Health insurers could one day set premiums based on predictions about your future wellbeing, employers could determine your productivity and loyalty, and banks might approve or reject your mortgage application using computer-generated analysis.
"I don't want to be too alarmist," futurist and author Gihan Perera told news.com.au.
"But we should care about what artificial intelligence and algorithms might one day determine about us based on the data we freely give over now."
Consumer data is big business and an entire profession is emerging — a new mining boom of sorts — as brands try to figure out how best to use the information they have.
And they have a lot of it.
Kylie Gleeson-Long, managing director of the Australia and New Zealand branch of global customer data science firm dunnhumby, said companies are drowning in information.
"Any company you talk to, every single one of them knows data is important and they have a strategy to collect it as a top priority," Gleeson-Long said.
But according to dunnhumby's research, only half of the world's top 390 retailers are currently using it in any meaningful way.
Less than 1 per cent have figured out how to integrate data in the full spectrum of their end-to-end operations, Gleeson-Long said.
"Finding a way of translating that into personal experiences for customers is a winning formula."
Long before smartphones, GPS, computers and the internet, retailers were savvy about tracking customer behaviours, she said.
"If you think back quite a way, the local store owner knew everything about you, what you liked and didn't like, and could recommend things and proactively order stuff for you.
"As retail grew, the ability to do that became impossible. But now, we can ask more questions in a single day about consumers than earlier retailers would've been able to ask in a single lifetime.
"And with that data, we're able to create personalised, one-to-one experiences in a way that hasn't been possible."
It might mean recommendations about products you're likely to enjoy — not merely because you've purchased them before, but because your data profile has made a prediction.
Spotify can recommend new music based on your previous consumption habits in a calculation that's not just serving you more of what you like now, but what you could like.
"Data usage has previously been used to make decisions based on what you've bought in the past, but now brands are using artificial intelligence to figure out what you might buy in the future," Perera said.
"If I go into a cafe every day and order the same coffee, then of course it's easy predict I'll probably get the same coffee tomorrow. But now, they're using AI to predict what I might do in slightly different circumstances based on my profile."
Often times, consumers are given a reward in exchange for their data — free Wi-Fi at the airport, points on shopping, special discounts and the like.
For example, an American coffee chain offers free drinks in exchange for personal information completed on an app, Perera said.
A US tech company has produced a device that connects to a smartphone and allows people with heart conditions to conduct a free at-home electrocardiography test.
"Why is it free? The data you're giving them is much more valuable and powerful than you paying for the service. In the future, they can make predictions about heart attacks and strokes."
Perera said the useful service and big perk of it being free shouldn't dissuade people from asking questions.
Why do they want that kind of data? What might they do with it in the future?
Private health insurers in Australia have been lobbying the Federal Government to overturn a ban on them accessing data from the controversial My Health Record.
They argue it would be anonymous and used for research and statistical analysis, which may very well be the case — for now.
At a recent technology conference, ANZ revealed it was testing the use of artificial intelligence to assess a potential borrower's risk profile.
And the company IBM has started using a system dubbed Watson that predicts future performance based on data and computerised analysis.
"It might not be bad now — it's even quite good — but it could be problematic in the future," Perera said.
