Businesses are stepping up their efforts to implement AI across the board. But while the technology promises a raft of productivity and efficiency gains, fear of AI amongst the workforce is rife, and should not be taken lightly. Left unaddressed, fear today almost certainly means friction and resistance tomorrow.
From Chat GPT and Midjourney to e-commerce chatbots and virtual assistants, Generative Artificial Intelligence (AI) is changing the way we create, consume, and connect. And in the coming years, its reach is primed to increase dramatically.
On the one hand, this technology holds the promise of increased productivity, accuracy, and savings; on the other, it threatens job disruption, possibly even replacement.
For example, the UK’s Office for National Statistics found that, while more than a quarter of employed adults believe AI could make their job easier, a third of the workforce is worried that the technology will put their jobs at risk.
The tech-optimist perspective is that AI will create new jobs and change existing ones for the better while reducing the need for lower-value work. But there’s a danger that, as companies rush to embrace AI and secure competitive advantage, this nuance gets lost on workers.
As one executive at a leading consumer-packaged-goods company recently explained to me, “When people hear AI, they think ‘My job is going away’ versus ‘My job is changing’… It’s hard for people to see what they’ve never known could be.”
Assuaging these concerns and building internal trust that AI is here to empower, not eradicate, will require very human traits: empathy, sensitivity, patience, and persuasion. Business leaders need to win hearts as well as minds, or they’ll encounter resistance at each stage of the AI maturity journey.
Consider a typical supply chain, for example. Enterprise supply chain operations span multiple geographies and rely upon thousands of employees with distinct skill sets, carrying out a wide variety of different roles. The introduction of AI will transform practically all of these jobs, yet the application of the technology will be markedly different according to role.
With our latest research showing that 37% of supply chain leaders planning to invest heavily in generative AI in the near future, it’s clear that the change journey is already underway, making it all the more important that this process is managed with care and consideration from those at the helm.
Here are five steps that will help bring employees onside as AI adoption accelerates:
1) Build trust through transparency
It’s important to clearly communicate the purpose and potential of AI to each worker cohort, emphasising how it will complement their skills and boost their productivity. The more radical the innovation being proposed, the more convincing and comprehensive the pitch required to get people on board.
Clear visualisations that explain the AI activity and its value, as well as the potential costs and risks, can be particularly useful at the start of the journey. And the message should be updated and shared often between the point of ideation all the way through to delivery, and tailored to employees’ changing concerns and priorities, to maintain emotional momentum.
2) Empower AI evangelists
Just as brands rely on popular influencers to generate goodwill for their products, business leaders can identify and support employees who are enthusiastic about AI to become internal champions, fostering a positive dialogue across the wider workforce and addressing any concerns as they come up.
The trick is to work back from the employees who need persuading, and identify change champions who are already credible with these groups, regardless of whether they have prior experience working with AI.
3) Bridge the jargon gap
Using jargon and other inaccessible language doesn’t just hinder comprehension; it can breed distrust too. According to Hilary Shulman, an associate professor at the Ohio State University School of Communication, “The use of difficult, specialized words is a signal that tells people that they don’t belong… You can tell them what the terms mean, but it doesn’t matter. They already feel like this message isn’t for them.”
To avoid shutting people out, business leaders need to identify and train up employees with a proven knack for explaining technical topics in terms that their peers understand – and, conversely, translating employees’ practical needs and requests (i.e. where they think AI could help them) for the technical partners driving implementation.
4) Demystify AI through learning
Many of the early attempts to introduce statistical forecasting models into businesses were blighted by workers’ proclivity to adjust the software’s forecasts based on their own judgements. This type of anti-machine bias tends to arise from a lack of understanding about how the software works or what it is designed to do.
In the case of inscrutable AI models, total comprehension may not be possible, however, it’s still a good idea to try and demystify what the AI is doing and why. One effective and easy-to-implement learning technique is to create simulations using open-source AI tools, showing employees the impact of making a particular business decision with and without the AI involved.
5) Prioritise continuous feedback
With any major change, it’s essential to solicit frequent feedback to see how people are adjusting to the AI-empowered world. Regular stakeholder check-ins, town halls, and pulse surveys are great ways to track attitudes and adoption, as are digital tools such as feedback pop-ups and electronic tracking built into the AI solutions themselves.
A proactive approach to feedback also makes staff feel as though their opinions and feelings are being taken seriously by leadership. As trust is built, the introduction of AI becomes less of a threat to the workforce and more of a mutually beneficial innovation, where the impact on employees is seen to matter as much as the bottom line.
For businesses looking to bring AI into the heart of their day-to-day operations, bringing employees on board really is half the battle – and must be prioritised from the outset.
About the Author
Steve Hochman is a 20+ year veteran of supply chain innovation at venture-backed startups and large global brands. Steve led global supply chain strategy for Nike and later was the company’s head of S&OP and VP, Global DTC supply chain. Earlier in his career, Steve was a Bain & Co consultant and product manager for Intel’s New Business group. Steve also helped launch three circular economy supply chain startups and co-led the Global Environmental Management Initiative, a consortium of Fortune 500 companies devoted to source-based waste reduction.
