Risky Business or Digital Guru? How Pakistan’s Investors Navigate the Hype, Fear, and Promise of AI-Driven Trading

Abstract/Description

Purpose: This research work is conducted to analyze the impact of AI Perception (AIP) on Risk Tolerance (RT) and Investor Behavior (IB) of individual investors in Pakistan and understandings of AI-driven investment tools in decision making within financial markets.

Methodology: We adapted a quantitative research design and collected data through survey responses from 216 individual investors. A structured questionnaire was used to measure the key constructs; all the measures were based on established scales. We examined AIP-RT-IB relationships using structural equation modeling (SEM).

Findings: The results from the analysis indicated that a positive perception of AI significantly enhances risk tolerance as well as enhance investor behavior towards investment. Besides, higher risk tolerance shows a positive effect on investor’s behavior, and the indirect effect of AI perception on investor behavior through RT has been proven partially. Finally, the research identified that higher level of risk tolerance weakens the positive impact of AI perception on investor’s behavior.

Implications: These results suggest that improving AI perception among investors is still significant to increase their risk tolerance and overall investment behavior. This AI-powered tool can be fully utilized to educate the investors and engage them for more insightful decision-making by financial institutions.

Novelty: This work contributes to the emergent literature on investor behavior with valuable insights into how AIP affects RT and IB. It consequently points out the importance of AI perception in shaping investment decisions within emerging markets, hence addressing an important lacuna in prior literature on AI technology issues from the point of view of behavioral finance.

Keywords

AI Perception, Investment Behavior, Risk Tolerance, Retail Investors, Financial Market

Track

Finance

Session Number/Theme

Finance - Session I

Session Chair

Dr. Mujeeb

Start Date/Time

14-6-2025 9:00 AM

End Date/Time

14-6-2025 10:40 AM

Location

MCS 3 Ground Floor, AMAN CED Building

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Jun 14th, 9:00 AM Jun 14th, 10:40 AM

Risky Business or Digital Guru? How Pakistan’s Investors Navigate the Hype, Fear, and Promise of AI-Driven Trading

MCS 3 Ground Floor, AMAN CED Building

Purpose: This research work is conducted to analyze the impact of AI Perception (AIP) on Risk Tolerance (RT) and Investor Behavior (IB) of individual investors in Pakistan and understandings of AI-driven investment tools in decision making within financial markets.

Methodology: We adapted a quantitative research design and collected data through survey responses from 216 individual investors. A structured questionnaire was used to measure the key constructs; all the measures were based on established scales. We examined AIP-RT-IB relationships using structural equation modeling (SEM).

Findings: The results from the analysis indicated that a positive perception of AI significantly enhances risk tolerance as well as enhance investor behavior towards investment. Besides, higher risk tolerance shows a positive effect on investor’s behavior, and the indirect effect of AI perception on investor behavior through RT has been proven partially. Finally, the research identified that higher level of risk tolerance weakens the positive impact of AI perception on investor’s behavior.

Implications: These results suggest that improving AI perception among investors is still significant to increase their risk tolerance and overall investment behavior. This AI-powered tool can be fully utilized to educate the investors and engage them for more insightful decision-making by financial institutions.

Novelty: This work contributes to the emergent literature on investor behavior with valuable insights into how AIP affects RT and IB. It consequently points out the importance of AI perception in shaping investment decisions within emerging markets, hence addressing an important lacuna in prior literature on AI technology issues from the point of view of behavioral finance.