The rapid integration of artificial intelligence (AI) into organizations across diverse sectors is reshaping risk profiles, demanding risk professionals in these sector re-evaluate their risk management strategies and how they approach regulatory compliance and operational resilience. Retail, leisure and hospitality are among those sectors significantly impacted by AI.
To provide insights on how AI is influencing real business and what measures organizations can consider to navigate the risks and opportunities, below, we take a look at some practical perspectives drawn from a WTW retail, leisure and hospitality industries roundtable, held in spring 2024.
The importance of understanding the AI regulatory landscape
The regulatory framework surrounding AI is complex and varies by region. In the European Union, for example, the Forthcoming AI Act aims to regulate AI systems comprehensively, focusing on safety, transparency and accountability. This act categorizes AI systems based on their risk levels and imposes stricter requirements on high-risk applications. For businesses operating within the EU, this means ensuring AI systems are compliant with these new regulations, which could involve significant adjustments in how AI technologies are developed and deployed.
In contrast, the U.K. currently lacks specific AI legislation but is moving towards a principles-based, cross-sectoral approach to AI regulation. This approach will likely rely on existing sectoral laws to impose the necessary guardrails on AI systems. This means businesses, need to take a proactive stance to align AI practices, even before formal legislation is enacted.
The impact of AI on risk profiles and risk registers
AI technologies are set to transform traditional risk management practices.
Currently, risk registers in many organizations remain manually updated and often lag behind the rapid pace of change in business environments.
AI can automate and enhance risk registers, providing real time, dynamic risk assessments. This capability can allow businesses to respond more swiftly and effectively to emerging risks.
However, integrating AI into risk management processes also introduces new categories of risk, including ethical considerations, data privacy issues and the potential for AI-driven decisions to go awry
AI impact on business resilience and supply chain
AI can significantly enhance operational efficiency and business resilience. In supply chain management, AI-driven systems can optimize inventory levels, predict maintenance needs and identify potential disruptions before they occur.
However, this increased reliance on AI also introduces new vulnerabilities. For instance, AI systems are only as good as the data they process; inaccurate or biased data can lead to flawed decision making.
The interconnected nature of AI systems also mean a failure in one area can have cascading effects throughout the supply chain. Such exposures mean you need to regularly stress-test your AI systems against various scenarios to be assured they can withstand unexpected challenges.
AI and workforce risk management
The deployment of AI will inevitably lead to changes in the workforce. Automation of routine tasks can free up employees for more complex and creative work, potentially leading to greater job satisfaction and productivity.
However, there's also a risk of job displacement and organizations must manage this transition carefully to maintain workforce morale and avoid potential backlash.
