The way we work is changing at a rapid pace portfolio work, ‘slash’ workers, fractionalised jobs and the influencer movement. While the concepts have been around for eternity, these are now widely accepted approaches in the last decade.
Who would have believed 10 years ago that 25 year olds would be paid to travel around the world and take photos of themselves? In 2009 who would have thought that you could efficiently be a private driver to hundreds of strangers, or hail a cab effortlessly in hundreds of cities.
Yet these are just the beginning stages of a technology revolution that is redefining the future of work.
The real revolution comes from machines, computers, phones that simulate human intelligence and start to do the lower end of our daily tasks - freeing us up for more challenging activities.
With the advent of vast stores of computing power provided through cloud systems, AI platforms are arising that enable computers to do truly human like tasks.
There are a range of tasks that are more suitable than others for this early automation. Those tasks that are high volume and repetitive, process driven and well-defined; these are logical places to first apply automation.
One must distinguish between simple automation and artificial intelligence in this context. A process that simply takes a predefined input, performs a task and delivers an output in a way that does not involve humans is automation. Steady advances in automation have been occurring since the beginning of the industrial era. This is not what we're talking about. Automation through artificial intelligence is an entirely different field. While the objectives are comparable: more work in less time, the methods and the capability are significantly different.
Artificial intelligence based approaches simulate human intelligence through statistical methods so that inputs can be varied and non-deterministic.
Let's look at a real example.
A pattern matching automation needs the exact phrase “I want to buy a car”. If a user says “I need to buy a car” , the simple process will fail. Artificial intelligence approach takes multiple training phrases.
“I want to buy a car”, “I need to buy a car”, “Sell me a car”, “I need a car”, “How do I buy a car”, “Get me some wheels”... etcetera, you get the picture…
From here it builds a statistical model and anything that the user asked for is compared with that model resulting in a percentage confidence that the user actually wants to buy a car. This is the way humans comprehend - we just aren’t explicitly aware of it!
In the area of conversational artificial intelligence (talking computers, chatbots, digital employees etc), machines are now able to automate vast quantities of customer service type enquiries. Ideal use cases are questions such as
“Where is my parcel?” - for a delivery company.
“What is my account balance” - which is the most common enquiry for utilities
“Where can I find your store”, “ do you have this item” : for any retail store
Examples of great success in this area include fashion retail chains Hallenstein Brothers and Glassons; operating throughout New Zealand and Australia. Via their digital employees Benny and Charlie, they handle many of the routine questions online shoppers have about the status of orders, returning items, exchanging etc. Also checking store hours, finding out sale information and much more. Implementation of the system has enabled the companies to grow at a high double-digit rate without adding staff in their customer service centre.
Another company that has had excellent results implementing conversational agents is Tower Insurance in New Zealand. Automating the windscreen claim process eliminated phone wait times for their most common claim type, dropping a process that was often 20 minutes long down to a process it took only 2 minutes. not only did this reduce the call demand on the service centre, it dramatically improves the customer experience with end-to-end automation off the process, while freeing up call centre staff to deal with more complex claims.
This is the crux of the future of work. Artificial intelligence is not here to take your job, Augmented Intelligence is here to take those parts of your job that you don't like, the parts that get boring, the parts that you cannot do 24/7. As AI steadily develops in capability, Humans are able to move into more interesting parts of the rolls, they're able to grow, they're able to develop.
Humans are very well adapted to dealing with ambiguity, complex situations and the use of empathy. Adapting our workforce so that wait times for customer service are dramatically reduced while providing human workers with more interesting more engaging work, also significantly improve the customer experience? This is a unique win-win-win situation, the employer, the employee and the customer all benefit.
In my experience of building conversational digital employees across Australasia, the workers whose roles are changing at the most interested in the most engaged in the process. I've never had someone say to me “Goodness, I wish we had more phone calls like this!”. I do routinely hear people explained how they look forward to providing a high quality of customer service and getting more challenge in their role.
Moving to the concept of augmentation brings a new lens turn the discussion. Many augmentations have crept into our lives and there are very few that we want to do without. In the car world we have ABS brakes, Power Steering and navigational aids. there are very few people now that would argue we don't want those in every single new car! artificial intelligence powered augmentation is the same, it's just a little closer to home because we can speak to it in natural language.