Intelligent Automation – What Lies Ahead?

We live in an era where the fundamental rules by which businesses are being rewritten daily due to the power of software driven automation. But skeptics of its future ask if this automation will ever be catapulted beyond scraping screens for data, translate languages or run unattended pre-recorded process loops. These are pertinent questions. Advances in computational sciences specifically in Robotic Process Automation, AI, Machine Learning, Big Data Analytics as well as percolation of these into business operations have added firepower in bringing efficiencies and harvesting of the data emanating from these processes. This has brought about an underlying transformational change in the way most businesses are run. The goal of this contest entry is to explore the impact of advances in software automation i.e intelligent automation in the near future and how these are extending human capabilities in various spheres.

1. Introduction

Automation, as we stand today, has transcended it’s span as a process or program-based optimizer to become an enterprise-wide catalyst.

IEEE defines Software driven Automation as a “Pre-configured software instance that uses business rules and predefined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management.”. Today, we already find this definition seems archaic. Automation, in the last decade, evolved from this definition to become an optimizer of substantive business processes. And further transcended to become an enterprise-wide catalyst.

But the question that begs to be asked is – what are the new frontiers that Automation will conquer? It is said that the Financial Service industry presents a $1 trillion cost saving opportunity due to automation & virtual nursing assistants alone deployed to automatically respond to routine queries could save the American health care industry upto $20 billion.

So the obvious next question is what sort of automation is essential to conquer such new frontiers?

2. Avatars of Automation

To usher in a new – bold era of aggressive automation, we envisage the following aspects represented from an evolutionary angle will play a key role:

• Automation is currently limited to static rule-based systems to perform repetitive actions. Current Automation implementations fail in cases where there is varied format of forms, change in structure of data like sensor data, web forms, Documents for OCR.

• The triumvirate of Analytics, advanced RPA & AI have helped automation move into the realms of dynamic actions, capability to process unstructured patterns & learning driven automated decisioning. The machine learning for intent recognition from unstructured or semi structured inputs and AI to make decisions during uncertain situations based on multiple intents.

• The proposed framework would be flexible with a component of supervised participatory framework to learn from continuous feedback. Automation tools can be evolved to specific cases using supervised learning for newer intents encountered by maintainers of the tool.

• The framework would also be able to dynamically update itself to continue to be relevant, operate normally while underlying applications or systems its associated are experience changes. i.e. human intervention is not required or required in a limited way to update Automations if source systems are reconfigured.

• A further extension of the framework would be the leveraging of Blockchain (Digital Ledger technology), Augmented & Virtual Reality (Extended Reality), AI & Quantum Computing. This would further extend the capabilities of automation to render it to be truly extreme – i.e. Liquid – Adaptability to underlying changes, execution at organization scale, rapid portability across processes, pervasive & ubiquitous prevalence across the org., embedded trust & security, Judgement based automation, self-learning automation

3. Automation – An Industry Point of View

To bring this above framework to life, the following perspectives from couple of industries are presented:

3.1 Telecom

As part of Network Operations of the future there is a need for Intelligent Automation to do continuous tasks like 24×7 performance monitoring and optimization, predictive maintenance, prediction of network faults and congestion, automated resolution of trouble tickets, cognitive alarms management. This would help improve customer experience and service quality assurance levels of telecom operators.

Automation can be used for automatically taking remediation actions on detection of cybersecurity issues on the network preventing misuse of the telecom networks.

Increasing machine to machine interactions using thousands of IOT devices would be on the network and it is important to have a tool that can detect anomalies on real-time basis and prevent abnormal use of telecom networks

Intelligent Automation can be used to analyze the behavioral patterns of different IOT devices. This would help telecom companies to manage the new device types in more secure manner. An abnormal behavior of a device can trigger alarms and initiate remediation process for using the Automation.

Framework to render enhanced Automation to Telecom Networks

3.2 Quality Engineering

Currently use cases in product pricing for quotations to customers are not being tested using Automation as the calculation involves complex methods to check the desired output in various conditions. AI powered Automation would be able to automate such situation and judgement-based processes. It would help in creation of real time test data for various scenarios of pricing based on client type, category, order type and other parameters.

Based on current and historical pricing trends, Cognitive reasoning abilities of Automation can analyze and predict future trends on varied customer segments.

Futuristic Automation test scenarios and test data can be embedded within the functional application being built and hence being tested during development on each build; this is done to validate whether the application meets the acceptance criteria of the client in a more real time manner.

Currently lot of manual effort is being utilized for Risk Mitigation plans as part of Quality Engineering. Intelligent Automation can be used to understand the unexpected events and attempt solutions using optimized risk-based solutions.

More than 50% of errors reported in applications are due to User Trainings. Intelligent Automation would monitor human transactions for variance and prompt alerts for any abnormal activities which were not possible earlier. As well as simulate a broader range of user behavior during testing aided by machine learning.

Business Augmentation delivered by Automation

Here are a few scenarios of today’s automation success stories can be further enhanced by the framework proposed:

Today’s Automation success stories	How Automation can further amplify these stories in the future
National Health Services (NHS) in UK saved 275k in 2018 induced by RPA induced in its GP referral process	This same RPA augmented by AI powered optical character recognition, dynamic rule engine is estimated to save potentially $820 million per year
A broadband co. in Australia shaved an entire month off its NW Planning & Design process via the use of RPA & AI Computer vision aided by Machine Learning	Expanding the scope of Machine Learning from its current supervised reinforcement learning method to sparse dictionary learning, anomaly detection & stronger association rules could reduce the turnaround by 2 months
A Finnish NW equipment maker deployed 24 bots to eliminate 5% of its events monitoring workforce by partially automating the alarms from its 2G & 3G (from its NetAct devices)	Augmenting these bots with AI capability to correlate alarms, suppress false alarms & embed dynamic threshold capability can potentially eliminate its 80% of its events monitoring workforce

Conclusion

The emergence of the technologies discussed in this paper holds immense promise in enhancing an organization’s capability to automation & benefit businesses at large. While the value of this is undeniable, the use & extension of this technology requires careful nurturing. In summary, while we are at the cusp of making a quantum leap in intelligent automation, the key to ushering in a truly extreme automation era would be to integrate the various advanced computational concepts at scale.

*** This piece won the Accenture White Paper prize – June 2019***

References

Accenture Technology Vision 2019 and 2018

Horses for Sources

McKinsey Quarterly

The Financial Brand

Wired Magazine

Marketwatch.com

Forbes.com

Expert Opinions

Intelligent Automation – Communications Industry PoV – Anonymous 1, Sr. Manager, Accenture

Robotic Process Automation – Anonymous 2, Associate Director, Accenture