Automation: In Focus

What could work look like in 2030? How will automation and robotics change how we all work? And how will businesses organise their workforces?

Predicting the future has always been a notoriously risky business, predicting the future of work in an age of increasing pace of technological disruption, amid a global pandemic, makes that task even more difficult.

Nevertheless, we can be certain of a few trends that tend to emerge alongside previous revolutions (or evolutions). Firstly, new business models emerge and disrupt old monopolies and obsolete business models. Secondly, new skill sets and new types of jobs are created and displace many existing roles that people are familiar with. I believe that with the advances in automation and robotics between now and 2030, we will see a similar situation.

I believe that we are currently in a phase of algorithmic automation where simple tasks, aka “the low hanging fruits”, are automated. Examples of this can be seen in the use of robots to automate repetitive tasks in a factory floor or in the use of robotic process automation (RPA) to replace humans for simple computational tasks in sectors such as banking and financial industries.

The next phase is probably three to five years away, so 2025 could well involve increased levels of human and robotic interaction, where we will begin to see semi-autonomous decision making becoming mainstream. In this scenario, more complex tasks will become automated but will remain likely to rely on dynamic interactions with humans who still have the final say on the potential decisions proposed by the automated systems.

In the next phase, somewhere in the next ten or so years, we are likely to see the automation of physical labour in complex tasks that require manual dexterity and dynamic problem solving, such as in autonomous vehicles used in transport and autonomous robots used in factories. This phase will see the ubiquitous adoption of cognitive technology to address the limitation in human attention, as well as the need for independent decision-makers with unbiased decision and trust protocols.

In this phase, humans are going to work seamlessly with robots, algorithms and systems to enhance and complement each other’s cognitive systems. It will certainly impact skills required in both current and new jobs, which will undergo an enormous transformation affecting most industries and this will directly affect the nature of our work, as well as how and where we work.

As algorithms take over tasks (financial services, for instance), what does the automation roadmap look like for many businesses?

As businesses absorb and implement the latest technological breakthroughs in automation and robotics, the labour market is undergoing a major transformation. This transformation must be managed wisely as, in my view, it will be the bottleneck to technology adoption and improved productivity across many industries.

Aligning the automation roadmap with the skills and workforce road map can lead to rapid technology adoption with increased productivity, as well as a new age of good jobs and improved quality of life for all. However, neglecting this human aspect will pose the risk of widening skills gaps, greater inequality and broader polarization across industries and societies.

With the aim of supporting businesses in the manufacturing industry our team at the Institute for Advanced Manufacturing and Engineering (AME), which is part of the Institute for Future Transport and Cities (FTC) at Coventry University, created a new multidisciplinary research group called People-Centred Productivity (PCP). The group is focused on exploring the ways in which business can positively impact their productivity by taking a people-centred approach to implementing technology.

Our team includes a range of academics and industry experts from across disciplines such as business and law, engineering, computing science and psychology, amongst others. Our work is creating a framework to support manufacturing businesses to adopt new technology to link the business strategy and business models to their technology and people roadmaps, ensuring that the right level of investment, development, sustainability and returns are achieved in both the short and long terms.

We recognise that many businesses forget that there is no historical evidence of technology being detrimental to aggregate employment levels. And yet in each phase of technological change, people fear for their jobs. Questions, such as will automation destroy more jobs than it creates, coupled with fears of not only job replacement but, also the possibility of a super-intelligent AI outsmarting humans, are evident in the context of automation and robots in most Western countries.

The automation roadmaps should address the people element and see it as the critical path to technological adoption. By doing so, businesses will be able to be proactive in addressing the changes to skills and workforce requirements. Furthermore, businesses will have a chance to present automation and robotics as an opportunity to improve the quality of work, the remuneration, job types and access to the job market for people who have been limited by physical disability or by declining physical strength in old age.

Will some sectors be more affected by automation and robotics than others?

As we progress through the phases of automation discussed in Question 1, I believe that different industry sectors will be impacted by and see varying effects over time. For example, in the short-term, the biggest impact is likely to be seen across industries such as banking and financial services, where algorithms can lead to faster and more efficient analysis and assessments.

In the medium to longer-term, let’s say between 2025 and 2030, the transport industry is likely to be transformed beyond recognition by the development of autonomous vehicles (cars, trucks, ships, UAVs, aeroplanes).

In manufacturing, it is expected that automation and robotics will have a positive impact on productivity and flexibility to deal with customer demand for greater product variety. Robots, in particular cobots, are key to improving productivity in this challenging environment. Also, advances in cobots and assistive technologies, such as exoskeletons, expand the scope of tasks robots can perform in support of worker productivity. These trends are predicted to increase the uptake of robots among manufacturers, including SMEs.

