Seven RPA predictions for 2020

A year ago, I made six predictions for RPA and AI in 2019. Five out of six came true (and, arguably, the sixth prediction was partially true, too).

This year, I'm going one better - so, here are my seven predictions for 2020 and in my usual style, they are in pictures...

This will probably not come as a surprise to many people but I believe that it will be good news for the RPA market.

As organisations face the realities of working in an economic downturn, I predict they’ll adapt their business models with automation rather than lay off employees. Organisations understand that the investment they’ve made in their people will pay off if they can afford to retain them. With automation available, they can scale up robots rather than scale down human employees. 

RPA will become the repository for automation in the same way that YouTube is a repository for video content. This idea comes from David Hunter of Ericsson. The centrality of RPA will run parallel with the development of automation code that is more useful and reusable, enabling it to spread even further and faster than it has previously. The spread of this centralisation and functionality will enable organisations to reuse code across industries and geographies.

At the moment, organisations treat robots like they're snowflakes. That’s what my colleague Chet Chambers has found. From this perspective, each automated process is a unique solution tied to a unique problem. 

In 2020, organisations will learn how to better standardise those robots and apply them across use cases and departments, and eventually across companies and industries. Once you combine and standardise robots into reusable and repeatable elements, the individual snowflakes become snowballs. 

Snowballs need the material of snowflakes but have a momentum that makes them more powerful. These snowball robots resemble one another and are just as predictable across all industries and geographies. The process of turning these snowflakes into snowballs is something we’re increasingly going to see, and it’s going to result in more predictable deployments and easier scaling.

According to Ian Barkin of Symphony Ventures, organisations inherit complexity as they grow. He compares analysing these organisations to archeology, digging through layers of process sediment that built up over time in the same way that sedimentary rock is built up over millennia.

For most of business history, human employees have been stuck having to connect and integrate increasingly outdated technology systems via repetitive, manual work. In 2020, students entering the workforce will be familiar with better options and will force lagging businesses to transform their processes. 

Their familiarity will be helped by programmes such as the UiPath Academic Alliance.

The powers and abilities of machine intelligence are only growing, which isn't necessarily true of humans (and don't even get me started on politicians). 

Tasks that we once thought uniquely human are quickly becoming doable by software. The growth of AI will remain exponential, similar to Moore’s law, and there will be plenty of surprises in store. 

Every innovation we’re seeing in AI and computing is happening on top of innovations in quantum computing. We’re regularly increasing the number of qubits, and the potential use cases for this power are vast. Limitations that we’ve previously accepted as immutable won’t last. 

Even some of the most fundamental assumptions about AI are increasingly under question. Julie Shah, an associate professor at MIT, is pushing AI into possibilities via theories of linear temporal logic.

I predict that we will see revolutionary rather than evolutionary developments in 2020.

The impact of automation is proving to be societal in scope.

In 2020, extra-governmental organisations like the United Nations and the World Economic Forum will discuss RPA in the context of jobs, wages, and global economics. Automation is already having a massive impact on economies internal and external to individual countries.

Individual countries will also become increasingly interested in what effect automation will have on their societies. Prioritising RPA in these socio-political contexts and policy discussions will only become more important if my first prediction proves correct, and robots become key players in the coming economic downturn.

As larger, more established organisations move into the RPA market, they’re going to acquire and merge with upcoming RPA vendors. 

The leaders identified by the Gartner Magic Quadrant, Forrester Wave, and Everest PEAK Matrix reports likely won’t face acquisitions because their valuations are too high. Enterprise entrants to the RPA market will instead acquire and merge with smaller organizations to compete with these leaders.

 Global service integrator companies and other technology companies are already buying up automation-led services companies. For instance:

• Accenture acquired Genfour in 2017.
• Sykes acquired Symphony in 2019.
• Blue Prism acquired Thoughtonomy in 2019.

In 2020, the consolidation of these challenger companies across services and technology businesses will continue.

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Agree, don't agree, have more? Comment below or email me ([email protected]). Thanks all.