 through 2019, there were more than 20,000 venture capital investments involving AI. More than half of those occurred in three sectors:

  • IT infrastructure and hosting
  • Media, social media, and marketing
  • Business processes and support services

Other industry sectors with strong growth (more than 1,000 deals from 2012 through 2019) in AI investments include healthcare and biotechnology, robots and sensors, finance and insurance, and digital security.

Returns for Artificial Intelligence Venture Capital Investments

The relationship between venture capital and AI is not a one-way street. While investors are banking on AI wins across all industries, firms also turn to AI to increase investment returns.

Machine learning capabilities support AI-based algorithms that outperform human “gut reaction” and knowledge when choosing worthwhile investments. A University of St. Gallen team created an algorithm to select investment opportunities. It compared the machine’s performance against 255 angel investors, and the machine outperformed the average human by 184%.

How AI and Venture Capital Work Together

By 2025 AI will be involved in 75% of investment decisions. However, that does not mean people are set to become obsolete in venture capital processes; instead, it points to a growing collaboration between human knowledge and computational power.

Use of Artificial Intelligence in Finance

Artificial intelligence in finance and investment management is no longer a fringe idea. Most investors and finance organizations utilize some level of machine learning to understand the viability of funds and investments or drive workflows to get things done.

Artificial Intelligence in Business

Some ways AI and venture capital already work together — and some trends that will only increase in the future — include:

  • Evaluating investments. AI can take in and consider so much more data than a human mind can. That leads to a deeper understanding of potential investments, ensuring investors can make more informed decisions.
  • Creating more efficient workflows. Firms are already using AI to drive automated workflows, reducing the time it takes to act on a potential investment.
  • Forecasting performance of portfolios. Machine learning capabilities will continue to help firms create ever-more accurate forecasts, driving more innovative investments and increasing wealth-building capabilities.
Machine learning algorithms and artificial intelligence venture capital

Artificial Intelligence Stocks and Startups

While many companies and funds are investing in AI initiatives, pure AI stocks are still rare in the market. Instead, investors must look for opportunities for companies using AI to drive growth and innovation. Amazon, Google, Microsoft, and IBM are obvious choices, but others exist, including Toyota, Baidu, and Nvidia.

As with any disruptive growth concept, AI investments are perhaps even more exciting at the startup level. In 2018, more than $9 billion was invested in these types of companies. Some leaders include:

  • Softbank Group, which has a dedicated tech development fund called Softbank Vision Fund
  • Intel Capital, which is part of Intel Corporation and invests in thousands of tech companies
  • Lightspeed Ventures, which provides funding for tech startups in the early stages
  • Andreessen Horowitz, which has raised more than $7 billion for tech-driven funds

Artificial Intelligence Venture Capital Investments in Autonomous Vehicles

In 2021, billions of venture capital dollars were funneled into the mobility tech sector, primarily in the niche related to autonomous vehicles. Rapid growth in machine learning and AI is making driverless vehicle opportunities a reality, as evidenced by tests Walmart has done that include autonomous box trucks making deliveries to customers.

Autonomous vehicles could bring huge monetary and supply chain wins in the transportation sector alone. Driverless delivery or transport vehicles would help keep many of the supply chain problems that occurred during the COVID-19 pandemic from happening in the future, for example, so it is not surprising that venture capitalists are flocking to these opportunities.

Artificial Intelligence Venture Capital in Media and Social Media

Media and social media play enormous roles in society. They shape world views, sway voters, and inform the policy of governments and agencies. Disruptive models put publishing power in the hands of every person, the need for accountability across media types, and the increasing use of AI to manage publishing, marketing, and content creation. As a result, venture capitalists are looking for up-and-comers with the technology to make a splash in the niche.

Emerging Technologies: Quantum Computing Financial Systems


Jeff Bartel

Chairman and Managing Director

Quantum computing is one of the emerging technologies for businesses poised to impact financial systems and other processes. As a result, quantum computing will have an impact on economic sectors.

The Quantum Financial System Is Ready to Impact Investing

Quantum computing leverages quantum mechanics to support calculations and programmatic operations that were impossible before, even with advanced supercomputers.

The idea of quantum computing dates back to the 1980s, but it is only now, four decades later, that the technology is poised to have an impact on investing and other financial niches.

How is Quantum Computing Used?

Quantum computing is used to analyze and solve real-world problems with exponentially high combinations of potential answers.

Modern supercomputers do not have the working memory and functionality to approach these problems correctly. They have to consider each answer combination in order; real-world scenarios with a dozen or more inputs can have millions of potential combinations. Even if a supercomputer could evaluate and analyze every combination, it could take months or years to arrive at an answer.

Quantum computers push through all this data faster by using multidimensional modeling and algorithms that supercomputers cannot.

Orb on keyboard representing emerging technogies and quantum computing.

When Will Quantum Computing Arrive?

In some ways, quantum computing is already here. Companies like IBM and Google have already built systems capable of this calculation level. The IBM Cloud provides access to systems that support quantum coding and analysis.

