Over the past few years, it has been hard to ignore stories of the coming artificial intelligence (AI) or robotics age.
Warnings from experts around the potential harm it could cause are coupled with companies reeling at the prospect of making even greater savings. Unlike the previous revolutions that have come before, this one has highly paid professionals such as doctors, lawyers and accountants worried. Their concerns are around the fear of being replaced by a super brain or some animated hologram previously only dreamt up in science fiction shows.
Though some version of the above scenario is likely, you have to put AI in the same context as the paperless office. Over 20 years ago everyone was talking about a world in which paper tickets and a whole host of other documents would be digital. It is fair to say that is a lot less paper is used compared to 20 years ago, but it is more paperlite than paperless.
The concept of employees that you only have to pay for their upkeep, which works twenty-four hours a day, seven days a week and takes little to no breaks will naturally excite organisations. This concept is driving leaders into either commencing or looking to start their version of a Robotics programme. However, the significant savings can often blindside them into investing in expensive software and hardware, without fully quantifying how this new technology can be fully adopted within their organisation.
In 20 years+ of working I have seen countless businesses put all their eggs in one basket with one or two big strategic programmes and then only two years in seeing them either reducing the scope or having to write a blank cheque to cover the ever-increasing costs associated with the delivery.
When it comes to Robotics keep it simple; Robotics should be business, not technology led and your analysts should play a fundamental and strategic role in the programme, carried out through a phased implementation. Like any revolution, it starts off small and builds momentum.
#1 – Basic Automation
The first stage is a basic level of automation, think of this type of automation as keystroke or simple, repeatable processes whereby the information is readily available and in the right format. There are a lot of applications on the market in which the user can record a series of actions or steps that they undertake for a particular process. Once recorded, you can assign a trigger or prompt that when it occurs, the computer program will run the sequence of steps. A simple example of this is shortcuts on your keyboard, in most applications pressing the keys Ctrl and the letter ‘P’, triggers the printing of a document. You could use basic automation, for workflows driven from your website or for example, prompted processes, such as has the report been received; yes or no. Though it may not be as advanced as the other phases, you will realise savings and prepare your organisation for what is to come next.
#2 Advanced or Enhanced Automation
The second stage is the Advanced or Enhanced Automation, taking what we in did in the first step, but doing so much more. In advanced or enhanced automation we might have workflows that trigger actions based on data contained within emails, paper documents or user-prompted actions. Typically, most robotics applications do not have Optical or Intelligent Character Recognition (O/ICR) capabilities as standard, which means that your robots will not be able to read. By adding this functionality, your robots will be able to read emails, attachments or even scanned paper documents whether it is through printed text (OCR) or handwritten text (ICR). This phase of the AI evolution will open up more processes and savings, whether by performing tasks triggered by customer communications or by freeing up resource-intensive processes and by now you will likely begin to see significant savings across your organisation.
#3 Artificial Intelligence
The last and final stage is the full artificial intelligence part of the evolution. Developments within this area are frequently changing. Most organisations would start by building decision trees, algorithms and even monitoring production or live transactions, enabling them to begin a reactive, cognitive model within their organisation. Let’s use an example of a complaint’s process; a customer sends in a complaint in via email. The email states that the client’s flight was delayed for 8 hours and no one offered them any form of subsistence or compensation. The airline has a policy in which they will provide compensation of up to 10 dollars per hour where there is a delay of 5 hours or more. In the pre-Robotics process, the complaint would likely be passed internally within the organisation, eventually to a handler that will assess the claim and finally settle it by paying the customer 30 dollars. In an AI world, this could be handled much quicker and simpler. The customer would be able to fill out all of the necessary information via an online form. Once submitted this would trigger a series of workflows and based on the information provided, would derive a decision. The decisions would not only be based on the information and evidence submitted but also based on similar past cases. The robot would be able to calculate the most probable outcome and based on the results, would automatically calculate the compensation and pay the 30 dollars directly into the customer’s account, without a single human being involved at any stage of the process.
Though this was a straightforward example, by feeding your AI engine with past decisions and actions, you begin to help it create a probability model. Each time a new case comes in, the AI would be able to assess the nature of the communication and would then by following a set process which would, in turn, enable the robot to provide an outcome based on the most probable and best solution. AI is expanding, and already there are sophisticated cognitive developments in areas such as speech and visual recognition, making the application and opportunities exciting for the future.
It is hard to ignore the warnings, and I do believe there is some merit in the concern around using AI in the wrong context, however, from an evolution perspective, AI is exciting. Imagine the world in which doctors are virtual, being able to examine you via an advanced smartphone, being portable and available wherever you are in the world. It is not something to fear, as humans would still likely play a significant role, building and maintaining the robotics and for processes that require specialist knowledge or do not follow the norm. A world of virtual doctors would inevitably see health care costs fall, but so would unnecessary deaths, especially when health care is not readily available due to expense, being in remote parts of the world or just because help comes too late.
Analysts should be the ones building the workflows, defining the parameters and tweaking the robots to ensure optimum results. Ultimately though, for it to be truly effective, it cannot be seen to be a fad or a must-have, but instead, a strategic platform deeply ingrained within any organisation.