How AI Is Making Investment Decisions With the World's Money

Pension funds, insurers, banks, hedge funds and venture capital firms invest money on behalf of millions of people. Increasingly, artificial intelligence helps decide where that money goes.

This does not mean a chatbot is transferring billions without supervision. The change is quieter. AI systems search for opportunities, read company information, compare investments, estimate risk and flag decisions for human review. In some markets, they can also place trades.

The shift is already well under way. A 2024 survey by the Bank of England and Financial Conduct Authority found that 75% of responding UK financial firms were using AI. Another 10% planned to use it within three years. More than half of the reported uses involved some automated decision-making, although only 2% were fully autonomous.

AI is not waiting for permission to enter investment management. It is already inside the process.

What does AI investment decision-making actually mean?

An investment decision is not one moment. It is a chain of smaller decisions.

Which markets should a fund study? Which companies deserve attention? Are the financial assumptions realistic? How does the opportunity compare with similar businesses? What could go wrong? How much should the fund invest? When should it sell?

AI can now assist with each question.

In practice, investment firms use AI for five main jobs:

1. Scouting: Searching company databases, funding announcements, hiring activity, patents, product reviews and other signals to find opportunities.
2. Screening: Comparing thousands of companies against a fund's investment criteria.
3. Due diligence: Reading financial statements, contracts, market reports and other documents much faster than a human team could.
4. Decision support: Estimating possible outcomes and showing which assumptions matter most.
5. Monitoring: Following changes in a company, market or portfolio after the investment has been made.

The final legal responsibility normally remains with people. However, when AI chooses which companies humans see, which risks receive attention and which opportunities reach an investment committee, it already has substantial influence over the result.

From algorithmic investing to AI investing

Computers have been used in finance for decades. Traditional algorithmic investing follows rules written in advance. A system might buy an asset when its price falls below a set level or rebalance a portfolio when its risk moves outside an agreed range.

AI investing goes further. Machine-learning systems can identify patterns across large amounts of information and adjust their predictions as new data arrives. Generative AI can also work with text, images, presentations and conversations, not only numbers in a spreadsheet.

That matters because much of the information used in venture capital is unstructured. It sits in pitch decks, founder interviews, product descriptions, customer feedback, market reports and the history of similar companies.

The International Monetary Fund expects AI to play a larger role in trading and investment, with decisions becoming more autonomous over time. The Bank of England has reached a similar conclusion. It says AI could help markets absorb new information faster, while warning that models may struggle with shocks that have no useful historical comparison.

AI has already shown that it can beat professional investors

A 2025 study from researchers at Stanford Graduate School of Business and Boston College tested an AI analyst against actively managed US mutual funds.

The system used public information and adjusted the funds' portfolios every quarter between 1990 and 2020. According to the researchers, it outperformed 93% of the fund managers by an average of 600%.

That result is striking, but it requires context.

It came from a historical simulation. The AI was not managing real money in real time. Public-market investing also provides far more consistent data than venture capital, where companies are private, information is incomplete and results can take a decade to appear.

The study still demonstrates something important. AI does not always need secret information to find an advantage. It can create an advantage by processing ordinary information more consistently than people do.

How AI is changing venture capital

Traditional venture capital depends heavily on personal networks. Founders meet investors through introductions, events, accelerators and other investors.

That system can work, but it also has clear limits. A partner can meet only so many founders. An analyst can review only so many companies. Promising businesses outside familiar cities and networks can remain unseen.

AI changes the size of the search.

A venture capital firm can use machine learning to study millions of businesses and reduce them to a smaller group that matches its strategy. It can notice early growth, unusual hiring patterns, customer interest or signs that a new market is forming.

EQT began building its Motherbrain platform in 2016. The firm says the system now supports its investment process from finding opportunities to creating value in portfolio companies. Other venture firms have built similar systems for finding and evaluating startups.

This does not remove the need to meet founders. It helps decide which founders an investment team should meet first.

Euro VC's AI-led investment process

Euro VC is developing an AI-supported research system that draws on long-run business and investment data.

The purpose is not to produce an impressive-looking score. It is to improve the quality and consistency of the decisions we make.

AI-supported analysis is currently used across approximately 80% of Euro VC's scouting and investment workflow stages. This figure measures the stages in which AI provides analysis or decision support. It does not mean that 80% of investment control is autonomous. People remain responsible for every investment decision. AI helps us:

• Search across European markets continuously
• Compare companies with relevant historical patterns
• Test the assumptions behind an investment case
• Find contradictions across documents and data
• Build downside, base and upside scenarios
• Challenge conclusions reached by the investment team
• Monitor companies and markets after an investment

In Euro VC's internal testing, the AI-led selection model produced stronger results than the venture benchmarks used during development.

Past performance is not a reliable indicator of future results. Venture capital is high risk and illiquid. Capital is at risk.

These results are internal, have not been independently verified and cannot predict future returns.

Euro VC aims to extend AI-supported analysis to more than 90% of its scouting and investment workflow stages before 2030. This is an operational objective, not a performance forecast or guarantee. Human responsibility will remain in place. The difference is that far less of the work behind a decision will depend on memory, manual research or personal access.

Why AI can make better investment decisions

AI has several natural advantages over a traditional investment team.

