In the evolving landscape of AI integration, leaders must recognise and address the intricate human dynamics that can either propel or impede progress. In the Humans & AI in the workplcace Podcast we delve into the nuances of AI adoption, emphasising the pivotal role of mitigating these human bottlenecks for successful implementation.Here are three actionable strategies for leaders to navigate these challenges effectively:
1. Foster a Culture of Knowledge Sharing and Capacity Building
To counteract key person dependencies and capacity challenges, leaders must prioritise knowledge dissemination across teams. Encourage mentoring relationships, facilitate cross-functional training sessions, and leverage digital tools for efficient knowledge transfer. By empowering employees to acquire diverse skills and expertise, organisations can mitigate the risks associated with individual dependencies and enhance organisational resilience.Practical actions for Knowledge Sharing
To address Subject Matter Expert capacity start with spreading their knowledge to others. Your Subject Matter Experts are probably already stretched and pulled in every direction. This is only going to get worse, and you risk losing them. Here are some tactics to help you do this:- Get someone to shadow them
- Or pay the Expert a training bonus to train people across the business.
- Or help them document their knowledge using Speech to text and ChatGPT. If they are lacking capacity to do this, start by getting them to list out all the areas and problems are asked to consult in. Then have someone else run those topics through ChatGPT (or other Large Language Model). Put the results in front of your expert – as a first draft for them to review and fix.
Practical Actions for Capacity Building
To address Leadership Capacity challenges or when employees are not turning up to forums and meetings due to a lack of capacity:- Build an engagement plan – It’s your ‘go slow now, to go fast later’ option.
- Map out how you are going to approach and engage the people and groups you need on board and when
- Include how you are going to do it in a way that fits into their schedule.
- Now this is important. Normally we ask leaders and employees to fit into our schedule. But in a change strategy, we want you to find the path forward where you bend to them, rather than them bending to you.
- Make it easy for them to do what you need them to do.
2. Develop a targeted and comprehensive AI Change Strategy
Effective change management is paramount in fostering employee buy-in and overcoming resistance to AI adoption. Now more then ever leaders need to be thoughtful creating change in their organisation -especially driven by intelligent technologies.Taking the time initially to understand the intent for the change, the practicalities of what’s changing and what will stay the same, how it will change team interactions and individual roles and habits are just some of the key areas that require understanding before acting. Proactively understanding where the human bottlenecks are likely to appear in your organisation allows you to craft strategies and tactics to overcome these in advance. A tailored change strategy that prioritises inclusive design principles, clear communication, practical and accessible stakeholder engagement, and ongoing mechanisms for active participation will set you up for not only creating better experiences, but better outcomes overall. By involving employees in the decision-making process and addressing their concerns proactively, organisations can also foster a culture of ownership and accountability, laying the groundwork for successful AI implementation.A good change strategy covers the following key areas for AI change:- Context – an overview of the change (why the change is happening -the intent- and what is actually going to change)
- High Level Impacts – an overview of the high level impacts forecasted with a detailed change assessment completed across key areas of the business. Covers changes in skills and capabilities, culture and organisational structure for Humans and AI to work effectively as teammates.
- Watch outs and Enablers – an overview of the key factors that may enable the change in work practices and behaviours and support the change as well as the watchouts/human bottlenecks that require attention to avoid disruption and wasted effort.
- People Change Risks – an overview of ‘people’ change risks that need to me mitigated during the change and ongoing engagement period.
- Recommended Approach – Step by step guide for ‘how to deliver the change’ including communication and engagement options, leadership actions, learning opportunities, governance and metrics for AI change adoption.
- AI Change Roadmap –high level roadmap to guide activities and timings and help make decisions over time.
3. Cultivate an environment where ‘Iteration and Adaptation’ are rewarded
In the pursuit of AI-driven innovation and productivity, leaders must cultivate an organisational culture that repels perfectionism and embraces experimentation, iteration, and continuous improvement. By fostering this, the culture will generate innovation and adaptability, and organisations can navigate the complexities of AI integration with resilience and agility, positioning themselves for long-term success in the digital era.To do this, leaders need to encourage teams to adopt an experimentation approach, where failures are viewed as learning opportunities and feedback loops drive iterative refinement. This means changing your language to be more focused on the outcome and learnings, as much as it is about rewarding success. Asking how your teams co-created and collaborated across the business to deliver outcomes can start to change behaviours. Then of course you have to role model the change you want others to make as well. Especially when it comes to working with your peers in other areas of the business. Share how you are optimising your work using intelligent technologies, what’s working well, what isn’t yet working well etc. with your peers.
By embracing these strategies, leaders can effectively address human bottlenecks and cultivate an environment conducive to AI-driven productivity and transformation.
With a proactive approach to mitigating human challenges, leaders and organisations can harness the full potential of AI technology to elevate the performance of their people.
