AI in the workplace: ally or disruptor?
June 14, 2021
Paraphrasing a famous quote falsely attributed to Darwin but useful to summarize his thought, those who survive are those who know how to adapt to the changing environment in which they find themselves. All the others are simply wiped out, like dinosaurs annihilated by a large asteroid known as the Chicxulub impactor, or like Blockbuster hit by an even larger planetoid called Netflix.
And so, while artificial intelligence seems set to impact with the force of a meteorite on every single aspect of our lives, including workplaces, millions of employees ask the question: "Will AI be an ally capable of improving my working conditions, or an enemy responsible for the end of my career”?
Let's try to give an honest answer to these doubts and to understand how managers and employees may address the challenges of a new labor market reshaped by artificial intelligence.
How AI is reshaping the job market
From recruiting and onboarding to the training stage, from professional development to business process management, AI with its machine learning and deep learning branches is playing an ever-growing role that encompasses virtually any aspect of our careers. The adoption of AI in the workplace is notoriously on the rise, propelled by significant investments in implementation strategies but also the availability of machine learning consulting.
Alongside RPA, robotics, and cognitive technologies, AI represents one of the main tools deployed to either fully automate certain tasks or enhance or assist employees in fulfilling their duties. According to Deloitte’s 2019 Global Human Capital Trends study, 22% of the organizations surveyed already implemented AI while an additional 44% were exploring such possibility.
This abrupt trend has led to a complete redesign of jobs across a wide range of industries but, like any major technological and social upheaval, it has also sparked uncertainty and concern. Indeed, 64% of the respondents in the aforementioned survey consider artificial intelligence and robotics an important or very important issue for human capital, while only 26% of the interviewed declared that their corporations would be “ready or very ready” to face the impact of such technologies.
In this regard, one of the most widespread fears is certainly related to potential job displacement. Based on Mercer's 2020 Global Talent Trends survey of 7,300 business executives, HR leaders, and employees, 34% of the latter expect their jobs to be replaced in three years. Moreover, only 34% of HR leaders are investing in workforce training and reskilling to prepare for the upcoming changes, while business executives think that only 45% of their employees would be able to adapt to a job market reforged by the advent of AI. Not exactly the kind of exciting prospect.
On the other hand, 61% of employees believe their employers are preparing their workforce for future automation developments, and 55% trust their companies with regard to retraining. Furthermore, 78% of them said they are ready to learn new skills.
Automation, augmentation, or displacement?
The apparent inconsistency among different stats can only fuel the lively debate among pessimists, who expect workers to be massively replaced by AI-powered automation, and optimists, who think these technologies will generate new types of jobs, "augment" employees, and improve their workplaces.
The truth probably lies somewhere in between as the ultimate effect of AI, firstly in terms of job availability and secondly of work experience and performance, could be a sum of positive vs negative tendencies and will likely depend on how we approach this revolution.
Regarding the first aspect, the 2018 World Economic Forum report pointed out how the rising adoption of machines and algorithms in the workplace could create 133 million new positions compared to "only" 75 million that will be displaced by 2022. However, according to the report, such a positive trend may only be unlocked by proactively investing in workforce upskilling.
This encouraging forecast seems to be corroborated by PwC's 2019 AI Predictions paper, according to which the surveyed executives tend not to view AI as a source of job disruption in their organizations. 38% of them said artificial intelligence will lead to an increase in headcount, while only 19% think AI may provoke job cuts.
As for the employees' work experience and potential, Deloitte’s 2018 State of AI in the Enterprise 2nd Edition survey reported that AI adopters generally see more value in using AI-based automation to free up workers for more creative activities than to cut jobs.
Executives also consider artificial intelligence effective in making workers better at their jobs and happier. 78% of the respondents said that AI and cognitive technologies empower people to make better decisions, while 72% think that AI may increase job satisfaction. Finally, 78% of the executives surveyed believe AI will augment employees, ensuring new ways of working.
Which new ways of working are they talking about? Let's take a look, starting with the most relevant effect of AI in the workplace, namely workforce augmentation.
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A new enhanced workforce
"Augmentation" seems to be the watchword of today's AI implementation, as it summarizes a vision in which AI-powered machines may support and enhance employees in their workplace rather than replace them.
In particular, AI systems would take care of all those repetitive and dehumanizing tasks that make us come back home unnerved after a long working day, letting us focus on the most motivating aspects of our jobs, such as creative activities, socializing, and data-driven decision making.
These changes will trigger an overall shift in the type of expertise that the workforce needs. Specifically, the focus will move from manual skills to technological, cognitive, and emotional competencies, as predicted by McKinsey's AI, Automation, and the Future of Work analysis.
From doctors to AI-augmented super docs
Real-life examples of this growing trend can be found in a wide variety of AI applications across many industries. One of them is machine learning in healthcare used for diagnostics. Indeed, diagnoses are determined by comparing patients' information with the typical patterns of diseases to find out if they match. And artificial intelligence is the real “Sherlock” of pattern investigation.
