Who Let the Bots Out?: 2026 AI Portfolio Performance Showdown

Can AI effectively manage risk and deliver returns in real-world markets? To answer this question, we have deployed seven of the most advanced AI platforms.

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William Capada

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As artificial intelligence transitions from a conversational tool to a strategic partner, its ability to navigate complex financial markets has become a key area of interest for investors and technologists alike.

Can AI effectively manage risk and deliver returns in real-world markets? To answer this question, we have deployed seven of the most advanced AI platforms such as ChatGPT, Gemini, Copilot, DeepSeek, Perplexity, Meta AI and Grok to act as portfolio managers.

Key takeaways

  • June 2026 marked a strong turnaround for AI portfolios, with most models outperforming their benchmarks after a difficult May.
  • Gemini was the standout performer of the month, leading three of the four risk profiles: conservative at 11.50%, moderate at 12.76%, and aggressive at 16.50%. DeepSeek topped the neutral category at 5.24%.
  • Meta AI was the most consistently strong performer, posting gains across all four risk profiles, while ChatGPT recorded the steepest loss of the month, falling 21.77% in the aggressive portfolio.
  • Benchmark indices lagged behind most AI portfolios in June, with the S&P 500 falling 1.32% in both moderate and neutral, while the Russell 2000 gained a more modest 4.08% in aggressive and the S&P 500 Low Volatility Index rose 4.95% in conservative.

What is the 2026 AI Portfolio Performance Showdown?

The 2026 AI Portfolio Performance Showdown is a year-long experiment running from January 2026 to December 2026. It is designed to test how different artificial intelligence models make real-world investment decisions over a full market cycle.

The project aims to assess how AI interprets market conditions, balances risk and return and adapts its strategy as economic and market data evolves throughout the year. By tracking decisions over 12 months rather than relying on short-term predictions or hypothetical scenarios, the project provides a more realistic view of AI-driven investment behaviour.

All portfolios are constructed and managed under consistent rules, allowing for direct comparison between models and risk profiles within an Australian market context. The results displayed are updated monthly, with rankings based on total return adjusted for the specific risk parameters of each portfolio profile.

How are the portfolios built and tested over time?

At the start of the project in January 2026, each AI model is asked to construct four separate 10-stock portfolios and assign a percentage weighting to each stock. Each portfolio reflects a different risk appetite commonly seen among Australian investors and is designed to operate within the realities of the local share market.

The four risk profiles are:

  • Conservative, focused on capital preservation and reliable income

  • Moderate, balancing long-term growth with steadier returns

  • Aggressive, targeting higher growth through more volatile sectors and smaller companies

  • Neutral, designed to broadly track overall market performance

Once the initial portfolios are established, the project moves into a monthly review cycle that runs through to December 2026. At each review point, the AI models must decide whether to keep existing stocks unchanged, adjust position sizes to increase or reduce exposure, or replace stocks if they no longer align with the portfolio's objectives. All decisions must remain consistent with the portfolio's original risk profile.

This combined process tests both the quality of each AI model's initial stock selection and its ability to adapt strategy over the course of the year.

How are the results measured and reported?

Portfolio performance is tracked from January 2026 through December 2026 using total return, which includes both price movements and income such as dividends. Results are updated monthly to reflect portfolio changes and market performance over the same period.

Portfolios are ranked within their respective risk categories rather than against all portfolios combined.

At the conclusion of the project in December 2026, the full year of results will provide a complete view of how each AI model performed across different market conditions.

Important: This test covers performance over a relatively short timeframe. Results for individual funds, portfolios or indices during this period may not reflect how they perform over the long term. Past performance is not a reliable indicator of future returns.

Monthly Leaderboard: June

Which AI model is navigating the market most effectively? This leaderboard ranks AI models based on the performance of their portfolios over the month. Results are calculated using the percentage return generated by each portfolio, providing a clear comparison of how each model's investment strategy has performed.

Conservative

June 2026 delivered a strong result for conservative AI portfolios, with most models posting solid gains.

Gemini was the standout performer, rising 11.50% to lead all conservative portfolios. ChatGPT also performed strongly, returning 10.82%, followed closely by Grok at 10.43%. Meta AI added 4.98% and Perplexity gained 3.93%. On the downside, Copilot declined -3.52%, while DeepSeek recorded the steepest decline at -5.85%.

The benchmark portfolios also posted gains this period, with the S&P 500 Low Volatility Index returning 4.95%, while the iShares Core U.S. Aggregate Bond ETF added a more modest 0.30%.

Moderate

June 2026 brought a strong turnaround for moderate AI portfolios, with most models outperforming both benchmarks.

Gemini was the standout performer, surging 12.76% to lead the field by a wide margin. Grok also posted a solid gain of 5.90%, closely followed by Meta AI at 5.65%. Copilot added a more modest 2.44%. On the downside, Perplexity slipped -3.58% and ChatGPT declined -2.92%, while DeepSeek was the clear laggard, falling 10.39% after topping the field in May.

The benchmark portfolios lagged behind most models this period, with the S&P 500 falling 1.32%, while the S&P/ASX 200 edged up a modest 0.56%.

Aggressive

June 2026 delivered a sharply divided result for aggressive AI portfolios, with the field split between strong gains and steep losses.

Gemini was the standout performer, surging 16.50% to lead all aggressive portfolios for the period. Meta AI also delivered a strong result, gaining 13.32%, followed by DeepSeek at 11.82%. On the downside, ChatGPT recorded the steepest decline at -21.77%, followed by Perplexity at -17.34% and Copilot at -11.83%. Grok slipped 9.73%.

The benchmarks posted more modest gains by comparison, with the Russell 2000 rising 4.08% and the Vanguard MSCI Index International Shares ETF returning 3.03%, results that Gemini, Meta AI, and DeepSeek all comfortably exceeded.

Neutral

June 2026 brought a mixed result for neutral AI portfolios, though most models still outperformed a weak S&P 500.

DeepSeek led the field, returning 5.24%, followed by Grok at 3.11% and Meta AI at 1.35%. Perplexity and Copilot were broadly flat, slipping 0.93% and 1.79% respectively, while Gemini edged down just 0.45%. ChatGPT was the weakest performer, falling 3.34%.

The S&P 500 declined 1.32%, trailing most AI portfolios in the neutral category, while the S&P/ASX 200 gained a modest 0.56% for the period.

 

What stocks did each AI model choose?

The AI models were asked to build a 10-stock portfolio in January 2026. The portfolios are reviewed monthly, giving each model the opportunity to add or remove stocks and adjust portfolio weightings based on its assessment of current market conditions.

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Written by

Insights Analyst

William Capada is an insights analyst at Finder. With years of experience as an analyst, he has honed his skills in analysing complex datasets and extracting actionable insights. Proficient in various analytical tools, he has a proven track record of delivering meaningful insights that drive strategic decision-making. William conducts research related to economic data and is also responsible for updating the insights statistics pages. He also assists in ensuring that the scoring makes sense for the Finder Retail Awards. See full bio

William's expertise
William has written 5 Finder guides across topics including:
  • Data Analysis
  • Data Visualization
  • Retail Awards
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