Artificial Intelligence (AI) is reshaping industries and redefining human potential globally, but its impact is not without challenges. In this interview with OLUKOREDE YISHAU, Obianuju Anobili, a trained Lawyer and Houston-based expert in compliance and business risk management, sheds light on accountability and responsibility in the use of AI models, with insights drawn from her experiences in Nigeria, the United States, and other parts of the world.
How would you explain the growing influence of AI in today’s world, particularly in your areas of expertise?
AI is no longer a distant concept; it is now an essential driver of innovation across industries. It encompasses a wide range of disciplines, such as vision, perception, decision-making, and robotics, all of which enable machines to mimic or augment human capabilities. In compliance and business risk management, AI holds enormous promise. It can enhance decision-making processes, improve operational efficiency, and identify risks more effectively. For example, AI tools can analyze vast amounts of data in real time to detect financial fraud or monitor regulatory compliance in industries like banking and healthcare. However, alongside these benefits are significant responsibilities. The use of AI demands accountability because decisions made by these systems often affect individuals, businesses, and society at large. Governments and organizations are rightly focusing on the ethical, social, and economic implications of AI, ensuring its use aligns with privacy laws, equity principles, and human rights.
You have worked in both Nigeria and the United States. How do the challenges of AI adoption differ between these two countries?
The challenges differ mainly due to disparities in technological infrastructure, regulatory frameworks, and socioeconomic contexts. In the United States, AI adoption is advancing rapidly, fueled by well-established tech ecosystems and substantial investment in innovation. However, the challenge lies in creating robust governance frameworks that address issues like algorithmic bias, data privacy, and the ethical use of AI at scale. In Nigeria, AI adoption is still at an early stage, with limited resources and infrastructure. The country has immense potential to leverage AI for economic development—particularly in areas like agriculture, healthcare, and education—but faces barriers such as insufficient digital literacy, inadequate access to data, and weak regulatory enforcement. That said, Nigeria has a unique opportunity to learn from the experiences of more advanced economies. Policymakers and businesses can adopt proactive measures to build a robust enabling environment for AI. For example, investment in digital infrastructure, targeted education programs, and international partnerships will be essential for ensuring AI benefits all segments of society, especially underserved communities.
On the topic of underserved communities, AI raises concerns about inclusivity and equity. How can policymakers ensure that these technologies are accessible to everyone?
Inclusivity is a cornerstone of ethical AI. Policymakers must design frameworks that account for the diverse needs of different user groups, including marginalized communities, children, persons with disabilities, and indigenous populations. This starts with data inclusivity—ensuring that training datasets reflect the diversity of the population and are free from biases that could lead to discriminatory outcomes.
For instance, in Nigeria, AI models tailored to local contexts—such as language processing tools for indigenous languages or agricultural advisory systems for rural farmers—can significantly improve access and equity. Policymakers must also promote education and digital literacy, empowering individuals to use and benefit from AI technologies. At a global level, initiatives like the UN Sustainable Development Goals provide a roadmap for using AI to address societal challenges. However, these efforts must be localized to reflect the specific realities of different regions.
You have mentioned data privacy and protection as critical aspects of AI compliance. How do these issues play out in Nigeria and the U.S.?
Data privacy is central to AI governance because these systems rely heavily on data to function. In the United States, frameworks like the California Consumer Privacy Act (CCPA) and the Health Insurance Portability and Accountability Act (HIPAA) set clear guidelines for data usage and protection. However, the fragmented nature of U.S. privacy laws can make compliance complex, especially for businesses operating across multiple states. In Nigeria, data protection is governed by the Nigeria Data Protection Regulation (NDPR). While this regulation is a step in the right direction, enforcement remains a challenge due to limited resources and expertise. For example, many businesses lack the technical capacity to secure user data adequately, leaving systems vulnerable to breaches. To address these challenges, Nigeria must strengthen enforcement mechanisms, encourage public-private collaboration, and invest in training for data protection officers. Globally, harmonizing data privacy standards will be crucial, given the cross-border nature of AI technologies.
Bias in AI systems is another pressing concern. How can companies address this issue in their models?
Bias often stems from the data used to train AI systems, which can reflect historical inequalities or incomplete representations of certain groups. Companies must adopt a proactive approach to mitigate bias, starting with diversity in data collection.
For instance, when designing an AI-powered hiring tool, it’s essential to ensure the training data includes applicants from diverse backgrounds to avoid favoring one demographic over another. Additionally, companies should implement robust testing procedures to identify and rectify bias before deployment. Transparency is also critical. Explainable AI techniques—where the logic behind a system’s decisions is clear and interpretable—help build trust and accountability. In Nigeria, addressing bias may require cultural context. For example, AI systems used in healthcare should consider local disease patterns and demographic data to avoid skewed results. Across the globe, fostering interdisciplinary collaboration between technologists, ethicists, and social scientists will be key to ensuring fair and unbiased AI.
What role do international organizations play in fostering accountability in AI?
International organizations are vital for establishing global standards and encouraging collaboration. The United Nations, for example, has emphasized the role of AI in advancing sustainable development goals, but it has also highlighted the need for ethical guardrails.
Other bodies, such as the OECD and the European Union, have developed AI principles that promote transparency, human rights, and inclusivity. These frameworks serve as benchmarks for national policymakers and private-sector actors. However, there’s still a need for greater alignment across regions. AI often operates across borders, so fragmented regulations can create loopholes or inconsistencies. International cooperation—through forums like the G20 or bilateral partnerships—can help bridge these gaps. For countries like Nigeria, engaging in these global conversations ensures their unique perspectives and needs are reflected in emerging standards.
You’ve discussed compliance from a governance perspective. What about at the corporate level? How can businesses embed accountability into their AI practices?
At the corporate level, accountability begins with strong governance structures. Businesses should establish AI ethics committees or appoint Chief AI Officers responsible for overseeing ethical compliance. Regular audits and impact assessments are also crucial. These reviews help identify potential risks—such as bias, data breaches, or unintended consequences—and enable timely corrective action. Training is another key area. Employees involved in AI development and deployment must understand the ethical and compliance implications of their work. This includes training on privacy laws, anti-discrimination principles, and cybersecurity best practices. In Nigeria, where many companies are just beginning to explore AI, building a culture of accountability from the outset will pay long-term dividends. Partnering with local universities or international organizations can help bridge knowledge gaps and accelerate responsible adoption.
Finally, what does the future hold for AI compliance, and what advice would you give to stakeholders?
The future of AI compliance will likely involve more sophisticated tools and frameworks for monitoring and accountability. For example, advancements in explainable AI and model auditing technologies will make it easier to understand and regulate these systems. For policymakers, my advice is to adopt flexible, adaptive regulations that evolve with the technology. Over-regulation can stifle innovation, but under-regulation risks harm to society. For businesses, accountability should be embedded in every stage of the AI lifecycle—from development to deployment. Companies that prioritize ethical practices will not only avoid regulatory penalties but also gain a competitive edge by building trust with consumers and stakeholders. For individuals, digital literacy will be crucial. Whether as users, developers, or policymakers, we all have a role to play in shaping AI’s future. By staying informed and advocating for responsible practices, we can ensure AI serves humanity rather than the other way around.
Thank you, Ms. Anobili, for this comprehensive and insightful discussion. It’s clear that compliance and accountability are not just regulatory obligations but ethical imperatives in the age of AI.
Thank you for the opportunity. It’s been a pleasure to share my thoughts on this critical topic. Together, we can shape a future where AI drives progress while upholding our shared values.
