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By Kayode Sanni-Arewa

A data analyst, Oluwasesan Adedeji David, has urged African innovators to deepen their focus on building locally relevant artificial intelligence (AI) tools, even as developed economies like the United Kingdom accelerate AI adoption through large-scale platforms such as Amazon Bedrock.

David, who wrote on the state of global AI development, noted that the UK’s embrace of Amazon Bedrock a generative AI service that enables organisations to build applications without the burden of managing infrastructure is reshaping industries from banking and healthcare to education.

He said Amazon Bedrock is altering how businesses and public services engage with machine learning, making it easier for even small enterprises to build powerful applications.

He said the UK’s mature cloud ecosystem, government-backed AI policies, and strong funding have created a fast-moving environment for generative AI.”

He added that financial institutions like NatWest Bank and the National Health Service (NHS) are already testing Bedrock-powered chatbots, clinical note automation, and adaptive learning systems, while startups in London and Manchester are using the platform for legal, climate and recruitment tools.

David, however, observed that African nations cannot rely on such heavy infrastructure, pointing to funding gaps, limited internet access, and power shortages as persistent barriers.

He urged startups in Nigeria, Kenya, Rwanda and beyond to leverage open-source platforms such as Hugging Face and Google Colab to develop solutions targeted at local challenges.

His words: “UK is due to its alignment with the country’s broader strategy which emphasizes responsible AI and innovation diffusion. Bedrock is helping accomplish just that by supporting accelerated developments and advancements in the key sectors of focus including health, finance, and education which have been long earmarked by the government for major AI integration.

“Key players in these sectors like NatWest Bank and NHS that have already begun piloting generative AI tools powered by Bedrock to enhance productivity, automate customer service, and generate synthetic data. From these preliminary tests, indications are positive that Bedrock’s AI power chatbots can help reduce clients’ waiting time and thus improving on efficiency as well as customer satisfaction.

“On the same note, the piloting run on NHS trusts have confirmed the reliability of Amazon Bedrock to create patient discharge summaries, optimize clinical notes, and support predictive diagnostics. With the clerical workload now shifted to AI, the human workforce becomes relieved from repetitive cumbersome tasks enabling them to focus on care delivery thus resulting in higher quality of healthcare services. Similar trends are prevalent in the education sector in the UK where institutions are increasingly using Amazon Bedrock in their tutoring and adaptive learning systems.

“The move to embrace Amazon Bedrock is not only propagated by strategic business decisions but also strong regulatory and policy backing in the UK. A review of the UK’s national strategy as an enabling factor for trustworthy AI frameworks and policy coherence across sectors.

“Such institutional support facilitates safer AI experimentation and provides legitimacy to platforms like Bedrock. However, skepticism still persists regarding digital sovereignty in the middle of widespread embracement of AI built on top of foreign infrastructure.

He noted platforms like Zindi Africa, which crowdsources data science talent to tackle real-world problems, and Tunisia’s InstaDeep, acquired by BioNTech, as examples of how African ingenuity is gaining global recognition despite resource constraints.

David called for more government and private sector investment to boost internet infrastructure, provide energy stability, and fund youth-led AI projects.

He explained that while the UK is harnessing industrial-scale cloud services, African startups are carving a distinct path that majorly focuses on practicality and localization.

According to him , Africa’s AI ecosystem is characterized by frugality and adaptation in efforts to keep up with the global AI trends while working with extremely constrained resources.

The tech expert added: -For instance, in the absence of expansive cloud credits or proprietary Large language models (LLMs), startups in Nigeria, Kenya, and Rwanda are limited in scale and innovation as compared to their counterparts in developed countries. This leads to a situation where African startups resort to leveraging open-source platforms like Hugging Face, Google Colab, and local language datasets to build custom AI tools that are practical and native to their parent countries.

“African AI startups are turning proximity to problems into a strategic advantage. Rather than attempting to compete directly with global tech giants, these startups are focusing on local relevance by building tools that address uniquely African challenges such as credit scoring for the informal sector, crop yield forecasting for smallholder farmers, or early warning systems for floods and droughts.

“These developers also enjoy the advantages of being situated within the very communities they serve thus giving them an edge in understanding the cultural, economic, and linguistic aspects of the emerging issues. As a result of this embedded connection, African startups are able to conceptualize innovations that are not only practical but also authentic.

“One prominent example is InstaDeep, a Tunisian-founded company acquired by BioNTech which developed predictive AI for genomic sequencing using on-premise infrastructure and optimized models. Similarly, Zindi Africa operates a data science competition platform that crowdsources AI solutions for social challenges such as disease outbreak prediction and crop disease detection.

“It is also important to note that while African governments have historically been less equipped with formal AI policy frameworks, there is a notable shift toward recognizing the value of indigenous innovation. While analyzing AI revolution in Africa and government policies, many African countries are now prioritizing AI capacity building and partnerships between startups and academic institutions.

He stressed that both approachesthe UK’s infrastructure-driven model and Africa’s grassroots, necessity-driven path offer valuable lessons for scaling AI responsibly and inclusively.