What is explainable AI?

What is explainable AI? As artificial intelligence (AI) becomes increasingly embedded in corporate governance operations, its inner workings remain a mystery to many. 

This “black box” nature of AI systems can pose significant challenges, from regulatory compliance to maintaining stakeholder trust. Enter explainable AI (XAI), a transformative approach that demystifies how AI makes decisions. This guide explores what explainable AI is, why it matters, and what corporate leaders need to understand to harness its potential responsibly.

Explainable AI refers to a set of techniques and methods that make the operations of AI understandable to humans. 

This transparency is crucial for many stakeholders who feel outrun by the current pace of change in the AI world. Often, AI models’ results come without insight into how they were generated; XAI focuses on clarifying this decision-making process.

XAI achieves this through tools and frameworks that translate complex algorithms into interpretable elements. For instance, it can highlight which factors influenced a decision or assign a confidence score to an output. This transparency ensures that users, stakeholders, and regulators can comprehend and trust AI-driven processes, even when dealing with advanced systems like deep learning models.

Explainable AI is essential for bringing trust, compliance, and ethical accountability. 

This is especially important in industries like healthcare, finance, and law enforcement. Here, like anywhere else, AI can represent a huge step forward for operational capacity. However, decisions in these industries significantly impact people’s livelihoods; understanding AI’s reasoning can prevent errors and biases.

Moreover, regulatory frameworks like the EU’s AI Act increasingly demand transparency in AI systems. Organisations that fail to adopt XAI risk non-compliance, reputational damage, and financial penalties. Beyond legal obligations, explainable AI builds stakeholder trust by demonstrating that AI systems are fair, accountable, and aligned with organisational values.

Board members and executives should realise that explainable AI is not just a technical matter—it’s a strategic imperative. 

Leaders need to recognise the importance of explainable AI in strategic decisions and ensure that the workings of AI can be grasped at all levels of business. 

You don’t need to ensure everyone on your board is an AI wizard, but you do need to ensure they know the main points about any AI system the company depends on. 

Beyond that, it’s crucial for leaders to stay proactive about AI rules, what they’ll need to report, and when.

What is explainable AI? It represents the next frontier in ethical and practical artificial intelligence. Organisations can drive innovation by making AI systems transparent and understandable while upholding accountability and trust. For corporate leaders, embracing this is an opportunity to bridge the gap between technological complexity and stakeholder confidence. In an era where AI’s influence continues to grow, explainability is no longer optional—it’s essential for building a sustainable, responsible future.