Five predictions for AI and process automation in 2020

The development of artificial intelligence (AI) and robotic process automation (RPA) rose rapidly during 2019.

In the coming year, this pace will climb even further.

Enticed by the potential for the technologies to streamline workflows and improve customer service, organisations will be undertaking deployments in ever-increasing numbers.

At the same time, the capabilities of the technologies will continue to grow at a breakneck pace. Where initially they were limited to assisting with very structured activities, they will increasingly be put to work in areas that until now have required human intervention.

During 2020, five key trends will shape the field of AI and RPA.

They are:

The rise of the RPA robot

Current projects involving the deployment of RPA robots have tended to focus on replicating existing tasks that have traditionally been completed by humans.

The robots have been able to learn a repetitive task and then complete it much more quickly.

While their AI capabilities allow them to read and understand certain documents, they have only been able to do this in a very rigid, rules-based way.

During 2020, the capabilities of RPA robots will increase.

They will become more adept at making decisions based on the documents they scan as well as data drawn from other sources.

By using rapidly developing machine learning and AI algorithms, the robots will be able to operate autonomously and add value to the organisation in which they have been deployed.

They will also be able to be used in more complex processes including those which are less repetitive and more open to interpretation.

One example is a local council that receives emails relating to a wide range of services into a single, centralised inbox.

An RPA robot can assess each email and determine how to respond or where within the organisation it should be forwarded.

Analytics projects will continue to fail

Many applications and IT tools offer far more capabilities and functionality than is ever put to use within an organisation.

This wasted capacity is termed a 'consumption gap'.

Experience shows that between 75% and 90% of analytics projects fail, and this is often due to the fact that the power of the technologies being deployed is far higher than the abilities of the users to take advantage of them.

To overcome this, businesses will need to invest in the data literacy of their workforce.

During 2020, they will also need to think a lot harder when designing and deploying new systems and be sure they match the needs and capabilities of the people who will be using them.

Routine work will continue to disappear

The number of RPA robots and AI-powered chatbots will continue to grow within organisations throughout 2020.

As a result, more than 50% of what is currently considered to be routine and repetitive work will disappear.
This trend comes despite the fact that many people's experiences with chatbots have so far been less than optimal.

The continuing development of the AI that powers these bots means their capabilities will increase, allowing them to more easily provide a satisfying experience for users.

People will also learn from previous projects and gain a better understanding of exactly how they should be put to use. 

The rising importance of data governance

More organisations are going to recognise the importance of their data and the impact that can be felt if that data is lost or mismanaged.

Therefore, responsibility for data governance will be taken away from the analytics team and placed in the hands of senior executives.

Master and metadata management will also become much larger concerns as more data is used by AI tools and RPA robots.

Any failures to effectively protect this data at all times is likely to have significant implications for an organisation as a whole.

Data monetisation becomes a valuable additional revenue stream

During 2020, more organisations will come to realise the value of the data they are holding.  Many will also identify ways in which that data can be monetised.

This could be achieved by making it available in various forms to customers, suppliers and even the wider market.

One area that will require more thought is exactly how the data can be presented and provided in effective ways and the mechanisms that will be needed to monetise this process.

An example is a retailer who has detailed information on customer purchasing habits.

This could be made available to upstream distributors and manufacturers.

They, in turn, could use that data to guide forward planning and future product ranges.

Amid these trends, adoption of AI and RPA robots will increase rapidly throughout 2020.

As organisations come to understand the benefits that can be achieved, solid business cases will be mounted for investment.

Just as computing dramatically altered workplaces in the 1980s, so too these technologies will usher in a new period of dramatic change in 2020 and beyond.