Faculty & Research
Faculty & Research
AI will only boost productivity when it works hand in glove with humans
By Byron Lee
AI has promised so much since its inception. In terms of boosting productivity, however, it has to date not delivered on its promise. In fact, like so many world-changing technologies before it, AI has actually slowed productivity growth during its period of infancy, rather than meaningfully boosting it. So, why is it not living up to even the more modest expectations set by its proponents? The answer doesn't lie in realm of technical limitations. Instead, we're simply not using it to its full potential.
Making the most of AI requires an organisation to carry out a complete redesigning of job roles, specific tasks and the overall structure of work to better combine the capabilities of AI solutions and the humans operating them. Digitalisation should not be viewed narrowly as a battle to "secure the latest tech first." Having the best AI does not necessarily lead to the most successful creation of value in firms. Rather, any long-term success in digitalisation efforts must come from a willingness to take appropriate technologies and recombine them within an existing operational setup to create value for employees, customers and society at large.
Leveraging AI is about taking the best of humans and machines together to maximise the potential and productivity of both. This can be expressed as:
increased labour productivity (from AI) = new AI technology + design of complementary processes and assets in organisations
Achieving this requires a wholesale redesigning of a firm's structure, its HR organisational practices and the culture that employees follow to achieve everyday work. In thinking about AI, firms need to consider the existing value created by jobs and then how to dismantle and redesign jobs to better capture the potential of humans and machines working in concert in the Digital Age.
One framework to consider this job redesign process is to use the classic Job Characteristics Theory posed by organisational psychologists Richard Hackman and Greg Oldham. During a time where the industrial revolution was in full force and services based work was increasing in importance, Hackman and Oldham asked, how do we design jobs so that they genuinely motivate people? In today's age, we can extend to this model to ask, how can firms use AI and employees to interact and create value for their firms in a digital organisation, while keeping employees motivated?
When it comes to (re)designing jobs, the use of AI must be considered in terms of its implications on the following five Characteristics of Work related to employee motivation:
- Skill variety – We all want to learn. We all want work that lets us carry out a variety of engaging tasks. Is digitalisation replacing boring repetitive parts of a job so that employees are freed up to learn new skills and knowledge that can benefit the firm?
- Task identity and task significance – These two elements constitute the 'meaning' of the work. Employees want meaning in their jobs. When machines take over some tasks, are employees able to more clearly see how their existing or new tasks are linked to a deeper contribution to the firm or even society?
- Autonomy – It is dangerous to use AI as the sole decision maker in a firm. When autonomy is taken away from employees, they may react with counterproductive behaviour. Hence, firms need to communicate the advantages of AI in supporting employees in making better decisions. This requires the integration of the decision making process so that both technology and humans work together to refine and make better decisions for the firm.
- Feedback – AI is not the perfect technology and continues to improve based on better algorithms and training data. Hence, both employees and AI can improve through the receipt of feedback and experimenting with changes suggested by other parties. Firms should provide the space and freedom to allow for healthy interaction to test whether such feedback can help improve both AI and employee results.
By considering this framework, organisations can more systematically redesign tasks as they integrate AI into the firm. In doing so, they will enjoy greater success in their long-term digitalisation efforts. Designing jobs that are focused on employees, yet incorporate the benefits of AI can lead to more rewarding and 'meaningful' work, greater upskilling of human capital and higher productivity for organisations overall. If we fail to design jobs with employees at the core, we may be left with a firm that is fully digital, but without the vitality and spirit of motivated employees that help the firm adapt and thrive in the changing context of the business world.
The redesign of jobs to incorporate AI is just a starting point in understanding this new and exciting field. As firms move towards greater and greater degrees of digital transformation, further research in understanding the ethical, economic and equality implications of digitalization is needed.
AI isn't an end goal; it is just the first step forward. To have a positive impact, we need to better understand how to take the best of machines and humans and combine them for the betterment of society.
Byron Lee is an Associate Professor of Management at CEIBS. For more on his teaching and research interests, please visit his faculty profile here.