Artificial intelligence: HR friend or foe?

Purpose While the use of artificial intelligence (AI) in the workplace is on the rise, few understand how it will affect our jobs. Will it be a hindrance? A threat? Or the solution to the current productivity dilemma? As with any new, and largely untested, technology, AI brings both challenges and opportunities that we need to be conscious of. Design/methodology/approach The current and potential future implementation of AI technologies at Schneider Electric is assessed. Findings In HR, it is our responsibility to help navigate business leaders towards making the best business decision, often with the use of technology. AI, like analytics before it, has huge potential. Originality/value What we know for sure, is that the development of human talent has become one of the top priorities for global CEOs. With severe talent shortages in the UK, finding the right candidates for the job and investing in their professional development and well-being to keep them for longer look like no-brainers.

MOTIVATION FATIGUE AS A THREAT TO INNOVATION: BYPASSING THE PRODUCTIVITY DILEMMA IN R&D BY CYCLIC PRODUCTION

What do employees need in order to be innovative? In this paper, we explored how employees with different lengths of tenure within the research and development (R&D) department of a company in the automotive industry answer this question. We found that the needs vary depending on the length of the employee’s tenure. New employees view innovation as an organisational work issue and employees with longer tenure seek the support of management in changing the work situation themselves in a way that will enhance innovation. In contrast, employees who have been with the company over 10 years show signs of resignation and blame management for the problems around innovation that they experience. However, one opinion that all groups of different tenures share is that there is not enough time to engage in innovation activities. To address some of these different needs, we suggest viewing productivity as a cycle of two outcomes: product information and knowledge creation. When one is low, the other peaks, and vice versa. This view of dual value creation in R&D is one way to bypass the productivity dilemma.