An AI Literacy Audit For Senior Leadership with Simon Hodgkins Ep 278 - The Global Discussion

Welcome to the global discussion. Today I want to talk a little bit about AI in Ireland because AI here in Ireland has entered, I suppose, the operational era. The conversation around AI has shifted decisively. It's no longer about exploration or experimentation. It's becoming more and more about execution. There was a recent study, the AI Ireland 2026 report, it was based on insights from 130 artificial intelligence leaders across many Irish organisations. The report itself, it makes one point really clear. AI is now embedded in business operations. The strategic question is no longer whether to adopt AI, obviously it's to figure out how you scale it responsibly, how you scale it effectively. This is a critical inflection point. I think it's the same point for many places that are heavily using artificial intelligence. It's an important point for leadership teams. AI is now in production, at least in this report, in 74% of organisations that were surveyed. They've moved into AI, they've moved into early production or even broad adoption. Only 2% have not yet started their AI journey. This level of adoption signals maturity and intent and AI initiatives are no longer isolated pilots run by innovation teams or a couple of people in an organisation. They're becoming part of core systems, workflows and operational models. However, production does not equal optimisation and many organisations are still navigating the transition from proof of concept to measurable business value. Efficiency is the primary strategic driver when people are asked about priorities for the next six to 12 months and the leaders overwhelmingly pointed to cost optimization. It was a 27.7% I think. Engineering assistants followed this at around the 20% market, it was 19.2, particularly in coal generation and productivity enhancement. So predictive maintenance actually ranked third at only 15.4%. The signal is clear, AI is being deployed as an efficiency lever. This is a very pragmatic approach in a climate where boards demand measurable returns. AI investments now have to demonstrate financial discipline, operational efficiency, improved productivity and proactive maintenance provide tangible, defensible return on investment. Yet there's also a strategic opportunity. Once efficiency gains are realised, organisations can reinvest AI capability into innovation, into product development, customer experience, transformation. Integration is the primary constraint, the most significant blocker that was identified by leaders. It's integration challenges. It was cited by 24.6% of respondents. The system's fragmented infrastructure and technical debt are slowing the progress. This finding is somewhat instructive. The barrier is not ambition or appetite. It certainly isn't that. It seems to be architecture. AI cannot operate effectively in isolation. It depends on clean data flows, interoperable systems, scalable infrastructure. Without foundational readiness, even the most advanced models fail to deliver some of the sustained value that we are searching for. So for executives and teams, this reframes the investment conversation. AI budgets must include modernisation, integration capability and infrastructure upgrades. Otherwise, initiative risks becoming a disconnected pilot rather than an enterprise level solution. The skills and literacy gap and resource shortages account for 15.3% of reported blockers. And importantly, this number extends beyond technical teams. So the report highlights the need for improved AI literacy at the leadership level. Strategic clarity begins at the top. So without a shared understanding of AI's capabilities, risks and limitations, organisations are struggling or were struggle to prioritise use cases or allocate capital more effectively. So the recommendation to conduct a senior leadership team audit on AI literacy, I think is particularly relevant. AI adoption is not solely a technical programme. It's actually more of a leadership mandate. And when I think about governance and controlled use, they're becoming standard. And I mean, on the question of generative AI with private company data, over half 56.2% of leaders favour a controlled use model. And this indicates a structured approach to risk management, sandbox environments, formal guidelines and compliance alignment are becoming standard practice. Now, only 15% describe themselves as fully production ready and trusting generative AI systems. And this caution reflects a growing awareness of regulatory expectations, security concerns and reputational implications of misuse. Governance, thankfully, it's not a secondary consideration, which it may have been in the more hyped areas. It's becoming central to AI strategy, something we've been working very hard on. And the report emphasises ISO 42.1, that certification is known to people in AI, a lot of companies are looking at it. And the regulatory alignment reinforces this shift. So when we think about the shift towards proactive operations and looking at the 90 day outlook leaders, prioritise, leaders prioritize proactive operations and predictive alerts at 25%, alongside cost optimization at 25%. And this demonstrates, I think, an evolution from reactive to predictive business models. AI is positioned as an early warning system, identifying risks in efficiencies and operational issues. AI is somewhat being positioned as an early warning system, identifying risks in efficiencies and operational issues before they escalate. This capability has direct implications for resilience, uptime, financial performance, and the organisations that fully operationalise predictive intelligence will probably gain much more structural advantages in speed and responsiveness. The report identifies a readiness gap. And while 41% are in early production, many organisations struggle with integration, complexity and skill shortage. The gap is not about a belief in AI's potential, it's about execution capability and closing this gap requires deliberate action, prioritising technical integration before scaling initiatives, appointing, certainly appointing executive level AI sponsors, defining clear commercial objectives by mapping data lineage and infrastructure readiness, and ensuring secure sandbox environments, transitioning pilots to production, only when measurable value is demonstrated. So launching structured upskilling programs, these are operational disciplines that are required. They're not necessarily just innovation, slow goals or nice to have. So we then enterprise influence and market implications over 43% of respondents represent organisations between a thousand to five thousand employees. So larger enterprises are currently shaping the AI narrative, at least in the context of Ireland and this report. So their scale, their complexity and resources naturally drive a structured adoption. However, this also presents opportunity. A smaller mid-sized organisations often carry less burden, often carry less legacy systems, and may have the agility to move much faster once governance and integration frameworks become clarified. The competitive landscape, it's still forming, and from a strategic outlook, AI in Ireland has moved beyond experimentation. It's entering a discipline governance driven phase of operationalization. The defining capabilities for 2026 will not be experimentation or enthusiasm. There'll probably be infrastructure readiness. When it comes to leadership, literacy, governance maturity, measurable ROI discipline around AI, it's not a peripheral innovation agenda. It's part of the enterprise architecture. The organisation has treated us such structured, integrated and certainly strategic airline. They're going to be best positioned to convert adoption into sustained competitive advantage. The question for executive teams is not whether AI matters. It's whether their organisation is now structurally prepared to lead with it. I hope that's been thoughtful. I hope it's made you think about a few different things. I hope you'll join me back here for some more conversations on the global discussion. Thank you.