Machine learning and deep learning algorithms can be trained with massive datasets collected from previous patients' cases, detect recurring patterns among the data they are fed with, and progressively learn to recognize potential signs of various diseases. In many medical disciplines, data analytics in healthcare powered by AI already proved invaluable to assist doctors with useful insights, suggest diagnoses and recommend proper treatments.
This implies that medics, exempt from or assisted in time-consuming data analytics tasks, could focus more on the patient's well-being, both physical and psychological. They may, for example, spend more time helping the patient understand and accept diagnoses or subsequent treatment plans.
AI, call centers, and human approach
Another significant example of AI's impact on jobs relates to the workflow of call centers. This type of workplace, as well as any other environment subject to customer service automation, can greatly benefit from the assistance of AI-powered tools. Think about chatbots enhanced with natural language processing technologies, which can deal with huge amounts of routine queries faster than humans and without longing for a coffee break.
This new approach allows human operators to handle the most complex cases, acting as problem-solvers and focusing on the relational and emotional aspects of their work. After all, you may need a machine to quickly respond to a thousand complaints about momentary internet outages. But you also need human empathy and context understanding to reassure a customer in your business continuity.
Once again, this combination of machines and human employees in call centers showed its potential in the healthcare field, especially during the hard times of the pandemic. As reported by Harvard Business Review, a major healthcare provider deployed an AI-based bot to alleviate the hotline traffic volume. This bot was assigned the task to present patients with several questions from the US Centers for Disease Control and Prevention for triaging purposes, allowing healthcare professionals to take care of the most pressing cases.
When robots lift weights for you...
Artificial intelligence, as you may expect, is also paving the way for manual labor transformation. Among AI use cases involving workplaces and augmented workforce, indeed, it's worth mentioning modern developments in logistics and warehouse processes. Partial workflow automation is already widespread and implies AI-driven robots complementing human workers in fulfilling their duties, such as by lifting and stacking merchandise.
Similar synergies can be found in the main storages of ecommerce leaders, including of course Amazon. At their warehouse in Kent, WA, dozens of robots seemingly wander around chaotically while transporting vertical shelves loaded with goods, but never bump into each other. And so, while artificial intelligence works tirelessly to optimize product movement and robot coordination, employees take care of ‘babysitting’ the machines to make sure everything runs smoothly.
Other ways to leverage AI
As previously mentioned, artificial intelligence is a technology affecting every aspect of our jobs and workplaces. Here are some of the most important areas:
- Headhunting: The influence of AI on our careers begins even before we set foot in a new office. For example, machine learning and predictive analytics software can be used to pre-screen candidates and filter the most suitable ones for the interview, matching their data with the required profiles. Even the recommendation engines of major job search websites take advantage of ML, including LinkedIn.
- Job interviews: Once the candidates are selected, it's time for interviews and assessments, which can be partially automated and assisted via AI using HR predictive analytics. An example of this approach, which represents a mainstay of HR digital transformation, is that of the British-Dutch giant Unilever, which saved a cumulative 50,000 hours of candidates' time and reduced the hiring process length from 4 months to 4 weeks. Their AI-powered hiring system can even analyze the body language, use of keywords, and tone of applicants.
- Training: Several corporations leverage AI in education to catalyze employees’ professional development. The Faethm data analytics platform deployed by Mastercard collects information regarding performances, careers, and so on, to offer personalized suggestions on the best learning strategies and career progression. Honeywell, on the other hand, is betting on AR/VR tools, which allow new hires to experience their tasks through virtual reality.
- Employee monitoring: The last (and potentially most controversial point of our list) relates to AI implementation for employee monitoring and surveillance. On the one hand, AI-powered systems can be deployed to ensure the well-being of workers. In this regard, Blizzard Activision offered incentives for employees who would agree to use health wearables to monitor their physical conditions.
On the other hand, many leading companies have already adopted artificial intelligence and data analytics to keep an eye on staff performance and activity (over 50% of corporations with a turnover above $750 million, according to Gartner estimates). This includes initiatives against "rogue employees" taken by financial institutions such as J.P. Morgan for some years to monitor their employees and identify any criminal activity.
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Today's challenges for tomorrow's success
Artificial intelligence is an extraordinary tool, capable of transforming our workplaces and revolutionizing the employee experience at best. However, its implementation raises some questions that will need to be answered in the near future.
- Can we contain the intrusiveness of AI within reasonable limits? This issue will be more and more important as the regulation of privacy and data management becomes increasingly stringent (think the GDPR).
- Is it possible to avoid a mass job disruption? Probably yes, but only if we'll be able to reallocate the affected workforce to new positions opened by technological innovations.
- How can we close the skills gap required by job transformation? The prospect to simply replace workers with new, AI-ready staff may be inviting. However, it sounds pretty naive in a job market notoriously affected by AI talent shortage. A good alternative? Investing in job reskilling and upskilling.
By effectively addressing these challenges, we will ensure (paraphrasing our astronomical introduction) that the effect of AI on workplaces ends up being more like a beautiful comet tail in the sky than a cataclysmic meteorite impact.
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