7 key RPA trends for 2020: from AI enabler to more strategic scaling

What are the key RPA trends for 2020?

1. Greater RPA vendor differentiation insights will emerge

Organisations now face a bewildering choice of over 150 robotic process automation (RPA)-branded products — and they all vary significantly in productivity claims, design quality and approach — so a greater understanding is urgently required to understand these important technical nuances. A clearer demarcation of RPA products will start emerging this year, where vendors fall into two broad categories: those that provide fast tactical benefits across desktop environments and those that deliver more strategic transformation across a large-scale enterprise.

As organisations attempt to scale up their automation projects, having this clarity will prove crucial as many newer RPA branded offerings possess design limitations. The painful reality can be code-heavy deployments requiring extensive debugging efforts and high change management overheads. This assertion is backed by Gartner’s recent prediction that; “Through 2021, 40% of enterprises will have RPA buyer’s remorse due to misaligned, siloed usage and inability to scale.”

Only when RPA delivers on the promise of being a transformative tool — at scale — will its real value be recognised. This means that organisations’ focus will increasingly gravitate towards RPA technology that’s underpinned by no-code, business-led design principles. This means no lengthy design, programming, build and deployment projects that prevent automation efforts from getting going.

RPA collaboration is key too, so those vendors offering a centralised platform, will enable both humans and increasingly intelligent ‘digital workers’ to deliver, share and expand automation initiatives across the enterprise — thereby accelerating gains.

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2. New RPA selection criteria

There will be a re-think of how organisations should choose RPA, with more informed assessments of its ability to successfully operate and scale in large, demanding, enterprise environments – where security, resilience and governance are more important than just implementation speed. This means that RPA vendor selection criteria will consider more meaningful, real-world insights. These include the overall level of coding required, from zero to high effort, proof of value ‘after’ the proof of concept, scalability potential, collaboration potential, robot capabilities, overall security and auditability capabilities.

These insights will become more important than ever to ensure that organisations see through the market hype to de-risk RPA selection and avoid longer-term issues.

3. Better measurements of RPA’s value

By examining the experiences and proven outcomes of mature RPA user organisations, we’ll see more meaningful methods of measuring the impact of RPA. These can include;

  • New service and product offerings — those activities that are being performed that were previously impossible for humans to perform, or to perform in a secure and compliant manner.
  • Productivity increases — how much time is being generated back to the business
  • How service quality and delivery is being improved — this could be due to faster, error-free, execution, quicker time to market, reduced risks associated with longer response times.
  • Accelerated, innovation and opportunity generation — how business people are using the additional capacity and technological capabilities to create new value-generating services and products.
  • Operational transformation — how actionable insights from automated process transaction data are being used to optimise, or reinvent business processes that enhance stakeholders’ experiences and create long-term value.
  • Happier, motivated, staff — how many people are being liberated to work on more intellectually challenging, fulfilling, value-generating work – and gleaning satisfaction in their new roles.

4. RPA becomes the AI enabler

Throughout 2020, RPA will further evolve towards ‘hyper automation’ — by being an increasingly favoured route for testing and deploying artificial intelligence, natural language processing, intelligent optical character recognition, communication analytics, process optimisation and machine learning deployments — into the enterprise.

We will see easier access for accessing and downloading a wider range of pre-built AI, cognitive and disruptive technologies — via ‘Digital Application Exchanges’. These exchanges will provide a one-stop shop for building out, scaling and adding skills to digital workers with direct access to innovations from partner ecosystems — helping to deliver more intelligent automated innovations.

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5. Clearer differentiation of digital workers and robots

There’ll also be a greater understanding of the vast differences between the differing robots on the market and their capabilities, which is important as they are the catalyst for enterprise transformation. There are those robots that rely on recorded process steps to complete tactical tasks but are unable to adjust to any unplanned changes, and there are more advanced ‘digital workers’ that operate more like humans.

These digital workers are different from other robots, as they’re a pre-built, smart, highly productive, self-organising, multi-tasking resource, that uniquely use and access the same IT systems and mechanisms as humans, without APIs — so are capable of automating processes over any past, present and future application.

Digital workers perform activities in the same way as humans — faster and more accurately, but will also increasingly work with and learn from humans and other robots too. This year, far more organisations will be employing the unique capabilities of human and digital workers that collaborate to perform evermore complex, end-to-end activities.

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6. RPA focus on more strategic use cases

More organisations will employ a more holistic, strategic approach to RPA by re-imagining processes and organisational structure and other technologies — and there will be a greater focus more on automating more end-to-end process and optimising workflow.

Smart enterprises will also explore a broader suite of process discovery, process mining, process automation and data ingestion to help them deliver the most business-aligned, complex activities that are expected to deliver the most value. These will include legal document validation and extraction, autonomous invoice processing, fraud detection, and similar business and process areas.

7. More strategic approach to scaling RPA

Over 2020, automations will increasingly become more carefully planned, modelled and designed to deliver sustained value, longevity and resilience — at scale. Key success factors for achieving success at scale will include integrating RPA into a broader digital transformation strategy, alignment with process governance, key stakeholder support and process optimisation.

Other success factors include partnering with IT and external partners, developing expertise in automation and process optimisation, clear governance and operating model, a centralised framework for IT architecture and infrastructure, and stakeholder communications and change management.


Peter Walker

European CTO, Blue Prism