I believe that in my field of finance, AI is currently being used to gather information on the stock market and giving estimations for fair valuation of financial assets. I have heard from professors previously that they use AI to write code for algorithmic trading strategies. I think if we look more towards the consultancy side of business administration I have seen during an internship last year that it’s used to gather information about specific companies to invest in, the sectors they are part of and potential growth opportunities. It was also used to help create slideshows and presentations quickly. For academic purposes I currently ask AI to help explain finance concepts and test by understanding by creating practice questions solidifying my knowledge on the topic I am examined on.

AI Suggestions on its uses in finance:

AI is already reshaping finance, and its role will deepen across several core functions. The trajectory isn’t speculative—it’s visible in how major institutions are allocating capital and redesigning workflows.

Trading and Investment Management
Quantitative funds and banks like BlackRock and Goldman Sachs use AI for signal generation, portfolio optimization, and execution timing. Machine learning models can process alternative data (satellite imagery, transaction data, sentiment feeds) far beyond human capacity.

Expect increased use of reinforcement learning for dynamic trading strategies.

AI-driven funds will likely outperform traditional discretionary approaches in highly liquid markets, though they may still struggle in regime shifts.

Risk Management and Fraud Detection
Banks such as JPMorgan Chase deploy AI to detect anomalous transactions in real time.

Models identify fraud patterns that rule-based systems miss.

In credit risk, AI refines probability-of-default models using nontraditional data sources, improving underwriting precision.
This is one of the most mature and high-ROI applications.

Retail Banking and Personal Finance
Consumer-facing platforms like PayPal and apps integrated with Bloomberg Terminal are embedding AI assistants.

Hyper-personalized financial advice (spending, saving, investing).

Automated financial planning that adapts continuously to user behavior.
This effectively scales “wealth management” down to mass-market users.

Algorithmic Lending and Credit Scoring
Traditional credit scoring models are being augmented or replaced by AI systems that incorporate behavioral and transactional data.

This expands access to credit in underbanked populations.

However, it raises regulatory scrutiny around model interpretability and bias.

Regulatory Technology (RegTech)
Compliance is expensive; AI reduces that burden.

Automated monitoring of transactions for AML (anti-money laundering).

Natural language processing to parse regulations and ensure institutional compliance.
This is a major cost-saving lever for financial institutions.

Market Intelligence and Research Automation
AI tools can synthesize earnings reports, macroeconomic indicators, and news in seconds.

Analysts increasingly act as “validators” rather than primary information gatherers.

Generative AI will compress research cycles dramatically.

Operational Efficiency and Cost Reduction
Back-office automation (reconciliation, settlements, reporting) is being streamlined.

Expect fewer manual processes and lower operational risk.

This is less visible but economically significant.

Constraints and Risks

AI in finance isn’t frictionless:

Model risk: Overfitting and failure in unprecedented conditions (e.g., crises).

Regulation: Financial authorities demand explainability—black-box models face limits.

Data quality: Garbage in, garbage out still applies at scale.

Systemic risk: If many institutions rely on similar models, market behavior could become more correlated and fragile.

Bottom line

AI won’t just “assist” finance—it will redefine the industry’s operating model. Humans will remain in oversight roles, but decision-making—especially at scale and speed—will increasingly be machine-driven.

If you want, I can break this down into specific career impacts (e.g., which finance roles are most at risk vs. most augmented).

Link to chat: https://chatgpt.com/share/69f66834-81cc-83ea-b148-b3ad0c520f3e

Dr. Rehab Interview Questions:

• “In your view, what are the most visible ways AI is currently impacting the [e.g., Marketing/Accounting] industry today?”
  1. “Do you feel these changes are enhancing the quality of work in the field, or just the speed?”
• “How would you describe the current stance of your department or faculty regarding the adoption of AI tools?”
  1. “Where do you see the most resistance, and what do you think is driving it?”
• “What is a ‘human-only’ skill in [Business/Marketing world] that you believe is becoming more valuable as automation becomes more common?”
• “To what extent have you chosen to integrate—or intentionally exclude—AI from your own professional research or work?”
• “If a colleague suggested a new AI tool to help with your grading load, would you consider it ? What criteria would it have to meet for you to consider it?”
• “How are you currently navigating the challenge of teaching and assessing foundational business concepts when students have access to instant AI-generated answers?”
• “What concerns, if any, do you have about how AI might change the way students develop critical thinking or problem-solving skills?”
• Do you think it is a priority for business students to have ‘AI Literacy’? Should there be courses specifically addressing this?
• “What do you believe is the biggest risk to the business world if we adopt AI too quickly—or too slowly?”–> if people don’t use AI will they lag behind, are there risks of getting used to AI too much/quickly

