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The 3 things leaders can do to reduce the fear of AI in their team

In the ever-evolving landscape of modern workplaces, the integration of Artificial Intelligence (AI) has become not just a possibility, but a necessity. However, the mere mention of AI often evokes fear and uncertainty among team members. In our Humans & AI Podcast we tackle this topic specifically as the fear of AI is attracting more and more attention in the workplace. Effective leaders of change, recognise this challenge and proactively take steps to alleviate fears and cultivate confidence in AI adoption.Here are three practical strategies for leaders to reduce the fear of AI within their teams.

1. Become AI Fluent

Language serves as the cornerstone of effective communication and understanding.  Leaders must use language that demystifies AI and provides clarity on its realistic impacts, fostering curiosity and understanding among team members.You can build your AI fluency and effectively communicate AI concepts using the following tactics. (You can also find more information in our AI Adaptive Knowledge Centre):

  • Participate in Free Online Courses

    Explore the free online courses on AI fundamentals at Coursera, edX, and Udemy. Each offer comprehensive courses designed to enhance AI fluency.

  • Leverage Learning from IT Teams

    Collaborate closely with your IT team to understand AI use cases specific to your organization. Engage in discussions and seek insights on how AI can enhance existing processes and workflows.

  • Network and Learn

    Reach out to industry peers and experts to gain insights into their AI journeys. Attend conferences, webinars, and networking events to stay updated on the latest trends and best practices in AI adoption.

  • Follow Industry Leaders

    Utilize professional networking platforms, like LinkedIn, to follow key industry leaders and influencers in the field of AI. Engage with their content, participate in discussions, and stay informed about emerging AI trends.

  • Read Foundational Literature

    Delve into foundational books and resources such as Harvard Business Review’s “HBR Guide AI Basics for Managers” to deepen your understanding of AI concepts and principles. We have a full list of recommended books in the AI Adaptive Knowledge Centre under Expand on the Resources tab.

2. Curate Opportunities for Exploration

Leaders play a pivotal role in fostering a culture of experimentation and exploration within their teams. By creating structured opportunities for team members to engage with AI technologies, leaders can demystify AI and instil confidence in its potential. More and more Leaders will need to help their people see AI as a ‘team mate’.

Here are practical ways to curate opportunities for exploration:

  • Host Lunch and Learn Sessions

    Organise informal lunch and learn sessions where team members can explore AI use cases and discuss potential applications in their roles.

  • Encourage Hands-on Experimentation

    Provide access to AI tools and platforms for hands-on experimentation. Encourage team members to explore AI capabilities and brainstorm innovative solutions to business challenges.

  • Facilitate Cross-functional Collaboration

    Foster collaboration between different departments and teams to explore AI opportunities across various business functions. Break down silos and encourage knowledge sharing and cross-pollination of ideas to drive innovation.

3. Build an Optimisation Mindset Culture

Effective leaders understand the importance of embracing an optimisation mindset when integrating AI into work processes. By promoting a culture of progress over perfection, they empower their teams to embrace experimentation, iteration, and continuous improvement.

Here are actionable steps to build an optimisation mindset culture:

  • Provide Clarity on Expectations

    Clearly communicate expectations regarding progress and improvement. Set realistic goals and milestones, and encourage team members to focus on incremental gains.

  • Emphasize Learning and Adaptation

    Encourage a growth mindset where learning and adaptation are celebrated. Create a safe environment where team members feel empowered to experiment, fail, and learn from their experiences.

  • Reward Iterative Progress

    Recognise and reward iterative progress and incremental improvements. Celebrate small wins and milestones achieved along the AI adoption journey.

It’s never been a more important time to be leader who is thoughtful about creating the best experience of change in their business. The integration of Humans and AI in the workplace, is an important and significant evolution of how we work (and live) and it will be the leaders who are good at leading change, that are able to mitigate fears and foster confidence, enabling their team to understand how to leverage this technology to serve them in their work.

By watching your language, curating opportunities for exploration, and building an optimisation mindset culture, you can empower your team to embrace AI technologies with enthusiasm and confidence.As organisations navigate the complexities of integrating Humans and AI in the workplace, it is this efficacy as a leader of change, that will pave the way for successful AI adoption and business transformation.

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Why Digital Literacy and Responsible AI are crucial for leaders in business: Insights from our conversation with Kylie Walker, CEO at ATSE

As leaders look to AI to help solve innovation and productivity challenges in their business, it’s imperative for them to ground their decision making in a deep understanding of both the opportunities and the watch-outs with AI in the workplace. In the Humans & AI in the Workplace Podcast we dig into the complex dynamics of AI adoption and what leaders can do to get in front of the change that’s already happening.

In a recent episode of the podcast, Kylie Walker, CEO of the Australian Academy of Technological Sciences and Engineering (ATSE), shared insight into the role of ATSE and its mission to guide decision makers in leveraging science and technology to address intricate challenges around adopting AI. The discussion also spotlighted the release of the Responsible AI essay collection by ATSE and the Australian Institute for Machine Learning.

Here are some of our key takeaways from the conversation.

Empowering Leadership in AI Adoption

One of the central themes in our conversation with Kylie, was the imperative for business leaders to embrace agency in integrating AI within their organisations. She highlighted how important it is to understand both the opportunities and risks inherent in AI adoption as the pace of AI-driven change accelerates. Kylie also stressed the necessity for leaders to cultivate digital literacy and fluency to effectively navigate this evolving landscape.

Navigating the Impact on Jobs and Upskilling

While acknowledging the potential impact of AI on employment, Kylie also highlighted the opportunities AI presents for upskilling and career advancement.  During the conversation, Kylie noted that AI serves as a catalyst for innovation and efficiency across various sectors, requiring a proactive approach to workforce development.

Prioritising Responsible AI Implementation

Kylie emphasized the importance of approaching AI implementation with a sense of duty, advocating for inclusivity and responsible practices. This is a really important role for all leaders, as Inclusive AI development is vital to prevent the exclusion of marginalized populations, with a particular focus on identifying and mitigating the impact on key groups.

Fostering a Culture of Innovation and Inclusion

The conversation also underscored the value of leveraging the diverse skills and knowledge of employees to drive innovation. Respectful transitions for employees impacted by AI-driven changes are essential for maintaining a positive workplace culture. Kylie highlighted the resilience and resourcefulness of individuals as key assets in navigating technological transformations. Particularly in individuals sometimes overlooked because of their current circumstances or previous career choices.

Seizing Opportunities and Mitigating Risks

While discussing the myriad of opportunities afforded by AI, Kylie identified critical considerations, including privacy concerns and the need for robust data governance. Dr Debra Panipucci and Leisa Hart shared their experience, that stimulating curiosity and encouraging experimentation are key strategies for fostering a growth mindset within organisations, essential for navigating the complexities of AI implementation.

Conclusion: Charting a Course for the Future

As leaders grapple with the transformative potential of AI, Kylie’s insights serve as a roadmap for responsible and inclusive adoption. By prioritising digital literacy, fostering a culture of innovation, and embracing ethical considerations, organisations can harness the full potential of AI while mitigating risks and ensuring equitable outcomes for all. Through collaboration and proactive engagement, the promise of AI as a force for positive change can be realized, driving innovation and shaping a more inclusive, sustainable and prosperous future.

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Navigating Human Bottlenecks When Implementing AI: Key Strategies for Leaders

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.