It can examine more opportunities

A fund that relies only on people will miss companies. There are too many businesses, markets and data points for any team to follow manually.

AI can maintain a much wider search without becoming tired or distracted.

It remembers previous decisions

Investment teams change. People leave, memories fade and lessons are lost.

A well-built system can retain the reasoning behind earlier decisions. It can compare what investors expected with what actually happened.

It applies the same test repeatedly

People can be influenced by reputation, presentation, mood and familiarity. AI can apply the same base criteria to every company before human judgement enters the process.

It can challenge a convincing story

A good founder should be able to communicate a vision. The danger is that a powerful story can hide weak assumptions.

AI can compare that story with available evidence and identify the parts that require closer examination.

It can improve human judgement

Research comparing people and machines suggests the strongest result may come from using both. One study found that machines performed better when large amounts of structured information had to be processed, while experienced analysts did better when company knowledge was harder to measure. The combined human and machine model reduced extreme errors made by either side.

That is the model we believe is most useful for venture capital.

Where AI can still fail

AI can process more information than a person. It cannot guarantee that the information is correct.

A system trained on past winners may learn patterns that no longer matter. It may favour the types of founders who received funding previously. It may mistake correlation for a real cause. It can also become highly confident about an answer built on incomplete data.

There is another risk. If many investment firms use the same models and information, they may reach similar conclusions at the same time.

The Bank of England has warned that AI-driven investment strategies could create more correlated positions. During a market shock, several systems might try to reduce the same risks together, making price movements more severe.

AI can remove some human mistakes. It can also repeat one machine mistake across thousands of decisions.

This is why data quality, testing, human oversight and a clear audit trail matter as much as the model itself.

How to evaluate an AI-driven investment fund

Investors should look beyond claims that a fund is "powered by AI". The phrase alone says very little.

Before investing, ask these questions:

These questions are more useful than asking whether a fund uses the newest model.

Will AI replace venture capital investors?

AI will replace parts of the job. It is already doing so.

Manual market searches, first-stage screening, document summaries and simple comparisons will require much less analyst time. Investment teams will be able to examine more companies without adding the same number of people.

Other parts of venture capital remain harder to automate.

A founder may be entering a market that does not yet exist. Customer data may be limited. The business may depend on a scientific breakthrough, a regulatory change or the ability of a small team to attract exceptional people.

Those decisions require judgement under uncertainty. AI can inform that judgement, but responsibility still belongs to the investor.

The likely future is not AI versus human investors. It is investors using AI competing against investors who are not.

Frequently asked questions

Can AI make investment decisions?

Yes. AI can already screen investments, estimate risk, construct portfolios and support trading decisions. Some systems can act autonomously within set limits. In most regulated investment firms, people remain accountable for important decisions.

Is AI better than human investors?

AI is often better at processing large amounts of data, applying the same test consistently and identifying statistical patterns. Experienced investors can be better at judging unusual situations, understanding people and recognising when the past is no longer useful. A process combining AI and human judgement can be stronger than either working alone.

How is AI used in venture capital?

AI in venture capital is used for startup scouting, market mapping, pitch-deck analysis, company comparison, due diligence, investment scoring and portfolio monitoring. It allows a venture fund to examine far more companies than a human team could review manually.

What is the difference between AI investing and algorithmic investing?

Algorithmic investing normally follows rules written in advance. AI investing uses models that learn patterns from data and may change their predictions as new information becomes available. Both can automate parts of an investment process, but AI can work with more complex and less structured information.

Will AI replace fund managers?

AI is likely to replace many research and screening tasks. It is less likely to remove human responsibility for strategy, governance, unusual risks and final investment approval. Fund managers who use AI well may replace those who do not.

Are AI investment funds safe?

An AI investment fund carries the same basic risks as other funds, plus risks linked to its data, models and technology providers. Investors should examine the fund's strategy, track record, governance, human oversight and explanation of how AI is used. The use of AI does not remove the possibility of loss.

Can beginners use AI for investing?

Beginners can use AI to explain financial terms, compare public information and create questions for further research. A public chatbot should not be treated as a personal financial adviser or trusted to make trades without review. Always check the source, date and assumptions behind an answer.

How does Euro VC use AI?

Euro VC uses AI-supported analysis across approximately 80% of its scouting and investment workflow stages, providing analysis and decision support rather than autonomous control. The system searches for companies, compares opportunities, tests investment assumptions, examines risks and monitors portfolio developments. Euro VC aims to extend this to more than 90% of workflow stages before 2030, as an operational objective. People remain responsible for every investment decision.

The next investment advantage will be better judgement at greater scale

For most of investment history, access created an advantage. The best-connected firms saw opportunities before everybody else.

Access still matters. It is no longer enough.

The next advantage will come from examining more opportunities, learning from more decisions and finding evidence that other investors overlook. AI makes that possible at a scale no traditional investment team can match.

It will not make investment risk disappear. It will change who can understand that risk fastest.

At Euro VC, we believe the strongest investment process combines the reach and memory of machines with the responsibility and judgement of experienced people.

Europe builds the future. We back it.

This article is provided for general information only. It is not personal investment advice, an offer or a recommendation to invest. Venture capital investments involve substantial risk, are illiquid and may result in the loss of invested capital.

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