Ahon Sarkar is the General Manager of Helix by Q2, which empowers innovative companies to build personalized BaaS products.
This article was not written by ChatGPT. I want to establish that upfront because, according to news headlines I’ve seen, AI is going to take all our jobs. I’m not suggesting that AI won’t drastically change work as we know it or take a percentage of jobs over time, particularly service-level jobs. However, what we’re seeing now, and what I expect to play out over the next five years, is AI being used to augment rather than replace people. I believe AI will enable humans to focus on areas where they’ll add the most value. Here’s why:
AI Can Expedite Customer Service Experiences
Not too long ago, if you needed to report suspicious charges on your credit card, you’d call the card company, get a recording saying all of the agents were busy and have the option of getting a call back. Unfortunately, that call back might come 45 minutes later, when you were in the middle of something else. Then, you’d have to stop what you were doing and explain the problem to the agent, who would likely put you on hold while they resolved the issue.
With AI, you can spend just a few minutes feeding the relevant information to a bot, so by the time you reach a representative, 95% of the problem has been resolved. The human might ask a few clarifying questions, but a process that could have taken hours has been shortened for both you and the person on the other line.
And it’s not just suspicious credit card charges. Today, if you have any kind of question, there are all sorts of AI tools that can act as a first line of defense in helping you answer it.
AI Can Cut Down On Time And Costs
Now, let’s look at an even more dramatic example of how AI can systematize lower-value tasks. In my own company, we needed to document about 2,000 internal jobs.
Traditionally, we’d ask one of our development teams to have their engineers go through and document every single job, which would take about two weeks and cost roughly $30,000. Instead, one of our lead architects offered to document the jobs using generative AI (through Azure’s OpenAI). He said he might need a few hours, but he ended up finishing the project over his lunch break for a total cost of $6.50.
The output was generally indistinguishable from what a human engineer would have produced for a relatively straightforward task and freed up capacity for the engineers to work on solving actual problems for our clients, which is much more meaningful for them and delivers better ROI for the company.
AI Can Scale Personalization
In our final example, let’s talk about how AI can be a tool to assist bank customers in much the same way as humans. Before digital banking, consumers went to their local community bank to open an account. Bankers got to know their customers through personal conversations, so they could offer financial advice on an individual basis.
Historically these deep relationships have given community banks a competitive advantage over larger institutions. But today, nearly half of consumers are more likely to open a new financial account via a digital channel, and consumers are increasingly turning to challenger banks. One recent study found that 43% of accounts opened in 2023 were with fintechs. These institutions often offer low fees and an easy-to-use digital platform but don’t have the capacity to give each of their customers individualized service.
This is unfortunate for the 41% of consumers who want their banks to provide more personalized offers or information to help them achieve their financial goals. They could pay a wealth manager, but for someone with a small amount of money in their account, that can hurt more than it helps.
Instead of the number of staff dictating the level of involvement with customers, organizations can use AI to help ensure that every customer gets a targeted and useful experience. Recommendations and interactions can all be systematized through data capture. We can create a framework that can enable a completely individualized approach to financial planning for even the lowest-income Americans.
Fintechs like Acorns and Betterment have already partially automated building savings. The next step is to offer personalized guidance and advice (think of Iron Man calling his trusty butler, Jarvis, with an endless string of questions). For example, let’s say I want to buy a new car, and I’m not sure if I should buy the car with a minimum down payment and large loan or vice versa. There’s no one-size-fits-all answer to that question, but an AI-supported banking app could synthesize information like my debt-to-income ratio to give me an answer—complete with a paragraph explanation about debt-to-income ratios. I beieve this the future of financial education: information delivered in the moment, when you need it.
Thanks to the democratization of data and robust infrastructures that allow for connections into cloud-based AI computing, in the next decade we could all have a Jarvis in our pocket. Individuals can benefit in the short run by getting practical advice, and in the long run because of the implicit educational aspect. Society can benefit because better individual financial decisions make for a healthier economy. When looking at how AI will impact our lives and work, we need to remember that it will act as a force multiplier for humans. But we’ll still need humans.
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