Topic: Investor participation
A few years ago, a newly appointed bank director came to me upset about his tax refund. He had invested in a voluntary pension fund through our digital platform, quickly and confidently, expecting a refund of a certain size. The refund came in lower. The platform had offered him a calculator, a short instructional video and the option to speak to an advisor. He had skipped all three.
I sat down with him and worked through the two formulas side by side, using his own numbers, and the gap became simple arithmetic. He left satisfied. I left with a lesson that has stayed with me: a well-built digital journey can carry a capable, intelligent person all the way to a significant decision without the understanding that decision needs.
That lesson feels even more relevant as artificial intelligence enters the world of investing.
What AI does well
I use AI tools every day, for research, for improving my drafts and for testing my own thinking. I have long dialogues and brainstorming sessions with AI agents. In investing, their strengths are real. AI can read vast amounts of information, compare scenarios, spot patterns and explain unfamiliar ideas in plain language. Used well, it helps people ask better questions and arrive at a conversation with an advisor better prepared.
I have always been an early adopter. I launched and used one of the first mobile equity trading apps in my market in 2008 and was using video conferencing platforms years before the pandemic made them part of everyday life. New tools excite my curiosity, and AI is the most powerful one I have seen.
Information and judgment are different things
Investors today have more information than at any time in history: market data, company disclosures, commentary, research tools and now instant AI analysis. Investing, however, has always been about more than information. It is about context, behavior, priorities and time.
The right decision depends on a person’s goals, their need for cash, their tolerance for risk, their time horizon, their taxes and their ability to stay calm when markets fall. An answer can be fluent and confident and still miss the one detail that matters most for that person. Its quality depends on the information it receives, the question it is asked and the limits of the model behind it.
I think of AI as an intelligence layer that strengthens analysis through reviewing research. Judgment remains a human responsibility.
The human side of investing
Markets are shaped by numbers, and investor decisions are shaped by people. Fear can push an investor out of a sound plan during a downturn. Overconfidence can encourage too much risk after a strong year. Impatience can turn a long-term goal into a series of short-term reactions.
At the Pakistan Stock Exchange, we built a trading simulator where students and first-time investors could manage a practice portfolio with virtual money. What made it work was the people around it. I invited brokerage firms to voluntarily join to coach participants, answering questions in a chat window and offering tips without taking over. The tool gave people practice; professionals would add the perspective, and the trading simulator becomes an incubator of sorts for nurturing knowledgeable investors. That pairing is the model I see for AI in investing.
Augmented intelligence
I prefer the term augmented intelligence: technology that extends what people can understand and achieve. For investors, that means clearer explanations, side-by-side comparisons and better preparation for a conversation with a qualified professional. For financial institutions, it means sharper research, better support for advisors and education that meets each customer where they are.
The opportunity is large, because financial knowledge has never been evenly shared. Responsible AI can help many more people engage with money. They will also need the financial literacy to evaluate what they are told, the confidence to question an answer and the judgment to know when a decision calls for qualified advice. The OECD’s recent paper on artificial intelligence and personal finance makes the same point, pairing the promise of accessibility and personalization with the risks of bias, inaccurate outputs, privacy and exclusion.
Trust stays at the center
In financial services, a poor decision can have lasting consequences, which places a particular responsibility on institutions adopting AI. Customers should know what role technology plays in a recommendation, how their information is used and when a person reviews the outcome. Institutions should own the accuracy of their systems and the safeguards around them.
The goal is to help people make decisions that serve their long-term interests. Clear governance, sound data practices and a defined place for human review are what make that possible.
A closing thought
The future of investing brings the strengths of machines and people together. Machines help us process more, faster. People bring experience, empathy, ethics and an understanding of what a financial decision means in the context of a life. As AI grows more capable, good judgment becomes more valuable, and the real promise of AI is that it helps us make our decisions better.
As AI grows more capable of analyzing markets and recommending investments, where would you draw the line between what technology decides and what stays a matter of human judgment?