Why AI maturity matters
AI is reshaping industries - enhancing efficiency, boosting innovation, and enabling better, faster decision-making. It’s helping organisations deliver cost savings, personalised services, and smarter operations.
But while AI’s potential is vast, scaling it successfully is a real challenge. Many organisations are still stuck in pilot mode or struggling to align AI efforts with broader business goals. That's where understanding your AI maturity comes in, it reveals not just how ready you are to scale, but also where you need to focus to do it responsibly and effectively.
A framework for responsible AI growth
To help build AI capability, we’ve developed an AI Maturity Framework, that assesses your organisation against six core pillars:
Against these six core pillars, we evaluate them against nine guiding principles that support long-term, responsible adoption.
Strategy and Governance: The foundation of AI Maturity
The first webinar spotlighted Strategy and Governance, arguably the two pillars that underpin everything else.
Strategy: Aligning AI to business goals
Ian explored the need for a clear, business-led AI strategy – one that connects AI investment to specific, measurable outcomes. He outlined how organisations can prioritise the right projects, identify high-value use cases, and set realistic roadmaps for scaling AI initiatives.
A common pitfall? Focusing on tools over outcomes. Strategy brings focus and the credibility needed to drive investment and momentum.
Governance: Building trust and managing risk
Andy shared the critical role governance plays in ensuring AI is adopted safely, ethically and at scale. He stressed the importance of having structured oversight for AI programmes and embedding ethics from day one.
From risk management to accountability and fairness, governance isn’t just about compliance, it’s about building AI systems people can trust. One practical example: implementing ethical review processes for sensitive use cases, like employee wellbeing or medical decision-making.
AI as an enabler, not a risk
The message was clear: AI isn’t something to fear or delay – it’s an enabler of smarter, more resilient organisations. With the right foundation in place, businesses can unlock their full potential.
Practical steps toward maturity
Gary laid out our thorough approach for assessing AI maturity, powered by AI, that delivers:
- Comprehensive evaluation of AI strengths and gaps across six key pillars
- Prioritised AI use cases aligned with business goals
- A strategic roadmap for ethical and sustainable AI implementation
- Clear alignment between AI initiatives and overall business strategy.
- Improved decision-making for AI investments and implementation
This approach gives the blueprint for long-term success with your AI transformation journey and ensures you’re driven by real business value, not technology for the sake of it.
Common barriers and how to overcome them
A recurring theme was the disconnect between executive ambition and operational readiness. A 2025 McKinsey report found that only 1% of companies have reached true AI maturity, despite 92% increasing their investment.
To bridge the gap, the speakers emphasised the importance of quick wins, clarity around governance, and building confidence by delivering measurable impact early.
Know where you stand
Understanding your organisation’s AI maturity is the first step to scaling it effectively and responsibly. Our AI Maturity self-assessment helps you do just that, giving you a clear view of your current strengths and areas to improve, and providing a tailored roadmap to guide your next steps.
It takes less than 10 minutes, and the insight is immediate.