In a career that has spanned decades, I’ve seen many innovations that promised to change the world. Some lived up to the promise; others were fleeting moments in a never-ending cycle of software and hardware hyperbole. But I can’t recall a development quite like generative AI—artificial intelligence designed to generate new data from existing patterns.

Very soon, it will become sentient.

One sector facing absolute transformation is Finance. Tracking funds, in particular, present a full-on revolutionary opportunity. The whole landscape of financial transparency and accountability could be on the cusp of a sea change, and here’s why.

In the complicated labyrinth of finance, the task of tracking funds has been a Sisyphean accomplishment. Be it government spending, venture capital distribution, or your everyday banking, the stakes are high, and the room for error is a perilous cliff that many have unfortunately fallen off. It’s a realm full of numbers, ledgers, spreadsheets, and, yes, sometimes malfeasance.

Tracking funds, often called “tracker funds” or “index funds,” are investment funds designed to replicate the performance of a particular market index. The aim is not to outperform the index, but to mimic its activity as closely as possible. These funds can track various types of indices, such as stock indices, bond indices, or commodity indices. The idea is that by matching the index, the fund will provide a return that is consistent with the portion of the market that the index represents.

Here’s how they generally work:

The fund manager invests in the same assets and in approximately the same proportions as the index it aims to track. For instance, a fund that tracks the S&P 500 will invest in the 500 stocks that make up that index.

Unlike actively managed funds, where the fund manager makes specific investments with the aim of outperforming an index, tracker funds are passively managed. This often results in lower fees for investors because the fund is not paying for research or the expertise of a high-profile manager.

Because many indices contain a broad array of securities, investing in a tracking fund can provide built-in diversification. For example, an S&P 500 tracking fund provides exposure to 500 different U.S. companies across various sectors.

Tracking funds usually have lower costs compared to actively managed funds. They often have lower turnover rates, resulting in fewer transaction costs. This is an appealing feature for many investors.

Many tracking funds also offer a dividend reinvestment option, enabling investors to automatically reinvest dividends to purchase additional shares, thereby potentially accelerating the growth of their investment over time.

No tracking fund can replicate its target index perfectly, due to fees, transaction costs, and other practical constraints. The difference between the fund’s performance and the index’s performance is known as the “tracking error.” A lower tracking error indicates a fund that more accurately tracks its target index.

Tracking funds are generally transparent, disclosing their holdings regularly, and are straightforward about their fees and other costs. This makes it easier for investors to understand what they are investing in and what they are paying for.

Tracking funds come in various forms, including mutual funds and exchange-traded funds (ETFs), providing flexibility in how they can be bought and sold. ETFs can be traded throughout the day at market prices, while mutual funds are bought and sold at the day’s closing net asset value (NAV).

Now imagine, if you will, an AI that can not only analyze past and current financial transactions but can predict future flows based on existing data. An AI that understands, interprets, and even foresees financial trends so accurately that fraudulent activities could be detected before they even occur. We’re talking about a level of financial scrutiny, heretofore impossible, that comes with an invaluable attribute: trust.

In the burgeoning landscape of cryptocurrencies and decentralized finance, the potential of generative AI is even more promising. With blockchain technology offering a kind of transparency we’ve not seen before, the addition of AI can make these platforms as secure as Fort Knox. The AI will generate data models to monitor the consistency of transactions, flagging anything that seems amiss and thereby averting financial catastrophes before they happen. It’s like having an eagle-eyed sentinel that never sleeps, always on the lookout for inconsistencies that could signal everything from simple errors to complex financial crimes.

However, as with any technological advancement, there are looming questions that continue to pull at our coats. The ethics surrounding the use of AI in finance are as intricate as the algorithms that power it. Who owns the data that the AI uses and generates? In a world where our financial transactions could be scrutinized by an ever-watchful AI, the boundaries between security and invasion of privacy blur. These are questions that invite not just technological scrutiny but a robust legal debate. Which takes time. Time we don’t have.

So, generative AI could well be the herald of a new age in financial tracking, laden with both remarkable opportunities and some twisty trails. The pathway it opens for accountability and efficiency is groundbreaking, but it also nudges us closer to confronting ethical dilemmas that we always manage to sidestep.

In the final reckoning, generative AI in finance holds a mirror up to society’s values, forcing us to ask what we prioritize more—efficiency or privacy, transparency or autonomy.

As we stand at this juncture, one thing is clear: generative AI is not just a technological marvel; it’s a societal game-changer, poised to reshape the very fabric of our financial institutions. And as we wade through these uncharted waters, I can only hope that we navigate with both the wisdom of experience and the courage to face the unknown.

But, when I watch videos of congressmen debating topics about which they have no knowledge, yet absolute authority, I am not encouraged.