LAHORE (Special Correspondent) – President of the Lahore Chamber of Commerce and Industry (LCCI) Faheem Ur Rehman Saigol chaired a comprehensive training workshop titled “Artificial Intelligence (AI) Governance: Principles, Ethics, Risks & Regulatory Readiness,” aimed at sensitizing the business community to responsible AI adoption, governance frameworks, and emerging regulatory mandates. The workshop featured a detailed presentation by Shakeel A. Mian, Founder and Executive Director of TechGov Intelligence, who emphasized the necessity of structured governance to ensure AI is deployed securely, ethically, and transparently.

Attendees at the session included LCCI Executive Committee member Firdos Nisar, Convener Standing Committee on Coastal Maritime Atif Khan, as well as Nadia Khan, Hamid Ullah Khan, Imran Haider, Ilyas Majeed, Uzma Nadeem, Naila Tanveer, Omer Fareed, and Mehwish Addas.

Strategic Integration of AI in Business

LCCI President Faheem Ur Rehman Saigol stated that artificial intelligence is rapidly reshaping industrial operations, offering significant potential to enhance productivity, innovation, and decision-making. He noted that as businesses transition into the digital era, they must align technological advancements with accountability and ethical standards. Saigol underscored that the business community requires a deeper understanding of both domestic and international regulatory landscapes to adopt AI confidently while mitigating operational risks.

He described effective AI governance as a fundamental pillar of sustainable digital transformation rather than merely a regulatory obligation. He stressed that maintaining trust in autonomous systems requires robust human oversight, stringent data protection, cybersecurity measures, and continuous monitoring. Saigol expressed optimism that such professional training would empower local enterprises to harness technology effectively, maintaining their competitive edge in global markets.

Core Principles of AI Accountability

Shakeel A. Mian outlined the essential components of AI governance, identifying accountability, risk-based management, and model explainability as critical pillars. He noted that because AI systems themselves lack legal accountability, the responsibility for AI-driven outcomes must remain firmly with human operators and management boards. Effective governance, he argued, requires clearly defined ownership throughout the AI lifecycle, coupled with rigorous audit and compliance mechanisms.

The session introduced a risk-based categorization model for AI, classifying systems into prohibited, high-risk, limited-risk, and minimal-risk applications. Mian emphasized that high-risk deployments necessitate enhanced regulatory safeguards and human intervention protocols. The discussion also addressed data governance—covering data quality, privacy, and traceability—as the foundation for reliable AI performance.

Ethics, Bias, and Continuous Oversight

Addressing the risks of data-driven bias and discriminatory outputs, the workshop highlighted the importance of fairness validation and bias testing. Mian stressed that for AI to be ethical and non-discriminatory, businesses must implement continuous monitoring to identify model drift, where AI effectiveness may decline over time. The session also covered cybersecurity, emphasizing the need for robust IT controls, access restrictions, and incident response mechanisms to address system failures.

Participants were briefed on the necessity of ‘explainable AI,’ which improves user confidence and simplifies the audit process. Mian concluded that systems lacking transparency and auditability pose significant governance challenges. By enforcing version control, activity logging, and approval hierarchies, companies can successfully minimize risk exposure while fostering a culture of technological innovation. This session aligns with ongoing efforts to modernize Pakistan’s business environment, similar to initiatives aimed at enhancing organizational efficiency such as those discussed in recent developments at the MCI or the strategic oversight seen in other sectors, including the CDA operations or PIMS safety protocols.