AI Change Management

AI's Impact Across Industries

In applying the Prosci ADKAR Model to the AI Adoption webinar hosted by Prosci, 60% of the 679 respondents across industries said they expected significant disruption by generative AI. The most impacted industries were forecasted to be fintech, technology, banking, software and IT.

Prosci experts think that the amount of disruption across an industry depends on how the tasks overlap with AI’s features and capabilities. Even for the industries that are the least disruptable, AI would still make a significant disruption in their content-heavy tasks.

Applying ADKAR To AI Adoption Challenges: Real-Time Data

The four areas where AI can cause disruption are:

Industry disruption

AI affects industries differently, based on how well it can match up with the jobs that need doing. A recent report ranked industries by how much AI can automate their tasks. Industries like banking, insurance, software and capital markets have the highest risk of disruption. Sectors such as natural resources, chemicals, and consumer goods and services face less risk. However, even in the least affected sectors, companies will see changes, particularly in roles involving language tasks.

Organizational disruption

AI will disrupt organizations in various ways, driven by different goals. Some AI changes will focus on making current management processes more efficient, helping organizations and their employees perform better. Other changes will aim at growth, enabling the organization to reach new markets and opportunities. Finally, some changes will be transformational, pushing organizations to rethink their operations, services and value. These changes—aiming at efficiency, growth and transformation—often happen simultaneously and influence each other due to the interconnected nature of technology. Organizational leaders must prioritize these changes and decide which areas to focus on first.

Job disruption

The fear of job loss due to AI-powered tools is significant, yet an insightful perspective suggests that it's not about robots taking over jobs but rather individuals using AI to advance in their current roles.

Jobs evolve, so you must consider AI to make tasks more efficient. One example of jobs evolving is in agriculture and manufacturing becoming automated. A World Economic Forum report predicts a decline in roles like bank tellers and data-entry clerks due to digital advancements. Conversely, fields such as AI, sustainability, business intelligence and information security are on the rise.

Task disruption

You can’t deny AI's knack for making routine tasks quicker and less of a hassle. Employees can use AI tools to improve their productivity and quality of work, taking into consideration which daily or weekly tasks AI can assist with. This journey involves several learning phases: identifying complex tasks that AI can optimize, mastering the technology's interface for optimal results, and understanding appropriate versus inappropriate AI usage.

Change Successfully With Prosci Enterprise Training Arm stakeholders across your organization with role-based change management tactics and drive immediate results.

Current Use and Perspectives on AI Change Management

Drawing insights from over 200 change practitioners, the Artificial Intelligence and Change Management study by Prosci highlights the increasing integration of AI in change management. Approximately 48% of these professionals already incorporate AI tools into their change management practices.

Are You Currently Using AI Tools and Technologies in Your Change Management Practice?

Utilization of AI in change management

The areas below represent the top five reported by change practitioners using AI today, along with use cases and examples.

Communication support

Rewriting and refining messaging for different audiences
Ensuring proper tone and grammar
Tailoring content for specific communication channels

Example: Evaluate the CEO's tone in announcements for appropriateness with company-wide staff during a rebranding phase.

Content creation

Developing training materials and case studies
Drafting communications and presentations
Brainstorming creative ideas and formats

Example: Break down the complex topic of organizational restructuring into smaller, manageable segments for employees, focusing on individual roles and impacts.

Strategy and planning

Building comprehensive change management plans
Scenario planning and risk assessment
Aligning communications to strategy

Example: Provide real-time feedback on the proposed employee engagement strategy related to the new organizational structure and focus on its impact on team morale.

Automation and efficiency

Using chatbots for FAQs and stakeholder questions
Repurposing content across channels
Creating explanatory videos

Example: Create a chatbot to collect feedback on new HR policies and answer questions from department managers.

Data analysis

Surveying customers and analyzing feedback
Identifying themes and areas for improvement
Enabling customized messaging through segmentation

Example: Perform a thematic analysis of customer feedback on recent product launches to identify key themes in customer satisfaction and areas for improvement.

Common challenges in AI adoption in change management

A LinkedIn poll by a Prosci executive asked professionals how often they collaborate with AI, revealing that over 80% of respondents used AI in some form or another to improve productivity. Despite this informal finding, a Prosci research study on AI adoption in change management reveals challenges to adopting AI in the discipline.

These are five main reasons change practitioners avoid using AI, along with suggestions for overcoming those challenges:

Uncertainty and inexperience
Organizations should provide informative webinars and detailed use-case documentation highlighting AI benefits in change management.
Lack of relevant use cases
Developing and promoting AI tools with clear applications, such as AI for employee engagement, can provide direct solutions to the lack of use cases.
Limited access and resources
Companies can address this by allocating budgets for AI tools and forming dedicated AI support teams.
Knowledge gaps
Implementing training programs like AI workshops or online courses could demystify AI’s challenges.
Time constraints and lack of priorities
Developing efficient learning methods and setting clear priorities for AI integration can optimize time management for change practitioners.

