How AI impacts different personas
AI is reshaping the manufacturing industry and affecting employees and stakeholders in distinct ways. Depending on the role and function a person or team serves within the organisation, the impact on their way of working will differ. For example, leadership roles experience AI’s influence during strategic decision making, while operators encounter more operational changes focused on automation or efficiency. A good understanding of these nuances is crucial to tailor the change approach and increase adoption from all impacted stakeholders. To facilitate this, we’ve grouped similarly impacted roles into personas, each with specific ways of interacting with AI.
When evaluating or integrating AI solutions, take time to identify which personas you’re impacting and what the impact will be. This will help you tailor solutions and adapt approaches to the unique needs of each, boosting the speed of adoption and making the change more sustainable.
Inspiring employees and increasing adoption
As AI continues to transform manufacturing, the biggest challenge will be to engage your workforce and other key stakeholders and incorporate AI in your way of working. Adoption of AI doesn’t come from one-shot transformation and training programmes, but needs to be a continuous flow of small changes across the whole organisation (and beyond). To secure the successful adoption of AI, companies must invest in effective change management strategies that address the needs of all impacted stakeholders, starting from the overview of personas.
Success factors and pitfalls
Success in implementing AI hinges on several key factors, with a strong focus on workforce involvement and ethical considerations.
High-quality data: AI systems need clean, accurate and timely data to make informed decisions.
Seamless integration with existing systems: Companies face challenges when trying to incorporate AI into legacy technologies and the workforce must be prepared to manage this transition.
A workforce capable of working alongside AI systems: Human expertise remains indispensable.
Use AI for specific business objectives: AI shouldn’t be adopted without a clear understanding of its impact on both the organisation and its workforce.
Continuous monitoring and improvement: AI systems must evolve with changing business needs, technological advances and ethical standards.
Case 1
Reynaers Aluminium demand forecasting
With no forecasting module/system to feed its existing inventory solution, Reynaers Aluminium faced stock outs of some profiles and overstocking of others. To speed up the development of the company’s demand forecasting capability, the team decided to leverage AI for a first prediction based on historical data. By leveraging a hybrid approach, Reynaers Aluminium successfully built a robust demand forecasting capability. The project also shows that while AI tools can significantly enhance operational efficiency, their true value is realised when there’s a clear case for change, when they’re integrated with effective processes and when the benefits are clearly communicated to all stakeholders.
Case 2
PwC Belgium: Capture the AI Flag
Many companies struggle to understand the immediate impact AI could have on their daily operations. Despite growing interest, there’s a significant gap in practical knowledge and hands-on experience. To address this, PwC Belgium’s Experience Centre developed a bespoke Capture the AI Flag game that offers an engaging and educational experience to help demystify (Gen)AI and demonstrate its tangible benefits. PwC Belgium identified several key lessons from the initial iterations of Capture the AI Flag:
- Advancing along with AI: The team is constantly looking at how to make sure the game remains challenging and fun as the technology advances.
- Player engagement: The interactive and competitive nature of the game keeps participants engaged and motivated.
- Real-world scenarios: The game can be tailored to suit different contexts to help participants better relate AI concepts to their own operations, making the learning experience more impactful.
Focusing on the human element of AI integration
The human element of AI integrations involves recognising how AI impacts various personas within an organisation. It’s crucial to tailor solutions and adapt approaches to the unique needs of each persona to secure successful adoption. A clear strategy, effective communication, engagement, upskilling and reskilling are key strategies for increasing workforce adoption of AI.
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