www . refrigerationandaircon . co . za RACA Journal I November 2024 39
Contributor
• Automation and job displacement : AI-driven automation can lead to the displacement of workers who perform routine maintenance , monitoring , and management tasks , necessitating retraining and potentially leading to unemployment . Not what we want to hear in Africa .
• Skill gap : The shift towards AI-driven systems requires new skills , and there may be a gap between the skills of the current workforce and the needs of AI-integrated operations . Also not something we want to hear in Africa .
• Data security : The vast amount of data collected by AI systems can be vulnerable to breaches , risking the exposure of sensitive information about plant operations and employee activities .
• Surveillance : Increased use of AI in security and monitoring can lead to enhanced surveillance , raising ethical concerns about privacy and worker autonomy .
• Decision-making authority : The delegation of decisionmaking to AI systems raises ethical questions about accountability and the appropriate level of human oversight .
• Impact on quality of life : While AI can improve efficiency and safety , it can also contribute to a high-stress environment if not implemented thoughtfully , particularly if it leads to job insecurity or increased surveillance .
• Broader societal impacts : There are also broader societal impacts to consider such as potential long-term dependence on technology , reduced human expertise , stifling of innovation and flexibility , and significant shifts in workforce requirements .
Operational risks
• System failures : Dependence on AI systems increases the risk of significant disruptions if the AI system fails or malfunctions . Redundant systems and fail-safes are critical to mitigate this risk .
• Cybersecurity threats : AI systems can be targets for cyber-attacks , potentially leading to data theft , operational disruptions , or safety incidents .
• Integration challenges : Integrating AI into existing BMS infrastructure can be complex and costly , with risks of operational disruptions during the transition period .
• Interoperability issues : Ensuring that AI systems work seamlessly with various components of the BMS and other plant systems is critical to avoid inefficiencies or failures .
• Dependence on data quality : AI systems require highquality , accurate data to function effectively . Poor data quality can lead to incorrect predictions or decisions .
• Continuous monitoring and updating : AI systems need regular updates and monitoring to ensure that they adapt to new conditions and continue functioning correctly . Neglecting this can result in outdated or ineffective AI models .
• Integration with legacy systems : Many existing HVAC systems may not be compatible with AI technologies , requiring significant upgrades or replacements .
• Skill requirements : The integration of AI into HVAC design and operation requires new skills in data science , machine learning , and software management for engineers and technicians .
Regulatory compliance
• Validation and oversight : Ensuring that AI systems comply with stringent regulatory requirements is complex . Failure to do so can result in non-compliance penalties , recalls , or other regulatory actions .
• Bias and transparency : AI decision-making processes must
b . be transparent and free from bias . In the pharmaceutical industry , biased decisions can lead to product quality issues or unjustified deviations from standard procedures . Mitigation strategies
• Human-in-the-loop systems : Ensuring human oversight , decision making and intervention capabilities .
• Robust cybersecurity measures : Implementing strong cybersecurity protocols to protect against breaches and cyber-attacks .
• Regulatory collaboration : Working closely with regulatory bodies to ensure compliance and ethical standards .
• Continuous training : Providing ongoing training for employees to adapt to new AI systems and technologies .
AI and fully integrated smart building technologies are transforming BMS in pharmaceutical plants by enhancing design , operational efficiency , safety , compliance , and environmental sustainability . These systems leverage AI , IoT , and advanced automation to create not only more efficient but also more sustainable and eco-friendly environments . While offering significant benefits , these technologies also present challenges that require careful management and mitigation strategies . RACA
“ It is disturbing to see how often we go back to these sites after handover and find that the client has turned the BMS computer off and shut the door .”
www . refrigerationandaircon . co . za RACA Journal I November 2024 39