Amplified Intelligence through Automation

Rapid progress in the field of automation has marked a significant turning point in society; as unlike previous technological revolutions, this one will impact workers across the spectrum, from entry-level to senior white-collar jobs.
Some see it as a driver of economic growth and boundless opportunity to improve living standards whereas others see existential threats ranging from widespread technological unemployment to defying robots vying to usurp the role of governing bodies. Whichever fence you sit on, the human workforce will change significantly as machines continue to assert their competitive advantage in executing routine activities and identifying patterns in data of all shapes and sizes. The future of work will be defined by partnerships between the human and the robot workforce. Robots paired with artificial intelligence will fuel the cognitive evolution and allow the new ‘virtualised’ workforce to perform complex actions propelling the intelligent automation phenomenon.

The amplified intelligence era

Technology is evolving rapidly and the opportunity exists to exploit disruptive technologies to increase the value and pace of change of information assets across service, process, and workforce transformation.1 Today, digital penetration and adoption of disruptive technologies are empowering workers to amplify their intelligence with cognitive tools, allowing them to focus on improving productivity, build new products, and create new services models, – no longer limited by human intelligence or capacity – that’s the cognitive advantage.2 Artificial intelligence (AI) is an area of computer science that emphasises the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include; speech recognition, learning, planning, and problem solving.

Many of the cognitive systems that have been inspired by the human brain are gaining popularity; think of Microsoft’s Cortana, IBM’s Watson and Tesla and Google’s self-driving car platforms. Forbes’ prediction of the impact of amplified intelligence suggests that cognitive systems will be able to mimic human intelligence and entirely replicate human interactions by the 2020s. This rapid growth is on the radar of executives and in Deloitte’s 2016 Global CIO Survey, 1,200 IT executives were asked to identify the emerging technologies in which they plan to invest significantly in the next two years with sixty-four percent saying they’d include cognitive technologies.3

New breed of technologies

Analytics capabilities have been enhancing human capabilities for years now, but cognitive capabilities can improve on those efforts by making them smarter and faster – and by learning along the way.4 The scope of accessible data is expanding even further with the use of dark analytics which will allow workers to illuminate new opportunities and extract insight hidden behind unstructured data and the deep web, beyond what is traditionally available through structured data sources.5

The following underpinning technologies are key examples of what is being used to help drive amplified intelligence:

Technology Description
Robotic Process Automation (RPA) The design, construction and operation of a computer software to accomplish the task that can substitute processes currently performed by a human.
Analytics Focusses on identifying opportunities for growth, diversification and efficiencies by creating large-scale organisation intelligence with pattern detection and the ability to analyse multiple data sources.
Intelligent Automation The ability for an application to automatically make choices based on the pre-programmed business rules with a capability to learn similar to humans without being explicitly programmed.
Computer Vision Empowering an application to interpret images, videos and handwritten material to perform analytics or record key information.
Machine Learning (ML) The technique which gives an underlying application an ability to learn similar to humans without being explicitly programmed.
Natural Language Processing (NLP) The related field of computer science that focuses on the use of computers to process written and spoken language for some practical, useful purpose.

Organisations are excited by the array of use cases of these converging technologies, which will help them to monitor events, aggregate sensory data from numerous sources, and through AI, robots can assist in determining which course of action to take to deliver the most desirable outcome. The possibilities of an augmented workforce will ultimately help drive product design, upend venerable business models and rewire the competition.

Harnessing intelligent automation

The new breed of cognitive technologies presents a unique opportunity to re-design knowledge-based work with a diverse range capabilities.6 These capabilities range from next-gen digitisation, helping to recognise handwriting and identifying images, which can be combined with RPA and powerful analytics to form intelligent automation solutions. These solutions can either directly assist people in the performance of non-routine tasks or even automate those tasks entirely. This is the concept of intelligent automation and it is about taking automation to the next level by pairing it with cognitive technologies.

Intelligent automation solutions can adapt to unpredictable changes using both traditional RPA and cognitive agents to advance both IT operations and business process outsourcing – being the catalyst to evolve automation into a holistic business disruptor. Intelligent automation can boost efficiency gains in routine tasks by helping users to better understand dark data to derive insights and make decisions with the help of natural language processing and machine learning. Traditional automation capabilities will extend to be able to interpret content and apply various business rules by learning from historical data, real-time human actions and defined processes. Wide-spread adoption in the future will see exciting new opportunities in higher-value applications, such as virtual infrastructure engineers proactively monitoring, triaging, and healing server issues, or virtual loan specialists that help customers fill out mortgage applications proactively.7

When applied alone, RPA has great potential for automating routine tasks, but those involving intuition, judgement, creativity, persuasion, or problem solving can only be addressed with the rapid developments in the field of AI due the decreasing costs of data storage and processing power.8 By harnessing intelligent automation platforms, virtual workers will be able handle increasingly complex workloads and they are likely to change the way we run our business processes in the future.

Bottom line

The machine age may be upon us – decoupling our awareness of the world from humans’ dependency on consciously observing and recording what is trending – but the real impact will come from combining data, robotics and cognitive capabilities to drive an amplified intelligence era which will create new jobs in fields we had not previously imagined. Not only will this amplify human intelligence but it will allow humans to work on truly innovative work; promoting possibility, creativity and productivity potential – helping us to build a prosperous world for future generations.

Footnotes

1 Garter 2017, How We Will Work in 2027
2 Deloitte University Press 2017, Beyond doing something cognitive
3 Deloitte University Press 2017, Tech Trends 2017: The kinetic enterprise
4 Deloitte State of Cognitive Survey, 2017
5 Deloitte University Press 2017, Tech Trends 2017: The kinetic enterprise
6 Deloitte University Press 2017, The rise of cognitive work (re) design: Applying cognitive tools to knowledge-based work
7 Digital Cultures: Age of the Intellect, by Dr. Ganesh Shermon
8 Forbes 2017, Artificial Intelligence Is Becoming A Major Disruptive Force In Banks’ Finance Departments

Visit the Analytics and Exponentials page to explore our latest thought leadership on this topic.


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