Finally, whilst no industry will be immune to advances in automation and robotics, certain sectors are expected to see a lesser degree of change. For example, industries such as the health and the education sectors may be relatively less affected due to the importance and reliance on social skills and human contact.

Robots and automation are likely to play an important role in working alongside human doctors and nurses but are unlikely they will be able to replace these professionals by 2030.

What changes will CIOs and CTOs see to their jobs and their responsibilities as automation expands?

As businesses evolve with the technological advances between now and 2030, the role of the Chief Information Officer (CIO) and Chief Technical Officer (CTO) is likely to change in scope and importance in most businesses. I believe they will become the most important business strategists and operational leaders, second only to the CEO. This change in the roles will present a challenge for the entire executive committee and transform the C-Suite relationships.

It is likely that by 2030 all executives in an organisation will be focusing on digital business. For example, the legal team will be responsible to oversee ethical issues triggered by the use of AI or data protection issues and HR will need to monitor governmental regulations for the employment of humans, along with robots and AI decision-making algorithms.

There will be a variety of technological, legal and social constraints that the future CIOs and CTOs will have to be able to master and overcome, in order to be successful and benefit from the advances in technology benefits. The following paragraphs will discuss three examples of these.

The ability to rapidly and accurately assess the feasibility and constraints before adopting new technologies. With the continuous increase in the pace of technological change which follows Moore’s law, assessing technologies that need to be integrated and adapted into complex and interdependent solutions before it can be deployed in a real-world business situation will be one of the key tasks of the CIO and CTO of the future.

The ability to understand, communicate and advise on multidisciplinary topics, such as the overlapping areas of technology and the law. For example. data is fundamental to the use of Artificial Intelligence-based autonomous systems and, with this in mind, businesses wishing to adopt AI and related technologies will, therefore, need to deal with a range of legal issues such as protection of individual data rights and privacy, incomplete data collection leading to learning mishaps and misuse of data-sharing platforms.

Machine optimisation rules also need to be regulated to prevent biases in the insights that are generated using data. For instance, in the case of driverless cars, the development of the algorithms and safety systems will need to be aligned to complex regulations surrounding liabilities in the case of accidents which could be the result of a fault emanating from the human vehicle owner/driver, the car manufacturer, the provider of software, or some other supplier which will ultimately share responsibility for any accidents.

The ability to work with other business functions to guide the company in its efforts to optimise humans and limit social constraints related to technology adoption. For example, in a given society or industry, individuals may not be willing to have robots or automation replacing humans, especially for safety-critical fields such as health provision or flying passenger aeroplanes. Societal concerns could also be raised in regards to the potential rise in inequality as a result of automation, which in turn may affect the business brand and value. Acceptance of robots, automation and AI by society, in general, will eventually occur, but only when people are convinced of its advantages over humans and this can be a long process.

For tech companies, is automation the conclusion of their digitisation?

Digitalisation or digital transformation in its long-form is not about just automation of an existing process by utilising new technologies. Furthermore, it is also not about replacing paper or people with new digital tools, it is instead about doing things differently, creating new markets, industries and business models by combining digital technologies to generate value in new ways.

As such, automation is certainly not the end of digitalisation for tech or any other sector. Digital transformation’s goal is to create and deliver new value not just to improve what is already being done. As an example, imagine an Operations Manager in a manufacturing facility which uses a clipboard to track production in different areas and record issues. Replacing the clipboard with tablet devices or even adding a sensor to measure the production output automatically will have benefits, but will not in itself be digitalisation.

The redesign of the manufacturing execution systems, machines in the production line and the use of the Internet of Things with sensors that can do all the monitoring, data collection and incident reporting would leave the operations manager to focus only on things that humans do well, like observe other aspects of the operation dynamics, motivate manage and empathise with his team. The automated manufacturing system, in this case, can monitor the production output and quality of the products continuously and, if necessary, alert the operational team or even autonomously execute decisions and address problems sooner than might otherwise have occurred with only human checks.

Many businesses have a simplified view of digitalisation as automation of work, replacing humans or paper with robots, machines, digital devices, etc. This can easily lead to false hopes of unrealistic benefits from automation.

With our PCP research group, we aim to help business understand what digitalisation really means and how to use the latest technology to digitally transform whilst harnessing human’s unique value. As in the example above, rather than dehumanising work and replacing the operational manager as part of the manufacturing operations team, technology was used to get the best out of both the humans and the machines.

It’s not about just taking people completely out of the process, but rather, enabling them to do what they are good at by using robots and automation to support and augment people. The digitalised business will present many opportunities for innovation and new sources of competitive advantage. However, creating and capturing this value will require a complete rethinking of the business and of work itself.