Young “time billionaires” are more willing to take investment risk and more willing to let AI manage their money

Overview

This report is Deutsche Bank’s interdisciplinary thematic research discussing why so-called “time billionaires”—young investors expected to still have more than 1 billion seconds, or about 31.5 years, of life ahead—are more willing to take investment risk and more willing to let AI manage money and trading. The report focuses on investors in the United States and the United Kingdom, especially those under 55.

Core views

The report’s core view is that younger investors not only want to raise their investment risk relative to current levels, but are also more willing to rely on AI for portfolio management. The younger the age group, the more likely they are to say they will increase their risk tolerance over the next 1, 3, and 5 years. The report does not simply attribute this change to AI, but argues that social investing, behavioral psychology, aspiration inflation, and the market and social environment in which younger people grew up together shape this risk preference.

Analysis framework

The report uses proprietary Deutsche Bank dbDataInsights data, breaking down investor attitudes toward risk and AI advisory by age, country, and time frame, and combines behavioral finance and social trends to explain changes in risk appetite.

Methodology notes

• Behavioral financeInvestor risk appetite segmentation

  Observe changes in risk tolerance by age and time horizon

  The report compares the willingness of investors of different ages to increase investment risk over the next 1, 3, and 5 years to judge whether younger groups show higher risk appetite.

• Thematic researchAI advisory acceptance analysis

  Degree of reliance on AI to manage money and trading

  The report examines whether investors want AI to manage portfolios and trading, and links this preference with age and country dimensions.

• Behavioral psychologySocial investing and aspiration inflation

  Social comparison and rising wealth targets affect risk-taking

  The report argues that social investing trends and aspiration inflation push younger investors to seek higher returns, thereby increasing their willingness to bear risk.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Wealth management and brokerage platforms

  Directly benefit from rising demand among younger investors for risk trading and AI tools

  Strengths

  Can enhance customer stickiness through AI advisory, automated portfolio management, and personalized risk profiling

  Weaknesses

  Need to bear higher suitability, compliance, and model governance requirements

  Comparison

  Compared with traditional human advisors, AI tools may be easier to scale in serving younger clients

  Risks

  If AI advice misguides risk-taking or market volatility intensifies, it may trigger client losses and regulatory pressure

• Bank research and advisory business

  The report’s theme is relevant to bank wealth management and research products

  Strengths

  Can use proprietary data and research capabilities to explain changes in investor behavior

  Weaknesses

  Research conclusions rely on surveys and proprietary data and do not provide ratings on tradable targets

  Comparison

  Thematic research is better suited to judging long-term product and client behavior trends rather than short-term stock selection

  Risks

  Growing social dislike of AI may weaken the pace of AI advisory adoption

• AI investment management tools

  Younger investors say they are more willing to let AI manage money and trading

  Strengths

  Can meet demand for automated, personalized, and low-cost investment management

  Weaknesses

  Model reliability, explainability, and responsibility boundaries still need validation

  Comparison

  Compared with purely human services, AI is more suitable for reaching retail clients at scale

  Risks

  Model errors, excessive trading, risk mismatches, and regulatory uncertainty

Key data

• Report date2026-07-22The cover discloses the date as 22 July 2026.
• Research institutionDeutsche BankThe report was published by Deutsche Bank Research.
• AuthorsLuke Templeman, CPA; Galina PozdnyakovaThe cover lists two research analysts.
• Definition of time billionaireMore than 1 billion seconds, about 31.5 yearsThe report says that if one is expected to still have more than 1 billion seconds of life ahead, one can be called a “time billionaire.”
• Key populationInvestors under 55 in the United States and the United KingdomThe report says this group is especially eager to raise risk tolerance and rely more on AI to manage portfolios.
• Observation time framesNext 1 year, 3 years, and 5 yearsThe report uses these time frames to observe younger groups’ willingness to increase investment risk.

Impact & implications

For wealth management, brokerage, banking, and investment platforms, rising risk appetite among younger investors and greater acceptance of AI advisory may drive increased demand for AI investment tools, automated portfolio management, and social investing products. But this also raises the importance of suitability, investor protection, model risk, systemic risk communication, and compliance disclosure.

Risks

• Weak consumer confidence coexisting with rising risk appetite may reflect a disconnect between investor behavior and macro reality.
• Global systemic risk is seen by experts as increasing, and greater leverage or risk exposure at the household level may amplify losses.
• Growing social opposition to AI may affect acceptance of AI advisory and the regulatory environment.
• Using AI for investment advice and trading involves model risk, insufficient explainability, and unclear accountability.
• The report is thematic research and does not constitute a recommendation to buy or sell specific financial instruments.

What to watch

• Actual changes in young investors’ allocation to risky assets in the United States and the United Kingdom over the next 1, 3, and 5 years.
• User growth and retention for AI advisory, automated portfolio management, and social investing platforms.
• Regulatory requirements for AI investment advice, suitability obligations, and model disclosure.
• Whether consumer confidence, market volatility, and systemic risk indicators diverge from risk appetite.
• How wealth management institutions balance AI efficiency, client protection, and compliance responsibilities.