Benefits and Opportunities in AI Change Management

Our experts view AI's role in change management as evolving, particularly in its impact on the daily tasks of change practitioners. The essence of change management is embodied in the process of preparing, equipping and supporting people through changes at work. This concept is the foundation for understanding AI's integration within this discipline.

What Impact have AI Tools and Technologies had on Your Change Management Work?

What Potential Opportunities Do You Foresee With AI and Change Management Practices Over the Next 2 Years?

Over the next two years, AI is poised to transform change management in several key areas. The Prosci Artificial Intelligence and Change Management study identifies several primary opportunities where AI could make a significant impact, as detailed below.

Communication enhancement

The most prominent opportunity, according to 29% of the change practitioners, is that AI can enhance the effectiveness of change communications. It can help generate content and offer new perspectives, which can help refine communications and engagement strategies. Change managers can then focus more on strategic implementation rather than content creation.

Organizational transformation

Accounting for 21% of responses, AI's potential to accelerate organizational change is noteworthy. AI can aid in adopting new technologies, thereby speeding up change processes. AI can help practitioners focus on critical thinking and interactions by managing repetitive tasks more efficiently and intellectually.

Administrative support

Voted by 16% of practitioners, AI can efficiently manage administrative tasks like communication handling, training invitations, and stakeholder data analysis. This automation liberates change management professionals to engage in more creative and strategic work.

Decision-making and governance

Predictive analytics, improved training methods, and data-driven insights can substantially improve the success rate of change adoption and tailor strategies based on stakeholder analysis.

Stakeholder engagement

AI tools can build stakeholder confidence and support change adoption. They draft communications, assess sentiments with real-time insights, and design tailored change interventions, helping create personalized support for stakeholders.

Virtual environments

With 4% indicating its potential, AI can create immersive training and scenario analysis environments. These AI-driven virtual platforms can provide realistic training for managing change resistance and enhancing stakeholder preparedness.

Crisis planning

In this smaller yet significant area, AI can assist in anticipating and mitigating resistance and failures in change implementations. This proactive approach in crisis planning enhances organizational resilience.

These findings suggest a cautious yet optimistic approach toward integrating AI change management. These tasks are geared towards "safe" AI applications.

Change practitioners are still steering away from the more controversial applications of AI, such as relying solely on AI for data-driven decisions over human judgment or using predictive models to forecast employee turnover during changes.

Challenges and Barriers in AI Adoption in Change Management

What Potential Concerns of Challenges Do You Foresee With AI and Change Management Practices Over the Next 2 Years?

Bringing AI into change management has its challenges. According to the Prosci AI and Change Management study, professionals face challenges in grasping AI, managing its use, and keeping up with how quickly change management practices need to evolve.

Key issues include:

Fear and lack of understanding
Fear stands in the way for many, especially about job roles and security, and reluctance to try new things. Nearly a third of professionals (29%) are wary of AI, making them hesitant to adopt it. Overcoming this fear means ramping up education and hosting workshops to boost AI understanding.
Governance and compliance
This presents a challenge for 22% of respondents. Addressing legal and ethical concerns involves establishing clear regulations and standardized AI ethics frameworks.
Slow evolution of AI in change practice
Noted by 16% of practitioners, the change management field's lagging adaptation to AI highlights the need for incorporating AI tools and change management frameworks to stay relevant.
Security and privacy concerns
Data privacy and security concers 13% of respondents. To adress this, organizations need to implement robust data protection protocols and advanced encryption.
Human aspect and job displacement
About 8% report feeling AI may lead to the loss of human touch in change management, and 10% worry about job losses. Emphasizing AI as a support tool and focusing on reskilling can address these issues.

Average Barrier Significance Rating
1 = No Barrier; 5 = Very Significant Barrier

This approach ensures that AI enhances rather than replaces human skills, addressing the human side of change thoughtfully and intentionally.

ADKAR barriers exist when an element scores a three or above. From the data above, the first ADKAR barrier to focus on in most cases remains Awareness.

The figure below shows some factors that drive and restrain AI Awareness:

In the “Applying ADKAR to AI Adoption Challenges” webinar, Prosci Chief Innovation Officer, Tim Creasey, recommends a multifaceted approach to overcoming resistance, emphasizing the importance of contextual and task-oriented training.

Instead of focusing solely on AI tool functionality, he suggests that people should integrate training with people's actual tasks, so it's practical and directly applicable.

Navigating the Future of AI Change Management

Organizations and enterprises should address the restraining forces by building Awareness of the need for change, reducing fears, and providing access to AI-powered tools and training. There’s no denying that disruption is underway, and applying AI in change management is happening and will only continue to grow. With this in mind, it’s time to embrace AI in change management to reap the benefits of a smoother, more efficient transition.