This article is written by Forward Leading's guest writer Patrick Foster. The views and opinions expressed in this article are the author's own and do not reflect the view of Forward Leading Ltd..

Though the uprising of sentient robots predicted by books, shows and films for many years is perhaps not quite imminent, it’s inarguable that recent years have seen tremendous strides made in the field of artificial intelligence (AI). Exploring the boundless possibilities of cloud computing and machine learning, the world of automation is increasingly producing adaptable systems that are not only theoretically impressive but also of practical use.

Today, smart systems are already in widespread use in the form of home control hubs such as Amazon’s Alexa and smartphone voice assistants such as Apple’s Siri, two trailblazers in the shift from concept to execution — but what we’ve seen so far just scratches the surface of what can be achieved, and it won’t be long before AI technology finds greatly-expanded applications.

But what kind of route will it take to ubiquity? Here are 5 industries you can count on being majorly disrupted by AI tech in the coming years.

Customer Support

The incessant demand for customer support services coupled with the need for cost-effective operation created the call centre model so familiar to any large organisation. And beyond that, the generally-predictable nature of the work made it financially justifiable to outsource support to overseas regions where wages are lower.

While this certainly created jobs, they were never particularly desirable ones, and the resulting customer experiences were rife with frustration and puzzling inconsistency. But AI technology has the capability to essentially render the entire low-end customer support industry obsolete, which is why its use for this is wholly inevitable.

Using chatbot systems, any business can establish a support site to answer common queries, and a centralised AI program can monitor progression and escalate unusual issues to human staff when necessary. Since voice recognition is viable today, the technology can easily be extended to phone support lines as well, replacing the existing model seamlessly.

Healthcare

The process of differential diagnosis is incredibly laborious, which is why doctors gather in teams to throw theories around and see if any of them stick — but medical knowledge is learned by rote, and isn’t inherently creative. So many medical patterns have already been identified and stored that the information needed for a healthcare AI is ready to go. It need only be made accessible in the necessary way.

Of course, there are obstacles to be overcome first, such as the thorny issue of machine morality. People get intensely emotional about matters of health and like to feel that there is a person to blame if something goes wrong — someone fallible and thus a good target for anger. But machines don’t make mistakes due to tiredness or gut instinct, and their reasoning is obscured behind the scenes.

What we’re likely to see in the near future (as with many of these industry disruptions) is a careful process of relying more heavily on AI decisions but having them overseen by people to ensure that there is always someone accountable. We’re likely to see fully-automated diagnostic systems eventually (IBM has successfully tested its Watson system, for example), but only when society has overcome its current resistance to “trusting” AI.

Security

When I take my phone out of my pocket and open the case, the proximity sensor detects that the screen is uncovered and enables the display, then the system uses the camera to analyse my face, judges that the data matches that of the recorded profile, and automatically unlocks. If there’s an issue with the lighting, I can simply touch the fingerprint sensor to gain access.

The security industry has used everything from security guards to keycard systems, but all such security measures stand to be subsumed by AI security systems. A smart security system will be able to take numerous factors into account in deciding whether someone should be allowed access to a particular area, item, application, or file.

What’s more, a system of that kind will be far more capable of detecting tampering attempts. Equipped with myriad sensor batteries and given control over connected systems, it will be positioned to serve as the sole gatekeeper for a set area.

Ecommerce

Marketing is an area that has already been significantly disrupted by AI through programmatic advertising, but ecommerce in general has so much room for growth. Everything from pricing optimisation to UX design could feasibly be automated and thus made both more effective and more efficient.

As things are now, you can already build a tweakable template-driven store very rapidly, subsequently install an add-on to automate standard optimisation tasks, and even use a back-end chat system to request changes to be carried out automatically. The reason that we have yet to see a major disruption is that there’s a lack of awareness of the existing possibilities.

In time, we’re going to see large retailers trust their entire pricing models to automated systems that can read the market at all times and identify the price points that will generate the most revenue without driving customers away. At that point, price wars will become very interesting!

Transportation

Self-driving cars and taxis (as well as delivery drone fleets) are quite far into development now, and the results are very consistent. There are some large problems in the way, though:

So why do I see disruption occurring in spite of this? Because it can use the same approach as the healthcare system — instead of ceding control to the AI systems right away, transport companies can maintain human supervision until society has overcome its doubts and accepted that driverless vehicles are genuinely safer and more efficient.

There you have it — my prediction for 5 industries soon to be disrupted by AI tech. How do you expect AI systems to be used in the near future?

About the Author

Patrick Foster is a writer and ecommerce expert from Ecommerce Tips — an industry-leading ecommerce blog dedicated to sharing business and entrepreneurial insights from the sector. Check out the latest news on Twitter @myecommercetips.

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