The Challenge

Like many large organisations, the client was experiencing rapid, uncoordinated adoption of AI-related tools, particularly generative and agentic AI, alongside increasing external pressure to understand how AI would impact:

• Education delivery and student experience

• Workforce skills and future course offerings

• Operational productivity and service quality

• Governance, ethics, and responsible use

AI was simultaneously seen as a major opportunity and a material risk.

Leadership needed a shared, evidence-based understanding of AI before making strategic decisions.

The Goal

The objective of the engagement was to provide a clear, practical AI Landscape that would:

• Create a shared understanding of what AI is (and is not)

• Illustrate how AI is already impacting education and key industry sectors

• Identify high-value AI use case opportunities across students, teaching, and operations

• Inform the development of AI governance, capability uplift, and future strategy

• Enable confident, responsible executive decision-making

This work was designed to inform strategy, not rush implementation.

Our Approach

We acted as an independent expert advisor, grounding the discussion in real-world applications rather than hype.

The work focused on three core areas:

1. Clarifying the AI Landscape

We established a clear, common language for AI, positioning it as a spectrum that includes:

• Traditional data analysis and reporting

• Advanced analytics and machine learning

• Generative AI across text, speech and images

• Agentic AI across processes, interactions and decision support

This helped stakeholders understand when AI is appropriate and when simpler approaches are more effective.

2. Education Sector Impacts

We explored how AI could transform:

• Student experience and engagement

• Teaching delivery and assessment

• Course design, administration, and compliance

Rather than abstract theory, the work illustrated practical, education-relevant use cases across the full student lifecycle.

3. Industry and Workforce Impacts

To support future-facing portfolio and skills planning, we analysed AI impacts across key employer sectors, including:

• Health and care

• Automotive

• Construction

This provided insight into:

• How roles and skills are likely to evolve

• Emerging capability needs for students and employers

• Where education providers need to adapt course offerings over time

The Solution

The engagement delivered a comprehensive AI Landscape view, including:

• A clear framework explaining AI maturity and application types

• A structured set of AI use case themes across:

  • Students and teaching

  • Education operations

  • Key employer industries

• Identification of capability and skills implications for staff and students

• Strategic inputs to support:

  • AI governance and guardrails

  • AI use case prioritisation

  • Skills development and workforce planning

Importantly, the work deliberately avoided locking the organisation into specific technologies, instead focusing on principles, opportunities, and readiness.

Results & Impact

The AI Landscape work delivered several critical outcomes:

• A shared, organisation-wide understanding of AI and its implications

• Reduced risk from unmanaged or ad hoc AI use

• Improved executive confidence in discussing AI opportunities and constraints

• Clear inputs into AI governance, skills development, and future strategy

• A stronger foundation for responsible, value-driven AI adoption

The organisation moved from reactive curiosity to a measured, informed, and strategic posture on AI.

Key Takeaway

AI strategy is not about chasing tools, it’s about understanding impact.

By grounding AI discussions in real use cases, sector context, and capability implications, the organisation was able to engage with AI thoughtfully, responsibly, and with a clear line of sight to long-term value.