Lauretta Onwuegbuzie, and Victoria Adaramola

Introduction  

In the past few years, Artificial Intelligence (AI) has developed rapidly, permeating many sectors. This has necessitated the need for governance as countries and corporations navigate ways to regulate the use, development, and deployment of AI. The July Edition of the Hive Pulse Point on From Policy to Practice: Operationalising AI Governance Frameworks examined the complex challenges and opportunities around AI governance, emphasising the need for organisational agility, AI literacy, and compliance with existing regulatory frameworks such as data protection, consumer protection, and risk management, amongst others.

Understanding AI Governance and Why it Matters for Organisations

The importance of AI governance is highlighted by the impact of daily use of the technology for various activities. For example, smart household devices, health monitoring systems, predictive algorithms, and so on. As these systems grow more autonomous and complex, the potential risks, including data misuse, algorithmic bias, and possible privacy violations, underscore the urgent need for robust governance structures that safeguard ethical standards, privacy, and accountability in the use of AI. Given this reality, organisations must now find ways to govern AI, ensuring that it is used ethically and responsibly. Although there are principles, guidelines, and standards that has been leveraged by the industry, such as the OECD AI Principles, UNESCO Recommendation on the Ethics of AI, and ISO/IEC 42001 standard, the European Union's AI Act stands out as a pioneer regulatory instrument. Increasing number of African countries like Egypt, Morocco, Nigeria, Namibia, and Ghana have proposed AI-specific laws, and more have also announced plans to introduce the same.

Essentially, effective integration of AI governance structure is necessary for organisations to manage their risk and comply with global standards and guidelines on AI adoption. This often requires cross-functional collaboration, ensuring that legal, compliance, and risk considerations are embedded throughout product development, deployment, and operational processes.

How Can Startups in Africa Implement These Frameworks  ?

Startups across Africa face different challenges in adopting AI governance frameworks. This can sometimes be due to a limited understanding of its foundational principles, limited expertise for proper implementation, or limited resources to engage experts or use paid tools. In other cases, founders explore AI-driven solutions in response to emerging trends, even when the specific business challenges they aim to address are not fully articulated. Taking time to clearly define the problem at hand can significantly enhance the effectiveness of AI implementation. Organisations must articulate their goals and assign clear roles to ensure successful integration. Also, organisations must adapt global AI standards to local contexts for effective governance. Understanding the maturity of the organisation is key to implementing these frameworks successfully.

Furthermore, risk management frameworks are indispensable for ethical and legal AI integration. Startups must consider local laws and engage with stakeholders to navigate potential risks. Human oversight remains critical, especially in decision-making processes to prevent risks that might have costly repercussions. While budget constraints often limit access to proprietary tools, Startups are encouraged to use open-source alternatives as a viable solution for achieving compliance. For Startups who desire to integrate AI governance tools, there must be careful consideration of local and international regulations. Startups must align their frameworks with these laws to mitigate risks effectively.

Organisational Requirements for Effective Operationalisation of AI Governance Frameworks  

Creating an effective AI governance framework is essential for organisations seeking to manage AI systems responsibly and ethically. This begins with aligning the framework with the organisation's mission and vision, defining the scope and applicability of the framework, and communicating its value and impact to management and other stakeholders to get buy-in. This is then followed by establishing clear and adaptable internal policies to keep pace with evolving technologies. The need for adaptable policies necessitates continuous monitoring of legal and regulatory developments to ensure that the organisation remains compliant and can adapt to emerging jurisdictional standards. Other implementation steps include conducting regular assessments and providing staff training to ensure that ethical considerations are consistently upheld. A well-developed AI governance framework and playbook can serve as a practical guide, offering employees clear reference points that support the smooth implementation of governance measures across the organisation. Conducting AI Impact Assessments before deploying AI tools strengthens this approach by enabling early evaluation of potential ethical risks before deployment.

Equally important is cultivating a strong organisational culture that promotes awareness, accountability, and a shared understanding of the significance of ethical AI practices among all employees. To ensure that teams within an organisation are aligned to AI governance initiatives, collaboration and communication are crucial. One of the ways to promote collaboration is involving compliance teams from the ideation phase of product development or AI integration. Open communication channels are vital in allowing for timely updates and information sharing among legal, compliance, and technical teams.

To streamline AI governance, organisations can leverage existing privacy and security program frameworks. Organisations can avoid reinventing the wheel and achieve greater efficiency and coherence in oversight by building on well-established practices. Additionally, to drive AI governance further, designating an AI governance lead can help coordinate efforts across teams, prevent isolation, and ensure that stakeholders are informed and engaged throughout the process. This role is essential for fostering collaboration, especially within large establishments.

