Make work human: Taking the robot out of human workers by automating at scale

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Nelson Mandela said that, “The brave man is not he who does not feel afraid, but he who conquers that fear.” The modern-day workforce has done just that, according to recent academic research , commissioned by Automation Anywhere

The research showed that a majority of workers has transitioned from fearing that artificial intelligence (AI) will take jobs away, to a belief that of AI actually helping us do our jobs better and faster. This evolution of public opinion hasn’t arisen from the simple passing of time, rather it comes on the heels of considerable work and investment from companies, both of their workforces and the technologies themselves. 

The study shows that the majority (72 per cent) of workers surveyed don’t fear automation or AI and two thirds (66 per cent) actually want to know more about how the technology can help them do their jobs better. When implemented correctly, these technologies not only improve efficiency in business functions, but can also lead to more engaged and happier employees. The onus is now on business leaders to take meaningful steps to adopt these technologies at scale. However, this is easier said than done.

Make work human: The research

The study sets out to find the primary challenges and opportunities organisations face when implementing automation technology at scale, both in relation to performance and to making work more human. To augment a workforce is a continuous journey, and the report identifies several distinct areas relating to these challenges. Technology, skills, diversity, authenticity, and resilience lie at the heart of these challenges and must be addressed if businesses are to successfully augment their workforces with intelligent automation and AI technology, at scale.

Challenge 1: Technology

How do you build a culture that can evolve as the technology evolves? 

The challenge to scaling automation or AI across an organisation is not the difficulty of implementing the technology itself, but thinking more holistically about the organisation as a culture that needs to adapt and support changes to its working environment.

The research uncovered three facets to this challenge that are focused on:

  • Having an augmentation-ready culture and workforce. Few companies are embarking on an upskilling program alongside an automation program in a scalable way.
  • Strategic thinking about the business case and board level buy-in. The research pointed to the importance of projects being driven at a board level, but this often fails to be the case. 
  • Harnessing the key attributes of technology itself. Part of the challenge of scaling up is using automation to make sense of the vast and varied data now available to businesses.

Challenge 2: Skills 

How can organisations place people at the heart of their automation plans?

The workforce of the future will increasingly work with automation, rather than be replaced by it. As more jobs become supported by automation, the culture of the organisation will need to change. Organisations need to start thinking now about implications for hiring, reskilling, upskilling, lifelong learning, and rethinking the way we think about jobs.

The research found that the challenge of augmentation is to optimise human skills in collaboration with automation technologies. Automation and AI impact the workplace in two fundamental ways:

* They alter the way we work, alleviating or replacing many repetitive tasks and allowing us to concentrate on more human pursuits.

*They directly impact the HR process, changing the way people are hired, engaged within the company and managed. Within the existing workforce, upskilling and skills transfer will become paramount to remain relevant as these technologies begin to scale.

Challenge 3: Diversity

How can organisations act to enable equal access to AI and Automation capabilities across the workforce? 

Radical societal change brings with it a fundamental shift in trust. Automation and, especially AI come with a unique set of trust issues: not only is the technology new, but it promises to disrupt nearly every existing industry. From a diversity standpoint, AI can have an impact on both the practitioners creating and using the technology and the people affected by the data and algorithms generated. 

The World Economic Forum recently reported that only 22 per cent of global AI professionals are female and they note this gap has “remained constant over the past years” even as “AI encompasses an increasingly in-demand skillset.” The report warned that algorithms and biased data may provide avenues that disproportionately affect women, those less able, the vulnerable, lower income brackets and others. If certain demographic groups aren’t present in a data set, for example, they won’t be selected by the algorithm going forward. Or if a data set is overweighed with one kind of population sample, then bias will likely be present.

Today, both the education and the tech sector struggle to regain gender parity. Only 27 per cent of female students surveyed said they would consider a career in technology, compared to 61 per cent of males, and that only 3 per cent of females said it would be their first choice. 

Challenge 4: Authenticity

Do organisations have a responsibility to be open about their use of automation, and are they realistic about its potential?  

Gartner analysts consider AI mischaracterisation to be one of the top three problems that are impeding real development and adoption of artificial intelligence technology. Many companies claim to be using RPA or AI in some capacity, but how are they communicating its use to their customers and internally to their workers?

The research uncovered the challenge of authenticity; the decision to embed your ethics throughout of your organisation. Innovation is only possible with the buy-in and support of leadership, the employees tasked with developing it, and the people who will be impacted once the process is complete. Augmentation is not just about new technology; it is about changing the organisational culture. In today’s work environment, authenticity is highly valued. Motivating the workforce by ensuring trust, authenticity and transparency is of paramount importance at a time when that change can be so difficult to understand.

The key is to promote authentic engagement and motivation across an organisation by building real and valuable relationships and not over-promising to customers or to employees.

Challenge 5: Resilience

How can organisations create a culture of responsiveness to change, in readiness for widescale automation deployment?

The World Economic Forum (WEF) suggests that the right attitude coming from leaders is more important than intelligence. Resilience allows employees to come along for the journey and to focus on learning rather than a specific outcome or goal. The WEF also believes that new technology will create twice as many job opportunities as are lost. These new jobs are likely to require very different skills (typically people-centred ones).  

The research also brought to light the challenge of promoting dynamism – an innovative organisation capable of responding to change. To be augmented you have to think ‘augmented’. It is a journey and a constant process: change will happen, and humans will have to respond - so without the right mindset, businesses risk training and re-skilling for the wrong jobs.  

Let machines be machines and let humans be human

The five challenges outlined in this research can act as a road map for business leaders grappling with implementing these technologies in the most impactful way – at scale. Today, workers have shown an appetite to engage with these new technologies. Organisations that fail to adopt these technologies at scale are not just missing an opportunity to gain a competitive edge in an increasingly crowded global market, they are also turning their back on employee wellbeing and the future of work.

The future of the augmented enterprise is clear: a blended workforce of human workers and intelligent automation technologies, in which both machines and people can do what they do best. Let machines be machines, working on repetitive, consistent, and precise processes. And let humans be human, where they can be strategic, imaginative, and engaged, doing things that only humans can do.

James Dening. Vice President and Digital Worker Evangelist, Automation Anywhere