Artificial intelligence has moved from a speculative futuristic technology to a force shaping everyday life. Power productivity tools, power predictive systems, and enable new business models across sectors from finance to healthcare. But as technology accelerates, so do questions about its social impact. One of the most pressing debates in technology policy today is not whether AI should be regulated, but how it should be regulated, and most importantly, whether it is the AI itself or how it is used.
Nigeria is not standing still in the face of rapid AI adoption. Lawmakers and regulators have put forward proposals to create a dedicated legal framework for AI governance, including bills that would create a National Artificial Intelligence Council, require registration and licensing for AI developers and adopters, and impose risk-based ethical standards on AI systems deployed in the economy. The bill, expected to be completed by early 2026, will be one of the continent’s first comprehensive AI regulatory efforts, with a focus on transparency, fairness, accountability, and risk assessment of high-impact applications, and will give regulators powers to request information, issue enforcement orders, suspend dangerous systems, and more.
This approach recognizes the important reality that artificial intelligence is a general purpose technology, not a single product or industry. Like electricity and the internet before it, the fundamental mechanisms of AI are neutral. The risks and benefits depend on how it is applied. Treating AI as inherently harmful and attempting to regulate the technology itself risks stifling innovation without meaningfully protecting the public.
Instead, by focusing on regulating use, policymakers can focus resources where they matter most: situations where AI impacts impact safety, privacy, economic fairness, or democratic processes.
Transparency is more than just a bureaucratic protocol. When AI systems impact service eligibility, pricing, and legal outcomes, individuals and businesses need to be able to understand, question, and, if necessary, challenge those decisions. Regulatory guidance emphasizes that explainability strengthens trust and enables the right to challenge results. This is a key capability as AI penetrates high-risk areas.
At the same time, there are real risks that are directly related to the operation of AI systems. Security vulnerabilities, ingrained bias in training data, and the potential for generative models to be misused for harmful purposes are not just theoretical threats. These risks have sparked debate about whether developers should disclose the datasets and intellectual property used in training, allow independent audits, and require explicit consent frameworks from users. Accordingly, parts of the AI Bill propose measures that would require companies developing or using AI to provide independent audit access and clear user consent model steps that directly interact with the deployment of the AI, rather than the underlying algorithms themselves.
But here too, a nuanced perspective is needed. Regulations that are too strict or too broad can create barriers to entry for small businesses, penalize innovators, and ultimately entrench the power of large incumbents. The UK Government’s AI Opportunities Action Plan reflects this balance, recognizing the importance of safety and assurance, while clearly prioritizing innovation and growth. We are committed to supporting secure AI infrastructure and training without imposing heavy compliance burdens that can inhibit startups.
Alternative free development is equally problematic. Without clear standards, generative models can become increasingly sophisticated and used for malicious purposes. Phishing campaigns, automated scams, and deepfake impersonations have already evolved beyond the ability of most small businesses and consumers to mitigate. In situations where companies have limited cybersecurity capabilities, the absence of regulatory guardrails amplifies risks.
For emerging markets, the stakes take on an additional dimension. Like the millions of small and medium-sized enterprises operating across Africa, the informal sector is already highly exposed to operational risks due to poor documentation, limited payment verification processes, and minimal regulatory oversight. As AI becomes embedded in business tools from automated billing to customer engagement, deploying these systems without the right governance structures can inadvertently widen inequality and expose vulnerable businesses to new threats. This is not a reason to oppose AI, but a reason to support a regulatory approach that allows for safe and inclusive adoption.
Regulation also has a prescriptive function. It lets the market know what standards are expected, reducing uncertainty for investors, consumers, innovators, etc. When companies understand that transparency, fairness, and accountability are not optional, they can internalize responsible practices that can foster long-term trust, an important currency in digital ecosystems. Conversely, a lack of regulation can undermine trust, put users at risk, and slow overall adoption.
In other words, the real policy axis is not “regulating AI” or “encouraging AI to thrive.” It lies between indiscriminate regulation that treats all AI as a hazard and targeted governance that protects innovation while managing risk where it matters. This is possible through a focus on use with rules tailored to context, impact, and risk level.
New policy frameworks, such as those seen in the UK, illustrate this balance. It incorporates principles that protect the public and businesses from harm while avoiding overly broad restrictions on the technology itself. These promote explainability and accountability without hindering creative and commercial applications. This risk-based approach acknowledges that the benefits of AI in healthcare, commerce, logistics, and more will only continue to grow if people trust the systems that support it.
Artificial intelligence is not going away. Its evolution is only accelerating. The challenge for policymakers and technology leaders is not to contain this genie, but to ensure that its power is used safely and equitably.
Regulation in this sense does not mean containment. It means responsible governance that uses strategies that protect society’s interests while allowing innovation to flourish.
