- Many wealthy households employ sophisticated teams of money managers who cater to their every financial need. These services are out of reach for most Americans. But AI has the tremendous potential to democratize access to this support.
- Well-designed AI agents can help anyone save and invest more effectively, ultimately operating as your personal CFO. This evolution will mirror the phased progression of self-driving vehicles, but instead with “self-driving money.”
- First solved are single tasks, like saving money on loans or insurance policies. Next comes intelligent, automated decision-making customized to your financial goals. And finally, agents that act on their own and negotiate for you, profoundly disrupting the value chain of search, advertising, marketplaces, and brokerages of financial products.
- To achieve this future, it’s not enough to simply build the best agents. One must also conquer roadblocks of data integration, complex decision-making, regulations, and trusted security.
KEY INSIGHTS:
The concept of the “family office” dates back to 1901. After his lucrative sale of an iron mine to U.S. Steel in 1901, John D. Rockefeller assembled a dedicated team of trusted advisors to manage every aspect of his family’s financial life — from investments and budgeting to insurance, wealth transfer planning, tax strategies, and philanthropy. The office played a critical role in preserving and growing the Rockefeller family’s wealth over multiple generations.
More than 100 years later, wealthy families still rely on these elite wealth teams. But access to such white-glove financial services comes at a steep price. To qualify, you typically need at least $1 million in investable assets. For the most exclusive services, $30 million or more. People with more average means may turn to investment advisors or tax accountants, but rarely do they get a fully integrated financial strategy designed to optimize every dollar and build wealth.
What if this didn’t have to be the case? What if AI could make the benefits of a family office or private wealth advisor accessible to anyone? Why not have an AI agent that is a personal CFO for you and your family?
Recent advancements in large language models and AI’s ability to reason and automate tasks are starting to make this vision a reality. While AI chatbots like ChatGPT have dazzled users with their ability to provide information and generate content, AI agents take innovation to the next level by actively performing tasks. In one of the first such examples, OpenAI recently announced that a ChatGPT feature called “Operator” will automate tasks typically done through web browsers, such as planning trips or ordering groceries.
In the financial arena, AI agents could be equipped with a household’s unique financial data and goals in order to do everything a human wealth advisor can: anticipate needs, offer personalized recommendations, make informed decisions, and execute complex financial transactions. These AI financial agents (the first iterations of which are already in development) can deliver a level of holistic financial management once reserved for the 1 percent.
Such capabilities go well beyond what’s currently available on financial aggregation platforms, which often require users to manually evaluate and act upon complex options. AI agents remove this friction by combing through hundreds of options to intelligently identify the best financial products and enabling seamless, one-click transactions. Companies like ours are already deploying such AI agents to automatically help individuals save on essentials like home and auto insurance, optimizing credit cards cashbacks, or refinance loans. It’s simple. Save money. And don’t lift a finger.
This is just the beginning. The real magic happens when savings culled from these and other sources are automatically invested to generate long-term wealth. One of our models shows that small, AI-guided adjustments over the span of 30 years can yield up to 40% more savings for retirement. This could be a game-changer for Gen Z consumers, many of whom face a rising cost of living and anxiety about achieving financial security.
“One of our models shows that small, AI-guided adjustments over the span of 30 years can yield up to 40 percent more savings for retirement.”
A lot of technical work still has to happen for all these pieces to come together. But AI moves at a rapid clip. And what I’m seeing makes me incredibly excited about how democratizing wealth management can make a meaningful difference in people’s financial lives.
The evolution of self-driving money
Despite the undeniable appeal of saving and growing wealth, many consumers remain understandably cautious about entrusting their financial affairs to a software program. This hesitation stems partly from a strong tradition of self-management—approximately 70 percent of Americans handle their savings and retirement planning largely on their own. Because of this, I believe the adoption of AI financial agents will follow a phased progression, much like the evolution of self-driving cars.
Today, fleets of robo-taxis operate in cities like San Francisco, Austin, and Phoenix, but that “overnight” success was decades in the making. Automation began in the 1970s with features like cruise control. Gradually, innovations like automated steering, braking, and smart parking have ushered in limited autonomous driving, which still requires human supervision. Fully autonomous, nap-while-you-ride cars for consumers are coming, but they still need a higher comfort level among the car-buying public and more legislative support.
| Self Driving Car Level | Financial Autopilot Level |
|---|---|
| Level 0: No Automation Fully manual driving. The driver is responsible for all aspects of driving. | Level 0: No Automation Consumers manage all financial decisions manually—paying bills, managing debt, and investing without assistance. |
| Level 1: Driver Assistance Basic assistive features like cruise control or lane-keeping. The driver remains fully in control. | Level 1: Task-Specific Automation The system can automate individual, isolated financial tasks (e.g., auto-bill pay, robo-advisors for investing). |
| Level 2: Partial Automation The vehicle can control both steering and speed under certain conditions, but the driver must monitor at all times. | Level 2: Financial Copilot AI has a holistic view of the user’s financial landscape, providing coordinated insights, recommendations, and planning across multiple domains (e.g., budgeting, debt repayment, investing). |
| Level 3: Conditional Automation The car can handle most driving tasks in limited conditions, but the driver must be ready to intervene. | Level 3: Limited Automation AI agents begin automating certain higher-level financial tasks—like optimizing insurance, refinancing mortgages, or consolidating debt—often in coordination with multiple financial institutions. The user must approve or finalize these actions. |
| Level 4: High Automation Fully autonomous driving in most conditions, though limited by specific areas or environments (e.g., urban zones). | Level 4: Full Automation AI agents autonomously handle most financial tasks—such as reallocating investments, making payments, and opening or closing accounts—with minimal oversight from the user. |
| Level 5: Full Automation Fully autonomous driving in all conditions. No human intervention is required. | Level 5: Super Automation AI agents manage all aspects of personal finance with such high speed, precision, and frequency of transactions that user oversight is neither required nor practical. |
“I believe the adoption of AI financial agents will follow a phased progression, much like the evolution of self-driving cars.”
