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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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

  • AI portfolios pulled back in September 2026, with 21 of 28 portfolios posting losses after a strong August.
  • ChatGPT was the top performer overall, leading both the aggressive (4.32%) and neutral (-0.16%) portfolios. Copilot led moderate (1.02%) and Perplexity led conservative (0.39%).
  • Only seven portfolios made money this month, and none in the neutral category. Meta AI recorded the steepest loss of the month at -8.81% in the aggressive category.
  • Benchmarks generally held up better than the AI portfolios. The iShares Core U.S. Aggregate Bond ETF (4.78%) and Russell 2000 (4.38%) both outperformed every AI portfolio in their categories, while the S&P 500 (-0.93%), S&P/ASX 200 (-0.66%) and Vanguard MSCI Index International Shares ETF (-3.92%) fell.

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: September

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

September 2026 was a subdued month for conservative AI portfolios, with most posting small losses and none breaking above 0.4%.

Perplexity led the field with a modest gain of 0.39%, followed by DeepSeek at 0.28% and Gemini at 0.20%. On the downside, Grok recorded the steepest decline at -1.60%, followed closely by ChatGPT at -1.37%. Copilot, last month's top performer, slipped -0.45%, while Meta AI dipped -0.24%.

The benchmark portfolios were mixed this period. The iShares Core U.S. Aggregate Bond ETF returned a strong 4.78%, outperforming every AI portfolio, while the S&P 500 Low Volatility Index fell -0.93%.

Moderate

September 2026 was a mixed month for moderate AI portfolios, with August's across-the-board gains giving way to a split field.

Copilot led the way with a 1.02% gain, followed by Gemini at 0.64% and ChatGPT at 0.56%. DeepSeek, last month's standout, edged down -0.21%. Grok recorded the steepest decline at -4.78%, followed by Perplexity at -3.40% and Meta AI at -2.59%.

The benchmark portfolios both declined again this period, with the S&P 500 falling -0.93% and the S&P/ASX 200 dropping -0.66%.

Aggressive

September 2026 was a tough month for aggressive AI portfolios, with all but one model posting losses after August's across-the-board gains.

ChatGPT was the only portfolio in positive territory, rising 4.32%. Perplexity, last month's standout, held up best among the rest with a -1.24% dip, followed by Copilot at -1.93%. The remaining portfolios fell sharply, with Meta AI recording the steepest decline at -8.81%, followed closely by Gemini at -8.74% and Grok at -8.36%. DeepSeek dropped -7.03%.

The benchmarks were split this period. The Russell 2000 rose 4.38%, narrowly ahead of ChatGPT and outperforming every AI portfolio, while the Vanguard MSCI Index International Shares ETF fell -3.92%. Perplexity, Copilot and ChatGPT all finished ahead of the Vanguard benchmark.

Neutral

September 2026 was a difficult month for neutral AI portfolios, with every model posting a loss after August's strong result.

ChatGPT held up best, slipping just -0.16%, followed by Copilot at -0.31%. Perplexity fell -1.34% and Gemini dropped -2.14%. Grok declined -2.57%, while DeepSeek, last month's standout, fell -3.21%. Meta AI recorded the steepest decline at -3.37%.

The S&P 500 declined -0.93% and the S&P/ASX 200 fell -0.66% for the period. ChatGPT and Copilot were the only AI portfolios in the neutral category to outperform both benchmarks.

 

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.

William Capada's headshot

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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