Gartner predicts that by 2018, 45% of the fastest-growing companies will have fewer employees than instances of smart machines.
This shift toward automation is not new, but current advances in artificial intelligence, robotics and automation, supported by substantial capital investments, are accelerating this trend and will continue to improve organisational performance in multiple ways. Gartner predicts that by 2018, 45% of the fastest-growing companies will have fewer employees than instances of smart machines. As technology accelerates and the number of processes and things infused with software is growing rapidly, so are the possibilities for what can be automated. The speed of change is immensely fast and we’ve so far only seen hints of what’s to come. Exponential improvements in voice recognition, sensors, natural language processing, machine learning and computing power are giving rise to a new generation of transformative systems that will change the rules for how business is being done by solving an expanding range of business problems—from routine tasks to groundbreaking achievements.
A new era of growth and innovation fuelled by intelligent automation
An increasing number of artificial intelligence applications are being developed that make machines more sophisticated in how they learn and make decisions—expanding the limits of what a robot is and can do. By gathering and synthesizing vast volumes of data from multiple sources, these intelligent machines can automate complete processes or workflows, learning and adapting along the way. This rapid development of intelligent automation is bringing about a new era of productivity and innovation on an astounding scale, setting new standards for quality, efficiency, speed and functionality.
The future winners of the digitized economy will embrace intelligent robots as a springboard for new growth and innovation, rethinking what they do across every area of the enterprise.
Before long, machines powered by artificial intelligence will become a core capability that pervades every dimension of the business, enabling a more productive relationship between people and machines. The future winners of the digitized economy will embrace intelligent robots as a springboard for new growth and innovation, rethinking what they do across every area of the enterprise. Frontrunners are already using it to increase agility, simplify systems and operations, speed up time to market and drive continuous experimentation with new products, services and business models—reinventing their organisation and industry in the process.
However, incorporating artificial intelligence into the business won’t be an easy task. It requires organisations to rethink how many things are being done and entails a major shift in how IT systems are built. Organisations will need to redefine their business and IT architectures, incorporating AI as a new foundational layer. Organisations that fail in this endeavour will see themselves be surpassed by more forward thinking and agile competitors.
Thinking machines will transform the workforce across every industry
Knowledge workers are being complemented by technology in increasingly high-value ways. The next wave of cognitive technologies will give rise to a virtual workforce that can replicate a considerable number of human actions and automate nearly any software-based process— enabling end-to-end automation of a large part of our daily lives, which means that many jobs will be redefined. Gartner suggests that one in three jobs will be converted to software, robots and smart machines by 2025. We will see companies with workforces that comprise a mix of human and virtual employees working in concert on tasks for which they are individually perfectly suited. This evolution will have implications stretching across all areas and take many different forms.
- Cobots: A new generation of intelligent, collaborative robots are capable of learning from their human coworkers and performing a widening range of sophisticated tasks. By connecting cobots with machine learning, we will in a near future also see robots that can train themselves. Examples include Amazon Robotics’ mobile-robotic fulfilment system for automating retail distribution centres, Universal Robots’ machines that can perform a variety of jobs from sorting eggs to blood samples and Boston Dynamics’ autonomous, quadruped robots capable of climbing, running and following commands.
- Cognitive agents: New artificial intelligence platforms like IPSoft’s cognitive knowledge worker Amelia makes it possible to automate and augment business processes across a broad range of functions. Amelia is a virtual service-desk employee who speaks more than 20 languages, learns on the job, replies to e-mail, answers phone calls and holds conversations. She learns from reading manuals and situational context as well as by observing and working with human colleagues. In a help desk situation Amelia can understand what a caller is looking for, ask questions to clarify the issue, find and access the required information and determine which steps to follow in order to solve the problem.
- Robo advisors: The past few years have seen the rise of robo advisors such as Wealthfront and Betterment—online wealth management services that provide automated, algorithm-based portfolio management advice without the use of human financial planners.
- Robotic-Process Automation: RPA systems like UiPath and Blue Prism are revolutionising the way organisations think about and operate business processes, enabling users to simplify, accelerate and improve the accuracy of manual and repetitive tasks. Software robots drive the user interface of third party applications like humans. Typical activities include data entry, testing, content migration and legacy application integration.
