Automation today, and certainly in the future, can do many things equally if not better than humans, providing efficiency and cost savings. Ideally this also allows people to do more interesting work.
The opportunity is clear that – as artificial intelligence becomes yet more intelligent – systems will be able to scan data quickly, make better observations and create more meaningful links to make decisions; in other words, automated systems will be able to understand a complex problem across multiple companies and systems in seconds, then take remedial action before anyone notices.
However, we have to be mindful of the hype that accompanies this too: why would you want to use this capability? What benefits are you expecting? Do you use it for its own sake?
What makes sense to automate? For example, standard, repeatable processes like buying a parking ticket in a car park. The technology to do this has become much better so it can be automated relatively easily and is more acceptable to the user. For IT Service Management (ITSM) the obvious standard processes to automate would be password resetting and request management.
Conversely, the scope of responsibilities typically handled by a service desk and ITSM team are, by definition, much more complex involving a large amount of non-standard work. There might be thousands of potential scenarios where just to log an item could be hugely complicated.
The reality of automation is still relatively challenging and it’s easy to make requests that confuse most of the digital assistants available on the market, resulting in a substandard experience.
If we do still assume there will continue to be more automation of work in the near future, we also need to grasp a key point around readiness for automation – data quality. There’s no point automating a bad process, however it’s just as bad to automate a process that uses bad data.
Originally posted here.