Case Study — Building Shared Leadership Understanding of AI
- orrconsultingltd
- Jan 30
- 3 min read
1. Organisational Problem - Lack of Shared Leadership Understanding of AI
Many organisations are now experimenting with AI tools, but leadership conversations often reveal a surprising problem: everyone is talking about AI, yet few people mean the same thing.
This illustrative case study reflects a common situation organisations face when beginning their AI transformation journey.
In the Orr Consulting AI Transformation Process, this case study illustrates the Discover stage — helping organisations establish shared understanding before exploring AI opportunities and investment.
2. Situation
A UK-based recruitment and talent advisory firm had begun exploring artificial intelligence through a mixture of vendor capabilities and small-scale experimentation with generative AI tools.
Interest in AI was growing rapidly across the organisation. Board members were asking about strategic opportunities, while different departments were beginning to test tools that promised productivity gains or automation benefits.
However, leadership discussions about AI were becoming increasingly confused.
Different teams were using the term AI to describe very different things. Some were referring to generative AI tools such as ChatGPT or Copilot. Others were discussing automation, analytics or vendor systems that claimed to include AI capabilities.
As a result, conversations about AI were becoming fragmented and unproductive. Expectations were diverging, terminology was inconsistent and it was becoming difficult to have clear strategic discussions about how the organisation should approach AI.
The board recognised that before further pilots or investment were considered, the leadership team needed a shared understanding of what AI actually meant in practice.
3. Background
The organisation operated across several UK locations with a well-established digital and client service environment.
Several existing software platforms already included AI-driven capabilities such as forecasting tools and automated workflow functions. At the same time, individual teams had begun experimenting with generative AI tools for tasks such as drafting candidate communications, summarising CVs and role profiles, and preparing client-facing materials.
While these early experiments were promising, they were happening without a consistent framework for understanding AI capability, benefits or risk, particularly where AI might influence candidate communications, screening or evaluation.
The organisation had effectively entered what one executive described as a “Tower of Babel” moment, where everyone was talking about AI but using different language and assumptions.
4. Action Taken
In situations like this, Orr Consulting typically recommends starting with a focused programme of AI education and leadership awareness before further AI initiatives are pursued.
The objective is not to make leaders technical specialists, but to help leadership teams develop a shared understanding of AI capability, benefits and risk.
A typical session would introduce three core concepts:
The AI Universe, explaining the main AI capability types and the organisational questions they help answer
Common AI use cases, illustrating where these capabilities are already delivering benefits in practice
The AI Transformation Process, outlining a structured approach to adopting AI safely and effectively
The goal is to establish a shared vocabulary and mental model so that leadership discussions about AI become clearer, more realistic and more productive.
5. Likely Outcomes
When organisations take this approach, leadership discussions about AI typically become significantly more constructive.
Leadership teams develop:
a shared vocabulary for discussing AI capabilities
a clearer understanding of where AI could realistically create benefits
greater awareness of potential risks and governance considerations
alignment around the need for a structured approach to AI adoption
Instead of fragmented experimentation, conversations begin to focus on how AI can be explored deliberately and responsibly.
6. Recommended Next Steps
With leadership now aligned around a shared understanding of AI capability, benefits and risk, the organisation is in a much stronger position to move into the next stage of the Orr Consulting AI Transformation Process.
A common next step is to perform an AI Capability and Maturity Assessment to understand:
current AI capability across the organisation
existing governance and data foundations
areas requiring development before scaling AI initiatives
Establishing this baseline enables organisations to prioritise AI opportunities more effectively and move forward with confidence that future initiatives are grounded in capability, readiness and measurable benefits.
7. Final Thoughts
This Case Study is part of the Orr Consulting AI Insights Library — structured thinking for AI transformation leaders and decision makers.
If your organisation is beginning to explore AI and would benefit from leadership alignment, capability assessment or structured use case discovery, we would be happy to discuss your next AI steps.
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