AI governance essential for responsible, secure adoption of technology: Saigol

LAHORE, Sep 01 (APP): Lahore Chamber of Commerce and Industry (LCCI) President Faheem Ur Rehman Saigol Tuesday chaired a training workshop on “Artificial Intelligence (AI) Governance: Principles, Ethics, Risks & Regulatory Readiness”, aimed at creating awareness among the business community about responsible AI adoption, governance frameworks, ethical considerations and emerging regulatory requirements.

The workshop featured a detailed presentation by Shakeel A. Mian, Founder and Executive Director, TechGov Intelligence, who highlighted the importance of establishing structured AI governance frameworks to ensure that artificial intelligence is deployed responsibly, securely and transparently. Executive Committee member Firdos Nisar, Convener Standing Committee on Coastal Maritime Atif Khan, Nadia Khan, Hamid Ullah Khan, Imran Haider, Ilyas Majeed, Uzma Nadeem, Naila Tanveer, Omer Fareed and Mehwish Addas also attended the workshop.

LCCI President Faheem Ur Rehman Saigol said that AI governance is essential for responsible, secure and transparent adoption of technology. He added, artificial intelligence was rapidly transforming the way businesses operate and had the potential to improve productivity, innovation, decision-making and competitiveness. He emphasized that the growing use of AI also required businesses to adopt responsible governance practices to ensure that technological advancement remained aligned with ethical standards, transparency and accountability.

He said the business community needed greater awareness of emerging AI regulations and international best practices so that Pakistani enterprises could adopt AI confidently while minimizing associated risks.

He stressed that effective AI governance should not be viewed merely as a regulatory requirement but as an essential part of sustainable digital transformation. He highlighted the importance of human oversight, data protection, cybersecurity, transparency and continuous monitoring in building trust in AI systems.

The LCCI President said that such training sessions were important for preparing the business community for the rapidly evolving digital economy and expressed the hope that greater understanding of AI governance would help businesses harness the technology responsibly while remaining competitive in international markets.

Shakeel A. Mian said that effective AI governance required clear accountability, risk-based management, transparency, explainability and alignment with international regulatory frameworks. He emphasized that structured governance was essential for enabling businesses and institutions to adopt AI while controlling associated risks. He explained that accountability remained a fundamental principle of AI governance, with defined ownership required throughout the AI lifecycle. Board and management oversight, clear responsibility for AI-driven decisions and failures, and audit and compliance mechanisms were necessary because AI systems themselves could not be held accountable and ultimate responsibility must remain with humans.

The presentation highlighted a risk-based approach to AI management, categorizing systems into prohibited, high-risk, limited-risk and minimal-risk applications. It was emphasized that higher-risk AI systems required stronger controls, monitoring and regulatory safeguards. Human oversight was identified as another critical component of responsible AI governance. The workshop stressed the importance of human-in-the-loop mechanisms, intervention and override capabilities, escalation procedures and continuous supervision, particularly where AI systems were involved in critical decisions.

The speaker also highlighted the importance of data governance, including data quality, accuracy, privacy, data minimization, purpose limitation, data ownership and traceability. They observed that reliable data was essential for producing reliable AI outcomes.

The workshop further covered model transparency and explainability, with participants briefed on the need to understand an AI system’s purpose, logic, limitations, assumptions and input-output relationships. Explainable AI, it was noted, improved user confidence, facilitates audits and supports regulatory compliance.

Special attention was given to bias monitoring and fairness.

The presentation identified discriminatory outputs, data-driven bias and unfair decision-making as key risks, stressing the need for bias testing, fairness validation and continuous monitoring to ensure ethical and non-discriminatory AI systems. Cybersecurity and protection of AI systems and data were also discussed in detail. The speaker emphasized the need for IT and access controls, data protection, model robustness and cybersecurity safeguards to ensure trustworthy AI deployment. The importance of auditability and traceability was highlighted, including logging AI activities, maintaining traceable outputs, version control and evidence of compliance. The workshop was informed that systems that could not be properly audited would be difficult to trust and govern.

Shakeel A. Mian also discussed continuous monitoring and model drift detection, explaining that AI models could lose accuracy or effectiveness over time. Performance tracking, revalidation cycles and regular accuracy checks were therefore necessary to maintain reliable AI systems. The session also covered incident response mechanisms for AI failures, including detection, escalation, investigation, remediation and reporting. Access and permission controls were identified as another important safeguard, with role-based access, data restrictions, approval hierarchies and usage monitoring helping to reduce risk exposure.