It is becoming increasingly popular to invest in money-bleeding technology giants in preparation of an inflection point in profits, but you have to wonder how long Uber will be able to hold on for.

Jamie Davies

May 31, 2019

4 Min Read
How long can Uber keep bleeding cash?

It is becoming increasingly popular to invest in money-bleeding technology giants in preparation of an inflection point in profits, but you have to wonder how long Uber will be able to hold on for.

Uber is a massive brand, an innovator and genuine disruptor to the status quo. There are few examples of a concept riding the wave of digital to create such a severe disturbance to the traditional world. And while Uber might be the biggest transportation brand in the digital era, it is haemorrhaging cash quarter-on-quarter. Other segments have demonstrated there will be an inflection point, the moment of glory horrendous losses are turned into monstrous profits, but that scenario might be a long-way off for Uber.

Looking at the quarterly results, revenues grew to $3.09 billion for the period, a 20% increase year-on-year, but net loss from operations was $1.03 billion. This is 116% more than it lost in the same period of 2018.

The losses are certainly starting to mount as well. In the final quarter of 2018, Uber reported a net loss of $865 million. In Q4, the loss was slightly worse at $939 million. In this period of 2018, the firm reported net loss of $478 million from operations.

In the digital economy, investors are seemingly happy to swallow negatives, Uber’s share price following the announcement of the financials is holding steady, though how long can the potential remain potential?

Encouraging these investors are companies like Amazon and Netflix. In both of these cases, the firm build a dominant position in the respective segments, scaled globally, attracted millions of customers and then turned attentions to profits. Uber might be able to do the same thing, it is following the same trends, though there are sceptical voices.

Some might suggest Uber will continue to be a loss-making company until autonomous vehicles emerge. The theory is sound, after all a company’s biggest overhead is staff. Uber will be able to free up billions once the technology is perfected, making it a very profitable company. However, it might be decades before autonomous vehicles are a realistic prospect on the streets.

The technology might not be far away, but there are so many other moving parts which need to be factored in. Firstly, will people trust handing control of vehicles to machines? Are regulations and legislation in place to facilitate the introduction of this technology? How long will it take parallel industries, such as insurance, to ready themselves? Is the infrastructure, both roads and mobile connectivity, ready for autonomous vehicles? Have safety concerns been appropriately addressed?

There are so many factors to consider, the progression of autonomous vehicles is much more than technology. It might be decades before self-driving cars hit the streets; can investors wait that long for the Uber inflection point?

There is also an interesting, and slightly nefarious, philosophical question to consider when it comes to programming the artificial intelligence component of the technology.

Let’s say a car is driving down the street, travelling at 20 mph when a child steps into the road. The child is within the braking distance of the car therefore it is physically impossible to stop the vehicle in time. There are three options for the AI to choose from:

  1. Continue driving forward and potentially kill the child

  2. Turn sharply left and potentially drive into pedestrians

  3. Turn sharply right and potentially drive into on-coming traffic

In each of these scenarios, there is the potential for a fatality. But here is the issue; the AI will have to make a ‘conscious’ choice, the outcome might mean death, and the software engineer will have to write the software deciding how the AI will react.

The reason why this is different to today’s driving condition is because a human reacts without thinking through the possible outcomes. We cannot assess the information fast enough and react with a logical action, but AI can.

This scenario is of course highly unlikely, sensors and cameras on street furniture might be able to warn the vehicle of the on-going hazard, but it is a possibility therefore the AI has to be programmed to decide. There is no right answer here, but the AI is flawed unless a decision on what course of action to take is made.

Some might suggest the option with the smallest percentage chance for a fatality should be taken, but the risk of a fatality is still there. Because the vehicle has made a decision, should someone be held accountable if someone dies as a result of the action? This is a very complicated area.

So, if autonomous vehicles are out of the question for years to come, Uber will have to think of other ways to make money.

Uber Eats is proving to be a profitable venture for the firm, while the management team has promised to cut back on promotions which might carve into profits. But will these side ventures compensate for the way the core business and R&D businesses are churning through cash. What is clear, Uber needs to stop bleeding cash in such a dramatic fashion or credibility with investors might start to run dry.

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