Similarly, the journey to fully automated money management has begun with basic, “cruise-control” features. Auto-save tools at banks, for instance, provide a simple, hands-off way for consumers to grow their savings, while robo-advisors on platforms like Wealthfront and Betterment handle basic portfolio creation and rebalancing.
The next phase promises to provide even greater value for consumers. AI financial agents will aggregate a person or household’s full financial picture—investments, savings, expenses, and debts—into a comprehensive model, enabling strategic recommendations. Imagine asking your digital advisor: “Should I get a new credit card? Do I need life insurance? How can I retire with $5 million?” An agent might advise, for instance, to focus on paying down debt before contributing more to an investment portfolio. AI agents can also help consumers save tangible dollars by automating time-consuming tasks like identifying better insurance policies, refinancing mortgages, or consolidating debt. Surveys indicate that one of the main reasons people don’t refinance their mortgages is the perceived hassle of the task and the uncertainty of calculating the costs—obstacles AI could entirely eliminate.
Over time, these solutions will evolve into “self-driving money.” Consumers who opt in could allow their AI agents to execute financial actions on their behalf, such as managing all of their investment and retirement accounts from health savings accounts and IRAs to 401(k) and taxable brokerages. Just as wealthy clients trust human advisors to handle intricate financial details, users will develop confidence in their digital agents and delegate more decision-making.
Eventually, as AI systems become even smarter, they will be capable of superhuman money management. They will be able to automate all aspects of a user’s personal finances with such high speed, precision, and frequency of transactions that user oversight is neither required nor practical.
The end of marketing as we know it
The coming era of AI personal finance agents represents not only a groundbreaking approach to managing money, but also a seismic shift in how consumers interact with financial products. With AI agents scouring the digital landscape on behalf of users, fewer consumers will search directly for loans, credit cards, insurance, and other financial offerings. This shift will have profound implications for advertising and marketing strategies.
“The coming era of AI personal finance agents represents not only a groundbreaking approach to managing money, but also a seismic shift in how consumers interact with financial products.”
If AI agents become as ubiquitous as many predict—both in financial services and beyond—brands will need to direct their efforts toward engaging these digital intermediaries. Marketing in this new landscape will no longer be aimed at human consumers, but at their AI emissaries. This could mean companies creating their own specialized AI agents to “negotiate” and interact with consumer agents, effectively turning marketing into a form of machine-to-machine communication. In this strange future, companies that rely heavily on traditional advertising models and search engine optimization could face significant challenges.
Similarly, intermediaries like financial aggregators or brokers could be disrupted if they don’t offer deep customization or value-added insights. Why browse aggregator sites or marketplaces if your personal AI agent can instantly check hundreds of offers and pick the best one? Why use a broker if an agent can perform the services instantly for zero fee?
While this may sound dystopian on the surface, the real winner in this future is the end consumer. This era brings: less time searching, no manual paperwork, finding the best products at the best rates, and peace of mind that an agent is monitoring for better options truly around the clock. Analogously, the providers of financial products can no longer just rest on their laurels of “brand,” rather this intensely agentic meritocracy pushes them to always be innovating improved financial products and cheaper rates.
The barriers to overcome
Promises about AI’s transformative potential are everywhere. While skepticism about the timelines for these advancements may be warranted, I have little doubt that AI will be one of the defining technologies of our lifetime. However, challenges remain before intelligent digital wealth managers can become a reality.
The first hurdle is data integration. Financial information is typically scattered across multiple siloed systems—banks, credit cards, credit agencies, investment accounts, retirement plans, and insurance companies—each with unique protocols and formats. Developing robust systems to securely integrate and analyze data from these disparate sources is a monumental task, requiring the merger of often antiquated systems. Many SaaS companies have attempted to solve this problem, but with AI agents, we might actually have a chance to make it a reality.
Next, AI’s capabilities must continue to evolve to handle the complexities of financial decision-making and automation. Managing finances involves subtle nuances, emotional factors, and long-term considerations that demand more sophisticated and intuitive AI systems to really understand the users beyond simple preferences.
Finally, for these systems to succeed, guardrails are essential. Consumers will only trust AI to handle their finances if they believe their data is secure and that the technology operates ethically. Regulatory frameworks will play a crucial role in ensuring both security and fairness. Trust in AI itself is also a key factor. Companies developing these systems will need to implement strong controls to monitor AI decision-making and provide transparency when needed.
I believe 2025 will be the year consumers begin to truly experience the value AI agents can bring to their daily lives. While achieving fully automated financial management will take time, the allure of effortless, “always-on” wealth management makes it less a question of if and more a matter of when.
This is an idea whose time has come. Broadening access to sophisticated money management expertise beyond the grip of modern-day Rockefellers is long overdue. AI agents are our best shot at making that happen.