Who Has Quantum Computers and Other Emerging Technologies?

Some companies that have finished quantum computing systems in 2022 include IBM, Quantum Computing Inc., Xanadu, Microsoft (via Azure Quantum), and D-Wave Systems.

Potential Benefits of Quantum Computing

Quantum computing is one of the emerging technologies that have the power to bring significant change, especially in areas such as finance and investing. Some potential benefits include:

  • Ability to dig deeper into financial analytics faster and with more accuracy
  • Support for faster decision-making, whether that involves trades or business pivots
  • Better financial modeling, leading to cost savings

Consider the case of trading optimization. Trading and valuation today rely on ever-increasing data models, often considering factors such as funding, credit, debit, margin, and capital. Additionally, risk-averse investors balance conservative action with a desire to back businesses or buy into funds that align with personal or societal beliefs, bringing ESG factors into the mix.

Quantum computing has the power to hold all these disparate data points, allowing for rapid, complex analysis and data-backed decision-making. As a result, these solutions support investment managers in creating more value for clients and improving portfolios.

Retail generates enormous data, and many retailers are often limited to structured data that analytical systems can handle. Quantum computing opens the door to using all data, even raw data, to create more informed, higher-performing sales funnels and marketing campaigns. This level of access to information can also inform research and development for faster time-to-market on new products.

A benefit of quantum computing in logistics is creating robust simulations that analyze all possible delivery factors and routes. Such solutions could consider more data than any system or person before, evaluating all options and making real-time decisions about shipping or delivery. Those changes could lead to a level of automation, accuracy, and efficiency in shipping that has not been seen before.

Potential Risks of Quantum Computing

Quantum computing technology is not without risks. These computers present a current difficulty for some of the problems the enhanced calculation capability could help solve.

For example, the computers themselves can be highly unstable and require extreme storage environments. Those come with a heavy carbon footprint.

Quantum computing may also lead to increasingly augmented machine learning and AI. But unfortunately, while that opens doors to new technologies and innovations, it does the same for cybercriminals and hackers.

Emerging Technologies Related to Quantum Computing

The growth of quantum computing is leading to other emerging technologies. These stem from, support, or interact with quantum computing in ways that can lead to innovation and disruption in financial sectors and other industries.

  • Quantum time crystals. They can achieve a pattern of motion, theoretically in perpetuity, without drawing on an energy source. Google claimed it had achieved time crystals via quantum computing. The technology is fledgling, but the impacts of movement without a fuel source are enormous.
  • Quantum Artificial Intelligence (AI). Combining quantum computing with machine learning algorithms drives faster programmatic learning and adaptations, supporting AI environments, systems, and functions that are not possible with other computers.
  • A move beyond silicon. According to an analysis from Gartner, quantum computing will lead to developments beyond silicon and microchips. The very structure of computer hardware is evolving.

Who Will Benefit From Quantum Computing?

The benefits of quantum computing will be seen across almost all industries. For example, banking, financial markets, and insurance products are all likely to evolve within the financial sector.

Use Cases for Emerging Technologies: Quantum Computing

But what does quantum finance look like in the current and near future? Here are several sample use cases:

  • Financial targeting and prediction. More data supports better forecasting, but only if businesses can put that data to use. Even supercomputers are limited as to how much raw or structured data they can deal with at a time, so quantum computing creates a path for making better use of Big Data in financial models.
  • Trading optimization. The already fast world of trades can move at an even quicker pace with quantum computing. Investors can get information early, make data-backed decisions or even potentially automate them, and shave off seconds or even minutes in trade times that can reflect better profits.
  • Risk profiling. Quantum financial analytics may make it easier for investors to identify and qualify risks, leading to a significant impact for processes involved in choosing investments as well as M&A activity.

Computational Resources and Quantum Computing

At this point in the evolution of quantum computing, resources are one of the major bottlenecks. A scarcity of computational resources capable of this level of functionality means limited implementation options, at least in the near future. Unfortunately, it also means companies that have cracked the code on quantum computing can charge a premium for those technologies.

Meanwhile, real-world problems tend to be high-dimensional. As knowledge about the capability of quantum computers in solving such issues becomes more widespread, so will the demand for these technologies. Therefore, it may be a while before supply and demand align.

How Can Businesses Prepare for Quantum Computing and Other Emerging Technologies?

Meanwhile, businesses in the financial sector should start preparing for a world where quantum computing is more of a norm. Here are some tips for doing so:

  • Build partnerships or create an internal team ready to implement new technologies. Even if your horizon does not include quantum computing, technologies evolve quickly. To remain competitive, financial firms need to be early adopters, so be ready with a team or partners that can make it so.
  • Scout for investment and joint ventures. Look for ways to grow portfolios for your business and your customers by understanding the growth of quantum computing and what it may mean for investment opportunities.
  • Invest in cloud computing. You do not have to make the leap to quantum computing to realize physical servers and on-premises solutions will not hold up to today’s technology needs. By moving to the cloud now, businesses can position themselves to be more ready for the next wave in finance tech.