RPA and AI - Non-techy explanation

Two technologies – great alone, better combined for synergy

“Taking away the repetitive robotic work from humans and employing bots to perform those tasks is Robotic Process Automation; and

Incorporating human-like intelligence into software for it to perform tasks normally performed by humans is Artificial Intelligence.”

When tasks in any process are automated, the job is taken over by a software code or a bot – it’s like replacing human with a bot capable of doing the same work perhaps more efficiently and 24 x 7 at a cost lower when compared to a full-time employee (FTE).

 RPA and AI either alone or together, are capable of bringing to fore an entire “virtual workforce” that will assist humans in their day-to-day jobs and bring massive efficiency and cost savings.

So, let’s look at these two technologies in a bit more detail

Robotic Process Automation (RPA)

Let’s do a negative definition of RPA first by considering what RPA ISN’T:

Contrary to belief (of some and not all), RPA is neither a robot that can robotically do things or walk/talk nor is it a physically existing machine of some kind that can process paper or recognize voice.

RPA is:

Attended and unattended RPA

There are two types of RPA bots: attended and unattended/autonomous:

• Any process that cannot be entirely automated would require an “Attended RPA bot” wherein some human intervention is required and the rest of the process is automated based on the process rules. Attended bots may trigger the human intervention via an alert or may commence the process on receipt of data after human intervention.
• Unassisted/autonomous RPA bots do not require any human intervention and work independently and are capable of being triggered by a schedule or with a data event in the software.

Artificial Intelligence (AI)

Once you know how it works, it's Artificial Intelligence no more!

Artificial Intelligence (AI) is an application that can simulate and replicate human intelligence in analysing a situation, data and environment.

AI is not a single technology but a combination of machine learning, natural language processing, hypothesis formulation, data analytics, evolving algorithm among other things which results in replacing humans from the analysis and insight generation process.

Components of AI can broadly be:

AI is classified in the following 3 stages or tiers:

In 1996, IBM’s computer “Deep Blue” beat Gary Kasparov, the chess world champion, in the 1st out of 6 games. Deep Blue is an example of ANI where it could only play chess and no other game or for that matter do anything else.

The robot Sonny in the movie iRobot (2004 movie – starring Will Smith) is an example of Artificial General Intelligence where Sonny could mimic human intelligence and behavior but that’s still science fiction.

It is said that the time for moving from Artificial General Intelligence to Artificial Super Intelligence would be exponentially lesser than the time for us to reach Artificial General Intelligence . Given the current state of technology currently, we are still far away from even achieving Artificial GENERAL Intelligence.

RPA is unintelligent AI

RPA is just process automation and progressive addition of intelligence to RPA upgrades the application or RPA bot propelling it towards becoming AI. Following graphic shows the 4 broad stages of progression from RPA to AI.

• RPA is process-driven – its function is to automate a process and take out the need for humans to perform such tasks.
• Automating complex process necessitates the inclusion of intelligence and machine learning patterns in the data, this takes the RPA to succeeding levels.
• AI is more data-driven where data collected from executing the process is used by bots to learn and recognize patterns for future decision making.
• Progression of RPA from simpler to more complex process is achieved by augmenting intelligence in varying degrees thus moving the automation from RPA towards AI.

Failing to plan = Planning to fail!

RPA and AI are already a reality and the domain is changing very rapidly. Not heeding to the headwinds is a recipe for failure.

Technologies have been implemented, more implementation plans have been crystalized and deadlines set – several companies and governments have advanced adoption of RPA and / or AI. Working in such an environment would not remain the same.

Employee responsibilities for carrying out their jobs and the environment to carry out the jobs already have and would continue to drastically change requiring more tech-friendly attitude. Additional tech capacity building would have to be undertaken to build competency. Professionals (management, finance, logistics, administration, etc.) will now have to anticipate the future not only in their respective domains but also the technology domain to remain relevant.