I interviewed Dr. Rehab Abdelaziz a business and marketing professor at AUC about her thoughts, usage and future outlook on AI. She feels that AI is very close, and says that she always tells students and encourages them to use AI to give them a deeper analysis but not to use it instead of doing the research themselves. She highlighted that her department are quite flexible about the use of AI; they discussed its pros and cons and she feels that “we can’t keep on hiding, and we can’t keep on saying don’t use it”. Moreover, she said that professors in the department use AI to enhance the learning experience. One remark she made which I found quite interesting is how she feels that only a human being has the ability to come up with a creative concept. She feels that you can give AI the idea but you can’t wait on it come up with a creative concept. I totally agree on this point and feel that through my use of AI it lags behind in creating something truly original and creative. She emphasised her use of AI as a tool to get more perspectives on topics and concepts to generate a discussion with students as we witness developments and changes in the marketing and business world. I asked about her thought towards the idea of hypothetically using AI to grade students’ work and she was a bit sceptical about it and would maybe use it to track students AI usage. She brought to my attention that there are some learning outcomes in her course which AI cannot be used as a mean for cheating, such as presentations and in class exams. This made me feel a bit better because I find that in some of the courses, I take students are heavily using AI which makes their work appear lengthier and more impressive, hurting students who do put in their own effort.

Mrs. Bahia interview questions:

• “In your view, what are the most visible ways AI is currently impacting the investment analysis or financial reporting process today?”
• “Do you feel these changes are improving the accuracy of financial modeling/analysis, or just the speed at which you can crunch numbers?”
• “How would you describe the current stance of your firm’s leadership regarding the adoption of AI tools into your daily operations?”
• “What is a ‘human-only’ skill in the finance world that you believe is becoming more valuable as automation scales?”
• “To what extent have you chosen to integrate—or intentionally exclude—AI from your own market research, due diligence, or portfolio construction?”
• “If a peer suggested a new AI tool to help with Automated Spreadsheeting or Data Extraction, would you use it? What specific security and data privacy criteria would it have to meet first?”
• “Do you think ‘AI Literacy’—specifically understanding algorithmic bias and data origin—is a mandatory requirement for the next generation of finance professionals?”
• “What do you believe is the biggest risk to the global markets if we adopt AI too quickly versus adopting it too slowly and losing a competitive edge?”

I also interviewed Mrs. Bahia Ismail, the CEO of Misr Insurance Holding which gave me a richer view on how AI is currently being used in the finance sector. She explained that it is currently being used to speed up the process of investment analysis, making It more structured, comparing more variables, making the decision-making process a lot easier. She highlighted that AI has the ability to process large amounts of data, extracting meaningful statistics and trends. I asked about her experience with the accuracy of Ai outputs and she explained that free tools are less effective that paid ones in terms of accuracy. Moreover, she gave an example and said that she uses Claude’s paid version (pro with opus mode) for complex data analysis, however found that she still needs to review the output as it makes some mistakes. She explained that there isn’t a clear framework for the use of AI tools in the firm she works at, but they are currently testing and trying out different AI tools. She explained that the intuition of gut feeling which guides investment decisions is something getting more valuable in world of finance as AI spreads. The main concern she had with using automated spreadsheeting is potential lack of chat encryption and potential storing of confidential documents to train the AI tool. She had a very similar view to Dr. Rehab and said “if we don’t learn to use AI effectively, we will lag behind or produce work filled with errors and biases”.

I was a bit surprised with the findings; I didn’t expect AI to be currently used in the finance sector in Egypt. I imagined that using AI in a work setting is something a bit far in the future. I didn’t expect paid AI tools to still make mistakes and thought that it could be relied on more. What excites me is further learning about how to use AI for algorithmic trading and complex applications as I find it really interesting and something which can differentiate me from others in the world of finance. I also think that if we can use AI effectively in fraud detection and risk management this would be revolutionary. What scares me is how students are abusing AI tools using it as a way to cheat at exams, projects and assignments. I fear that my work may appear to be simpler in comparison to large blocks of text and figures AI gives as an output. I’m very concerned about the confidentiality of AI tools as I fear it may be a security risk if not managed effectively. As Mrs. Bahia and Dr. Rehab mentioned there are human aspects like the creative concept and gut feeling which make me feel less worried about being displaced by AI in the field. I hope to use what I’ve learned to be more methodical and aware with how I use AI instead of using it haphazardly. I also intend on learning about and trying out different AI tools to get a better grasp of when to use each and what they do best.