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Gartner reveals the three common GenAI misconceptions impacting supply chains

AI In Contracts

Chief supply chain officers (CSCOs) risk alienating their people due to Generative AI (GenAI) misconceptions that could have a negative impact on talent strategies, says Gartner.

The technological research and consulting firm analysed cross-functional survey data that was collected in November 2023 from 822 business executives.

This comprised leaders outside of the IT function who were involved in their organisation’s GenAI strategy, which included 112 leaders from the supply chain function. 

According to the findings, supply chain led all functions in two areas: the number of executives that indicated they planned headcount reductions and the total amount of planned headcount to be reduced by 2025 from the deployment of GenAI.

Analysts discovered three common GenAI misconceptions that they say will soon negatively impact supply chain talent if CSCOs fail to make course corrections. 

Commenting on the findings, Sam Berndt, senior research director in Gartner’s supply chain practice said GenAI should provide an opportunity for CSCOs to achieve many of their talent aspirations, including freeing their teams up for higher value work and attracting top-tier technical talent.

 “Our data shows that there is a real risk that many CSCOs will use GenAI to double down on poor assumptions that have already resulted in talent shortages, burnout and retention challenges for the function,” he said.

The three misconceptions are:

GenAI is primarily about labour cost savings and efficiency


An overemphasis on labour cost reductions risks not only being unrealistic, but also alienating the workforce as they see their prospects for long-term industry careers diminish. Instead of focusing primarily on cost reduction, Gartner says CSCOs should emphasise GenAI’s ability to unlock new levels of productivity.

“Employees who receive access to GenAI tools quickly notice a broad range of benefits, from improved decision making to better skill development,” said Berndt.

 “GenAI then becomes supportive of retention, as it improves the employee experience, and the organisation can reap the associated productivity benefits.”

GenAI threatens early career employees


Supply chain leaders indicate that most of the headcount reduction would fall on early career employees. Gartner explains that for a function that already struggles with attracting and recruiting new talent, this assumption will only make it more difficult to fill and maintain talent pipelines.

“Instead of viewing GenAI as a threat to entry level employees, CSCOs can advertise their use of the technology as an effective recruitment tool,” Berndt said.

“GenAI use and accessibility can be a powerful recruitment tool for younger generations who view working with the technology as a job benefit.”

GenAI is tangential to employees’ lives


Supply chain organisations have been slow to communicate how GenAI will impact the workforce. Gartner says without this communication, employees are filling the void with their own sources of information, speculation and anxieties about future job security.

“Even a sceptical CSCO with minimal plans for GenAI should provide clear communications about the organisation’s plans for the technology, and how it will affect the future of work. Employees are already forming conclusions about it that are almost certainly more negative than what CSCOs would want,” concludes Berndt.

Gartner provides three steps CSCOs can take to help shape the impact of GenAI on their organisations, including:

1. Start clear and regular communication with teams about GenAI and how the organisation is exploring it

2.  Shape the GenAI conversation through experimentation, including identifying the use cases beyond chatbots that will ultimately require new roles and organisational structures to support them

3. Treat GenAI as a future of work shift, not just a new technology. Use early enthusiasm about the technology to start building awareness around basic GenAI skills and behaviours (e.g. how to engineer and iterate prompts).

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