AI Business Value Realization: From an IT Project to Continuous Transformation

In today's rapidly evolving business landscape, the journey of AI value realization is a critical topic for organizations aiming to stay competitive. It's essential to understand that this journey begins as an IT project but evolves into a continuous transformation that requires change agility. This article explores the stages of this journey and highlights the importance of change agility, distinguishing it from traditional change management.

Starting as an IT Project

The AI value realization journey typically begins with a well-defined IT project. During this initial phase, organizations focus on planning and setup, involving a small number of users in a pilot program. The primary objectives are to ensure security, privacy, and governance approvals, establish an AI Center of Excellence (CoE), and identify high-value use cases. This phase has a clear start and end date, with IT leading the efforts.

Transitioning to Personal Productivity

As the project progresses, the focus shifts to personal productivity gains. This phase involves a major rollout, where general AI skills training and core prompts like meeting recaps and email summarization are emphasized. The goal is to inspire quick wins and reach a value tipping point, measured by usage and time savings. While IT continues to play a significant role, strong involvement from the organization's change management team is crucial. This phase also has a clear start and end date.

Extending to Business Processes

The next stage involves extending AI capabilities into business processes. This includes custom integrated workflows and role-based processes, with Copilot agents playing a key role. The success of this phase is measured by key performance indicators (KPIs) such as leads pursued for sales or candidates interviewed. Advanced reporting with tools like Viva Insights helps track business outcomes. Unlike the previous phases, this stage does not have a clear start and end date, marking the beginning of continuous transformation.

Achieving Organizational Value

The final stage of the AI value realization journey is achieving organizational value. This phase is characterized by continuous and unceasing change agility. Organizations must adopt a flexible and experimental approach to navigate the complexities and opportunities AI presents. This mindset shift from traditional change management to change agility is crucial for success.

Change Agility vs. Change Management

Traditional change management is a structured process designed to lead organizations through well-defined transitions. It involves developing strategies, tools, and techniques to manage the people side of change, ensuring a smooth, controlled transition. However, in the era of AI, where disruption is constant, this approach is no longer sufficient.

Change agility, as described by The Josh Bersin Company , is about cultivating the mindset and organizational readiness to anticipate, adapt, and respond to ongoing, rapid changes. It's not about handling a single transition but maintaining flexibility in a constantly evolving landscape. Change agility emphasizes continuous, bottom-up, employee-driven adaptation, focusing on people and effectiveness rather than just business efficiency.

For those that are familiar with Adaptive management, it is inherently interconnected to change agility, as both emphasize a responsive and flexible approach to navigating complex and dynamic environments. Adaptive management, often used in natural resource management and organizational strategy, involves continuously learning from outcomes and making iterative adjustments to improve performance over time. This approach aligns seamlessly with change agility, which requires organizations to perpetually adjust and respond to the rapidly evolving landscape of AI. By integrating adaptive management principles, organizations can enhance their change agility, ensuring that they remain resilient and capable of thriving amidst constant disruption. This symbiotic relationship fosters a proactive culture that prioritizes learning, experimentation, and adaptability, ultimately driving long-term success in AI adoption and beyond.

The AI value realization journey is a dynamic process that starts as an IT project but evolves into a continuous transformation requiring change agility. By embracing change agility, organizations can navigate the complexities of AI adoption and achieve sustainable value. This approach ensures that AI transformation is not static but an evolving target that requires active involvement from AI users and a flexible, experimental mindset.