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HR Leaders Priorities for 2024
Recently I participated in our company’s Change Leadership Community of Practice (CoP) bi-monthly session where we were reviewing and discussing the organizational change management trends for 2024. We reviewed several external sources as well as our own internal experiences. It was very informative and helpful to see the commonalities across clients, industries, and external sources like Gartner. The image is from Gartner and shows the Top 5 Priorities for HR Leaders in 2024. One of the reasons we wanted to bring this into our discussion was from an organizational change perspective. Over the years, I've seen the focus on organizational change and organizational change management be a concern for HR. Companies might centralize some things from an organizational change perspective for the organization as a function of HR and then may swing to distributing it among the business and then swing to centralize under operations or another function. Lately, I have not seen organizational change management being led by HR, but these top priorities are an indicator that it is on the minds of HR leaders. This makes sense to me because of all the changes that are going on today and the impact to people in the company in general. The complexity level and scale of change that's occurring needs to be a focus as it is tied to concerns like talent acquisition, talent retention, and upskilling talent.How can organizations identify and address employee resistance to change?
Change has always been a part of our journey in life personally and professionally, but it certainly has escalated over the last several years with no expectation that it will slow down. I have been managing change efforts for many years, but I am always interested in what the most current ways organizations can identify and address employee resistance to change.How can technology be used to support aspects of the change management process?
I am interested to learn about how technology can support the change management process end to end as I am engaging on a very large transformation effort for over 50,000 employees. How can technology be used to support aspects of the change management process?Measuring success of change management efforts
I am responsible for a Change Management Office (CMO) that partners with the PMO to ensure successful outcomes for all our initiatives. I would like to understand how we can better measure our change efforts success. How can organizations measure the success of their change management efforts?Key Organizational Change Management Consideration for Implementing AI
Implementing AI within your organization can offer incredible benefits, but it also involves significant change. We have all had transformational changes that not only impact process and technology, but impact people’s jobs, what they do, what skills they need, and restructuring. To ensure a smooth transition and maximize the potential of your AI efforts, consider these key organizational change management considerations: People and Culture: Leadership commitment: Secure strong buy-in and active support from leadership to champion the change, communicate effectively, and address concerns. Employee engagement:Involve employees early and often in the process.Address fears and uncertaintythrough clear communication,training,andopportunities to shape the implementation. Transparency and trust:Be transparent about how AI is being used,its limitations,and its impact on individuals and roles.Build trust by ensuring ethical development and use of AI. Reskilling and upskilling:Invest in training and support to equip employees with the skills needed to work alongside and adapt to AI-powered workflows. Change management strategy:Develop a structured approach to guide the change process,identifying stakeholders,potential challenges,and communication plans. Think back on your other large transformation efforts and pull the best of the best strategies forward. Process and Technology: Define clear goals and expectations:Clearly define what you want to achieve with AI and set realistic expectations for timelines and outcomes. Data readiness:Ensure high-quality,unbiased data is available to train and run AI models effectively.Address data governance and security concerns. Integration with existing systems:Plan for seamless integration of AI technology with existing IT infrastructure and workflows to avoid disruption. Governance and oversight:Establish clear ethical guidelines,accountability frameworks,and monitoring processes for responsible AI development and deployment. Communication and Feedback: Clear and consistent communication:Regularly communicate the purpose,benefits,and potential impact of AI to all stakeholders in a clear and consistent manner. Two-way communication channels:Establish open channels for employees to ask questions,express concerns,and provide feedback throughout the process. Address concerns proactively:Acknowledge and address employee concerns regarding job displacement,privacy,and algorithmic bias proactively. Celebrate successes:Share success stories and positive outcomes of AI implementation to build enthusiasm and momentum. Nothing helps people adopt better than knowing about how others are achieving success. Additional Considerations: Ethical considerations:Address ethical concerns surrounding data privacy,bias,and fairness in AI algorithms. Regulatory compliance:Ensure your AI implementation complies with relevant regulations and industry standards. Also, make sure you clearly communicate your company’s policies on using AI in their work. Agile approach:Be prepared to adapt and iterate your AI approach based on feedback,learnings,and evolving technology. By proactively addressing these considerations, you can create a more positive and effective transition to an AI-powered future for your organization. Remember, successful AI implementation is not just about the technology itself, but also about managing the human side of change effectively.Empowering Organizational Change for Successful Aurora Implementations
Navigate the complexities of adopting Aurora with our comprehensive organizational change services. We help businesses of all sizes optimize processes, transform workforces, and foster adoption essential for successful Aurora integration. Our team of experts possess deep platform knowledge and proven change management methodologies, ensuring a smooth transition and maximized value from your Aurora investment. How we can help you transition to Aurora: Strategy: Define essential behaviors, communications strategy, learning strategy, Change Advisor / Coach, and understand organization culture to improve success probability. Design & Plan: Design and plan change program (communications, engagement, and training), taxonomy, approach, customized delivery model, define messaging and essential behaviors/skills. Provide Aurora transition AI-infused technology with ChaMa templates for change impacts, plans, and assessments. Configure and train for client specific stakeholder audiences. Enablement: Execution support for the designed strategy and plan including stakeholder analysis, change impact assessment, stakeholder engagement, communications, training and office hours, readiness, and adoption. Let us collaborate with you as a trusted advisor to formulate your vision, design solutions for flexibility, advocate for you and your stakeholders. We are innovation driven and deliver speed, accountability, and transparency for your successful outcomes!What are the top questions for leaders that they should answer about AI use in their companies?
As AI continues to reshape industries, leaders across all departments need to carefully consider its implications. Here are some top questions they should answer: Strategic Impact: How will AI disrupt our industry and target market?Assess how competition is using AI,what products might become obsolete,and what new opportunities could emerge. Which areas of our business offer the highest potential for AI integration?Prioritize use cases like automating tasks,optimizing processes,or enhancing decision-making based on data analysis. What is our ethical framework for using AI?Define standards for responsible development,use,and data privacy to avoid potential harms. Implementation and Talent: What skills and resources do we need to integrate AI effectively?Evaluate current capabilities,identify any gaps,and plan for upskilling or hiring AI specialists. How will AI impact our workforce?Proactively address concerns about job displacement and equip employees to work alongside AI tools. What data governance processes do we need to ensure responsible AI use?Establish systems for data collection,storage,and access to prevent bias and maintain data security. Risk Management and Governance: What are the potential risks and limitations of using AI in our specific context?Consider areas like bias in algorithms, ability to explain decisions,and cybersecurity vulnerabilities. How will we monitor and evaluate the performance of our AI systems?Develop metrics and procedures to track progress,identify issues,and optimize outcomes. Who is responsible for overseeing AI projects and making key decisions?Define clear roles and accountability structures within the organization. Additionally: How will AI affect customer experience and interactions?Explore how AI can personalize communication,optimize marketing,or handle customer inquiries. How will AI change our internal communications and decision-making processes?Consider how AI can improve collaboration,data sharing,and strategic planning. How will we maintain transparency and build trust with stakeholders about our AI use?Communicate goals,address concerns,and demonstrate responsible implementation. Remember, these are just starting points. Leaders should tailor these questions to their specific industry, company goals, and risk tolerance. The key is to approach AI with strategic foresight, careful consideration, and a commitment to responsible implementation with a keen focus on how it will impact people.
