For one of our clients, we were engaged to assist them in “taking greater advantage of AI.” As is customary, we proposed conducting a diagnosis as the initial step, based on our philosophy that sound recommendations can only follow a thorough understanding of the actual issue—rather than merely addressing a perceived one.
In this case, the perceived issue revolved around the client’s inability to leverage AI effectively due to “technical debt” and outdated infrastructure. However, our detailed analysis revealed a different underlying problem: an organisational identity issue.
The Challenge
The client’s organisation was a hybrid entity, functioning partly as a vertical organisation and partly as a process-driven enterprise. While this might seem innovative on the surface, it posed significant challenges for their ability to embrace AI. Here’s why this dual structure was problematic:
- The organisation failed to fully capitalise on the benefits of either a vertical or a process-driven model.
- Tensions arose between line managers and process owners, as overlapping responsibilities led to conflicts.
- There was ambiguity surrounding key responsibilities, such as who should take ownership of designing and implementing an AI strategy—heads of business units or innovation process owners.
- Ultimately, the incoherent structure stifled the organisation’s ability to seize new opportunities, including adopting AI technologies.
The Approach
Recognising that the core issue was structural, we shifted our focus from addressing technical debt to helping the organisation redesign its operating model. Our process included the following steps:
- Stakeholder Engagement: We conducted workshops with leaders across both vertical and process-driven elements to understand their roles, pain points, and perspectives.
- Structural Diagnosis: Using our analytical framework, we assessed the organisation’s structure, identifying misalignments and bottlenecks.
- Proposed Model: We collaborated with the client to design a fit-for-purpose operating model that would enable coherence, alignment, and adaptability.
The Transformation
The redesigned model provided clear delineations of responsibilities. Vertical structures were retained for accountability and control, while process-driven approaches were integrated to promote cross-functional collaboration and agility. Governance mechanisms were introduced to resolve conflicts between line managers and process owners, ensuring alignment in strategic decision-making.
We also assisted the organisation in establishing a dedicated AI Strategy Team with representatives from both structures. This team would oversee the development and execution of the AI roadmap, ensuring all efforts were cohesive and aligned with broader business objectives.
The Impact
While the initial aim was to help the organisation leverage AI, the broader impact of this project was transformative. By addressing their structural challenges, the client positioned themselves to embrace not just AI but other innovations as well. The improved operating model fostered clarity, collaboration, and strategic focus.
As anticipated, with the foundational issues resolved, the client began identifying AI applications and implementing solutions independently. This reaffirmed our belief that a well-structured organisation naturally finds its way to success.
Conclusion
This case highlights the importance of diagnosing the true problem before proposing solutions. By addressing their identity issue, the organisation gained the clarity and coherence needed to unlock the full potential of AI—and beyond.