The discussion also underscored the importance of cost considerations, governance, and continuous learning as organisations adapt AI to strengthen their resilience.
In the subsequent two postings, we will summarise the speaker's presentation.
Dr. Goh Moh Heng moderated the session, drawing out essential questions from the audience, while Michael Nieman addressed them with insights from his experience.
One of the most common questions raised was whether the traditional seven pillars of BCM need to be modified to reflect the growing role of AI. Dr. Goh reassured participants that the fundamentals of business continuity remain unchanged.
The established planning methodologies continue to apply; however, AI can significantly enhance efficiency in areas such as conducting Business Impact Analyses or compiling recovery strategies.
Michael added that AI itself should be treated as an asset that must be recoverable under IT disaster recovery plans, but it also has the potential to strengthen BCM by detecting patterns in system logs or identifying dependencies that humans may overlook.
The session also explored the challenges faced by small and medium enterprises (SMEs). A participant asked whether advanced AI safeguards, such as real-time monitoring, were practical or financially feasible for smaller organisations. Michael acknowledged that cost is a major factor.
For large organisations, building dedicated AI systems with in-house controls may be possible. Still, SMEs may find more value in adopting AI as a service from providers that have already embedded governance, monitoring, and security safeguards.
This approach strikes a balance between affordability and resilience, while maintaining accountability.
Another concern revolved around AI chatbots and customer service. Participants reflected on high-profile incidents, such as Air Canada’s chatbot providing misleading information, which led to reputational damage and financial loss.
Michael noted that while chatbots can handle routine queries, they must be designed with clear escalation paths to human support when the AI is unable to provide accurate responses. He described practical examples where AI agents hand over conversations to human advisors through messaging platforms, ensuring customers still receive reliable service.
Dr. Goh reinforced this by highlighting that automation must always be complemented by human oversight, particularly in customer-facing contexts where trust and empathy are most crucial.
Throughout the discussion, both speakers returned to a central theme: the importance of keeping humans in the loop. AI can monitor, process, and detect anomalies at extraordinary speed, but decision-making must remain with people.
As Dr. Goh reminded participants, AI is here to stay. Still, the only sustainable way forward is to embrace it responsibly, contextualise it for organisational needs, and keep investing in continuous learning.
BCM Foundations Stay Relevant: AI Enhances but Does Not Replace Established BCM Methodologies.
AI Itself Needs Continuity Planning: Treat AI as a critical asset that must be recoverable, just like other IT systems.
SMEs Can Leverage AI as a Service: Smaller organisations may benefit from third-party solutions that already embed safeguards, keeping costs manageable.
Human Oversight Protects Reputation: Customer-facing AI must escalate complex queries to humans to avoid misinformation and reputational risks.
Continuous Learning is Essential: AI evolves rapidly; staying updated and contextualising AI to your organisation is key to long-term success.
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