Understanding the cost implications of integrating AI governance tools is also crucial for streamlining operations. Organisations that are not financially capable of integrating sophisticated AI governance tools can focus on compliance with existing laws and regulations, like data protection, consumer protection, competition, product safety, and intellectual property rights, when implementing AI systems. Lastly, promoting AI literacy within an organisation is vital for effective governance. Training and awareness can help employees understand AI risks and ethical usage, fostering a responsible culture.

AI Governance for AI Agents

There is an increase in the proliferation of AI agents being integrated into existing businesses and products. Understanding the operations and limitations of AI agents is crucial for establishing effective governance frameworks, especially as these systems operate with a degree of autonomy. Unlike traditional software, AI agents can make decisions, learn from data, and adapt their behaviour over time, which introduces complex ethical, legal, and operational considerations. Their autonomy demands a tailored governance structure that accounts for accountability, transparency, and risk management across various use cases.

A key aspect of this governance involves clearly defining the roles and responsibilities of human stakeholders, such as developers, users, and oversight bodies who interact with or supervise these agents. This ensures that human intervention remains possible and meaningful, particularly in high-stakes environments. As AI agents become more embedded in sectors like finance, healthcare, and public services, governance must also address issues such  explainability, liability, and compliance with jurisdictional laws. This includes ensuring that AI agents do not operate in regulatory blind spots and that their decision-making processes can be audited and contested when necessary. Ultimately, effective governance of AI agents must strike a balance between innovation and control, enabling their benefits while safeguarding human rights and institutional integrity.

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Africa's Readiness for AI Regulation

While the ambition to regulate AI in Africa is commendable, structural limitations suggest that a phased approach may be more effective. One of the panellists hinted that establishing AI-specific regulatory frameworks in Africa may be premature given current infrastructure challenges. Therefore, leveraging existing international frameworks can help address local challenges without overburdening systems. The EU’s own difficulties in operationalising its AI legislation serve as a cautionary tale. Addressing foundational issues, such as data protection and infrastructure, should take precedence over hard regulations. Focusing on these basics will create a more conducive environment for AI development.

Regulating AI in Africa presents challenges between innovation and regulation. Hence, a balanced approach is needed to foster growth while ensuring the responsible use of AI. While AI governance across African countries is still evolving, existing principles, guidelines, and international standards continue to offer valuable direction for organisations and tech companies seeking clarity on responsible AI practices. It is worthy of note that African countries have begun making extensive efforts at shaping AI use in their respective countries through soft-laws like strategies, blueprints, and guidelines. The African Union (AU) AI Continental Strategy was launched in July 2024 to harness AI as a transformative force for inclusive growth, ethical innovation, and socio-economic development across Africa. Countries like Algeria, Benin, Cameroon, Egypt, Ghana, Kenya, Mauritania, Mauritius, Senegal, and Zambia, among others, have also published national AI strategies to guide ethical AI adoption while fostering local talent and attracting investment in emerging tech sectors. As AI development and adoption in Africa advance, various AI regulations are likely to emerge on the continent. For instance, Morocco, Namibia, and Nigeria have a draft AI bill before their Parliament, while Ghana is working on an emerging technologies bill.  

While things continue to unfold, existing data protection and laws in some African countries are already providing some level of direction and data protection authorities playing the proxy regulator role on how to approach AI regulation; for example, data subjects have the right not to be subject to decisions made solely on automated decision-making. Another example is the approach of the Moroccan Data Protection Authority imposing a moratorium on the use of facial recognition technology before publishing guidelines on their safe use.  Additionally, existing consumer protection and intellectual property laws also provide some direction on how to approach issues that arise from the use of AI.

Conclusion

As AI continues to shape the future of innovation, operationalising AI governance frameworks is no longer just a theoretical exercise; it is imperative. From ensuring ethical deployment to managing risk and aligning with global standards, organisations must embed governance into every layer of their AI systems. This requires not only clear policies and cross-functional collaboration but also a culture of accountability and continuous learning.

Ongoing risk assessments, internal policy review, and algorithmic audits are necessary to monitor performance and uphold accountability. Also, understanding legal frameworks around data protection, consumer protection, and intellectual property is vital, as organisations must learn to balance commercial goals with regulatory compliance. Agility in governance structures ensures that responsibilities are clearly defined and that organisations remain responsive to evolving use cases.

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This article is based on the Hive Pulse Point Series event moderated by Lauretta Onwuegbuzie, with Ubongabasi Obot, Temitayo Ogunmokun, Victor Famubode and Ikran Abdirahman as panellists. We thank the guests for their time and input. You can catch up with the session recording here.

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