8 Thought Provoking Questions Raised By Self-Driving Cars… And What It Means for B2B

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Infer byline originally published on VentureBeat

The thought of self-driving cars on the road seems like a distant dream, yet they’re on the road today, and will be available to the general public within five years. Similarly, in the B2B world, artificial intelligence (AI) and predictive technologies represent a disruptive shift that’s forcing companies to re-imagine how they operate. We’re already seeing visible examples such as programmatic bidding in the advertising world. Most people believe that in five years, many parts of our business will be driven by AI.

With that in mind, here are eight questions everyone is asking about self-driving cars, each of which has an important parallel that helps frame AI’s impact on business and society at large.

TrustWill we be able to trust them?

Google’s self-driving cars have already driven 1,210,676 miles. These cars analyze tons of sensors and environmental signals, and carefully calculate movements to apply a conservative driving style. In fact, as of July this year, there had only been 14 accidents — all caused by human error, not by the software. Given the fact that around 33,000 people die in traffic accidents in the US every year, and much of blame falls to distracted drivers, there is a huge opportunity to make our roads safer.

In the B2B world, very few of our decisions are life or death, but there is still important revenue at stake. Machine learning can be used to develop models, but it’s still important for a data analyst to validate them and put the right safety checks in place. When the models are live, someone needs to monitor the impact of any changes and watch for drift in performance to ensure continued accuracy.


OwnWill I ever own one?

The thing that sucks about self-driving cars is that many of us may never have our own. The ability to run cars autonomously changes the economics of ownership. It will no longer make sense to own an expensive asset that we only use 5% of the day, when we could instead just request a car precisely when we need it. Furthermore, companies like Google may be willing to subsidize the cost of our transportation. If they know where we’re coming from and where we’re going, they can deliver a whole new level of targeted advertising.

Within B2B, this would be like rolling your own custom-built algorithms. The reality is that most companies will consume predictive-as-a-service instead. That’s because to operate highly accurate models, they’d need to be vicious about acquiring data, building connectors, and tuning performance. Just like having access to a fleet of self-driving cars, there are economies of scale and network effects that make subscribing to best-of-breed services appealing.

TrafficWill they reduce traffic?

Autonomous vehicles may well improve quality of life by eventually alleviating congestion. Once the world is full of intelligent self-driving cars, they can drive with significantly less distance between them on highways and in the cities, and they can automatically distribute traffic across more routes. In addition, thanks to the subscription economy, we’ll have higher vehicle utilization and cars will only park to recharge, which gives everyone more room to operate.

AI also means that everyone in the B2B world will have less noise to sift through. Marketers will have less ambiguity in their daily work, and customers will have less irrelevant clutter amongst the messages they receive from companies. This will result in less email, less communication, less interruption, and fewer mistakes. If we know the right message to put in front of the right person, at the right time, we can all operate far more efficiently.

DistanceWill they encourage people to commute longer distances?

If you have a car that drives itself, would you be willing to tolerate a much longer commute? Assuming I can sleep in the car, I might decide to live up in Lake Tahoe and commute down to San Francisco three nights a week. What would this do to our cities, suburbs, and environment? What are the implications for real-estate prices and energy consumption?

In the B2B world, AI could reduce dependency on hiring, which would mean that it’s easier to operate companies on a global scale or from a far off remote location. With AI as the “brains of your operations,” it’s easier to hire the best freelance economy talent wherever it is, and for however long you can get it. That’s because we’ll be able to easily plug humans into or out of our workflows at any time and hardly miss a beat.


EthicsWhat are the ethical impacts of AI?

The software that drives the car is programed to make decisions that aren’t always black and white. For example, if a fatal accident is imminent, are the passengers’ lives more valuable than those outside the car? And who has authority to override the car’s logic – the government, the vendor, or the owner?

When it comes to businesses, AI might decide who to promote and who to fire, what level of service each customer gets, or even the price they’re charged. That begs the question – who writes the rules for those algorithms, and how can we know whether we’re taking customer profiling too far?

LiabilityWho is liable?

In a world where cars are driven by software, vendors take on new levels of liability for ensuring that things won’t go wrong. If there is a fatal crash, is it the manufacturer’s fault, the vehicle’s owner (whether that be an individual car owner or a fleet manager), or the passenger who failed to override the car’s computer and take over? A recent episode of The Good Wife asked this question in a case where the “driver” was an employee of the self-driving car manufacturer, and the victim sued both the person who was testing the car at the time of the accident and the company itself.

B2B companies are used to starting with an empty database and a vendor that’s just responsible for making sure their software is accessible and doesn’t crash. But with predictive technologies, that’s no longer the case. AI vendors need to be aware of the outcomes each particular client is trying to predict, and where they want to steer their business. This puts them directly in the path of revenue, so if a quarter is off, we might ask “Is this the VP of Sales’ responsibility or the vendor’s?”

DisruptionWho is disrupted by this movement?

If self-driving cars are less susceptible to speeding and parking tickets, do local governments lose an important source of income? And how about the three million people who work in the transportation industry? How quickly will those jobs be displaced?

In B2B, we are quickly heading towards a world where inside sales is dominated by automated sequences and AI-driven messaging. Presumably that means that fewer people are needed to generate the same amount of pipeline. On the campaigns side, programmatic bidding and sophisticated attribution models may dramatically change the bets a company makes. While disruptive trends can be scary, it is important to get ahead of them and think about how we’ll shift our energy when AI takes the wheel.

LaggardsWill today’s established players be leaders or laggards?

While there is little doubt that players like Toyota, Ford, and Volkswagen will be in the mix, self-driving cars will still represent a disruptive shift for the auto industry. Because of the electrification of cars and the importance of software, players like Google, Apple, Tesla, and Uber may well lead the pack.

In the B2B space, Salesforce and Marketo will be in AI the mix, however they’re faced with competing priorities from their legacy businesses and they have a very different relationship with regards to data visibility. The new players that are emerging don’t have those constraints and can focus all their energy on acquiring data, building advanced models, and feeding applications with intelligent recommendations. Only time will tell who will win out, but I sure look forward to watching it all play out.

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Jamie Grenney

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VP of Marketing at Infer • formerly VP of Marketing at Salesforce • live in San Francisco • grew up in St. Louis and Colorado