- Autonomous vehicles: The capabilities of autonomous vehicles, such as Google’s self-driving cars, using sensors and artificial intelligence to automate transportation, are progressing rapidly with applications in many sectors. We are now seeing fully functional autonomous vehicles being tested on our roads and in a decade they may start replacing manual driving all together.
- Household appliances: Nest’s thermostat and iRobot’s robotic vacuum cleaner are examples of how we’re seeing an increased use of automation and robotics in the home. Common household tasks such as cleaning or folding laundry are extremely difficult for machines to perform and require exceptionally complex software algorithms. But recent advances driven by A.I. are now enabling robots to learn certain tasks by themselves and teach each other what they have learnt.
- Autonomous Drones: Increasingly smart and autonomous drones are being tested in many industries. Computer scientists and artificial intelligence experts at MIT have created a lightweight, quick thinking, autonomous drone that can dodge and dive its way around obstacles while flying at 30mph. The possibilities for use are almost endless. Drones are ideal for monitoring remote or dangerous locations, such as surveilling crops or landscape fires.
A new era in software development
Over the past years, born digital companies have transformed the way software is being developed and deployed, as well as how technology infrastructure is being built and maintained. Companies like Netflix, Spotify and Amazon have trailblazed the integration of software development functions with their IT operations, doing continuous delivery of smaller improvements, where teams quickly design, integrate, test, deliver and monitor software changes.
Automation is key to support this approach and to drive agility and innovation into the application development lifecycle. Software robots eliminate manual quality assurance and execution steps, verifying that every business process work across every application, every day—in the same way that end users would use them. Development teams don’t have to wait around for other teams to catch up but can independently and rapidly check in, test and deploy code through the click of one button, while maintaining consistent quality and coverage. This means they can achieve more in less time and run projects faster and more predictably.
Development teams don’t have to wait around for other teams to catch up but can independently and rapidly check in, test and deploy code through the click of one button.
Sophisticated automated testing of new code is performed at every stage of the development process to ensure that small problems like bugs and glitches are caught quickly before they become large. In addition, with the help of advanced analytics and other tools, code is preemptively scanned for exceptions and developers alerted about pieces of code likely to generate errors.
New products are normally released as canary builds, staged so that updates initially are released to only a small percentage of all users. If the software encounters issues, the automated system serve as a safety net and can quickly roll back deployment before the whole user base is affected. If the software works as expected, it is automatically rolled out sequentially to larger subsets of users.
What about organisations with legacy?
For organisations that weren’t born in the digital age and still have a mix of modern and legacy technologies, building and scaling automated IT systems can be a challenge. The best way to proceed is to focus on the highest-value automation opportunities. Customer-facing elements are typically the highest priority, and they usually also undergo the greatest level of innovation and change. To support this, developers need to incorporate automated testing into their IT architectures, such as verifying end-to-end customer journeys as well as performance and security tests. Each merge of new code into the main source code should trigger these tests and the deployment of the latest code to low-risk test environments.
In an era of continuous disruption, organisations don’t have the luxury to hesitate and defer change efforts. Leadership must acknowledge the necessity for change and speedily drive transformation in the organisation. When doing this, it’s key that leaders frame change positively as an opportunity and not as a threat of employees losing their jobs, by depicting how new tools can benefit both employees and the organisation through cost savings, reduced error rates, improved quality and the elimination of routine, mundane tasks in favour of more stimulating ones. Moreover, they have to be firm about what the organisation must stop doing and what they must start doing instead.
Where to start?
In order to take full advantage of the possibilities of intelligent robots, companies need to consider a number of issues pertaining to strategy, technology, information, human resources and risk including:
- How can we use intelligent automation to improve operations, innovate and grow?
- What solutions should we choose and how should they be integrated?
- How do we acquire and prepare information assets for machine learning applications?
- What talent strategies and staffing and training plans will we need as a result of the changing skill sets, job definitions and organisation design that intelligent automation give rise to?
- How do we assess and mitigate risks in the form of cyber threats, privacy breaches, product liability or discrimination?