Before a company embarks on the AI implementation journey, it must develop a comprehensive, detailed strategy to guide its transition.
Specific change management processes are needed to usher in the adoption of Artificial Intelligence (AI) effectively. Regardless of the type of AI solution, training and employee buy-in are essential. The full benefits of AI can only be realized if the entire workforce utilizes the technology as planned.
The Necessity of Official Change Management for New AI Initiatives
Change can be unsettling. A Gartner1 study states, “73% of change-affected employees report experiencing moderate to high-stress levels.” This indicates that most people are naturally resistant to change and may hesitate to embrace innovations like AI.
This resistance poses a problem because, while leaders make the strategic decisions, the success of these changes often hinges on individual contributors. Therefore, a structured change management strategy is crucial for successfully implementing and adopting new technologies.
Organizational change management (OCM) is defined as “the process of guiding organizational change to a successful resolution.” It typically includes three major phases: preparation, implementation, and follow-through. Anytime an organization pursues a significant technological overhaul, like integrating AI into its digital ecosystem, OCM is necessary.
Companies can follow multiple well-established OCM methodologies and certifications. An effective OCM strategy is essential when implementing AI regardless of the specific model chosen.
Key Components of AI Change Management
1
Fostering Readiness and Positivity about AI
People naturally feel uncomfortable with change and may distrust new innovations. For AI adoption to succeed, it’s crucial to prepare the workforce adequately. This preparation involves more than merely notifying employees about the change; it means educating them on the necessity of AI and how it will benefit their roles.
Leaders must communicate how AI will streamline operations, reduce manual and repetitive tasks, and allow employees to impact customers significantly. Understanding that AI can be intimidating, especially to those not accustomed to digital tools, reassurance about adequate training and guidance through the transition period is vital.
Securing company-wide buy-in well before implementation is critical to successful AI change management.
2
Creating and Following a Detailed Implementation Roadmap
Creating a roadmap involves collaboration with all stakeholders and any involved vendors. This roadmap should:
- Set a realistic timeline and plan for AI adoption across the organization.
- Assign roles with specific tasks and responsibilities.
- Develop an in-depth training plan and schedule based on employees' levels of interaction with AI.
- Establish key performance indicators (KPIs) to measure the success of the AI platform or application by specific dates.
- Anticipate potential roadblocks and define contingency plans for these obstacles.
Once finalized, ensuring everyone understands the process and their roles at each onboarding stage prepares the organization for a smooth implementation process.
3
Ensuring Continued, Consistent Organizational Usage of AI
The shift to using new technology for tasks traditionally done manually won’t always be seamless. Leaders must anticipate resistance and implement strategies to prevent employees from reverting to old practices.
Ongoing education, motivation, and support are crucial. Incentive programs and other methods can help make AI utilization an expected norm across the organization.
4
Continuous Review and Analysis of AI Progress
The implementation process doesn’t end once the software is in place. Continuous analysis of the technology’s impact on the business is crucial to ensure the organization maximizes its AI investment. KPIs established in the implementation roadmap are essential as they provide objective measures of AI’s success and ROI. Regularly reviewing these metrics helps identify trends and areas for improvement.
By addressing these key components, mortgage lenders can effectively navigate AI implementation challenges, secure employee buy-in, and drive toward a successful digital transformation. This structured approach ensures that AI integrates seamlessly into the organization’s workflows and significantly enhances operational efficiency and customer satisfaction.
