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The state of intelligent automation

The state of intelligent automation

Intelligent automation (IA) needs to be business led, integrated and cloud-enabled for the best results, according to global findings in a KPMG and HFS Research report.

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Shane O'Sullivan

Partner, Artificial Intelligence & Cognitive

KPMG Australia

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As organisations embark on intelligent automation (IA), KPMG and HFS Research have found that the vast majority are struggling to secure value from their IA activities. In particular:

  • Most are actively pursuing IA initiatives but are hindered by a lack of coordination, integration and prioritisation
  • Less than 20 percent of Australian organisations claim to have an ‘at scale’ IA capability
  • Even with Robotic Process Automation (RPA) – arguably the most mature of the IA technologies – organisations are struggling to achieve scale
  • Skills shortages – particularly in machine learning and artificial intelligence capabilities – are inhibiting IA growth
  • While everyone recognises IA will change the way people work, few have determined how best to address the impacts.

Our report, Easing the pressure points: The state of intelligent automation, dives into these findings. Based on a survey of nearly 600 business leaders across 13 countries, including Australia, it paints a clear picture of current IA implementation status – from the aspirations and strategies at play, through to the barriers and challenges being faced along the road to enterprise value.

Six key themes in the report include:

1. Business, not IT, led

Forty-eight percent of organisations describe their IA initiatives as IT led. This means that IA can stall as business leaders are not fully engaged with how their operations should be optimised for automation. IA transformation should instead be business led, with a clear understanding of processes and data management for machine-based decision making.

2. End-to-end approach

RPA’s ease of deployment has made it easy to automate several isolated steps of a process. However, IA requires end-to-end thinking, as data needs to be captured cleanly and passed on through the process.

3. Capture and control of intellectual property

As automation increases, businesses have struggled with effectively capturing their Intellectual Property (IP). IA initiatives need to capture organisational business rules, be able to easily refer to them, and to modify them when required.

4. Integrated solutions

Many organisations have picked one platform to drive their automation. This limits the ability for IA, for example when dealing with voice or unstructured data, making judgement-based decisions, or automating activities like digital marketing. Instead, IA needs to be thought of as an architecture around core systems covering front, middle and back-office requirements.

5. Obsolescence architecture

IA technologies are evolving rapidly. Architecture needs to be in place to allow for the easy substitution of new automation technologies.

6. Cloud enabled

As automation increases in intelligence, the demands for computing power increase as well. The IA architecture should be cloud enabled to cater for the increasing levels of data required for automated decisions.

Find out more about the status and future of IA in: Easing the pressure points: The state of intelligent automation.

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