TechTrends Africa

The assistant, now running on Meta’s newly released Muse Spark 1.1 model, can plan a task, link up with your email and calendar, build presentation slides, and carry a job through to completion without you having to babysit every step. The upgrade sits at the center of Meta’s push toward what it calls personal superintelligence — an assistant that understands your context, stays available around the clock, and takes care of things on its own. With Muse Spark 1.1 powering both the Meta AI app and meta.ai, the shift is less about smarter answers and more about follow-through. https://lnkd.in/dKhEwJUc

Applications are open for the newest cohort of Harambeans, the pan-African entrepreneurship network known for its highly selective admissions process and a track record of alumni companies that now shape parts of the continent’s tech landscape. Founders have two submission windows this cycle. An early admission deadline falls on September 30, 2026, followed by a regular admission deadline on October 31, 2026, according to details published on the Harambeans application page. Each class admits just 30 members from a pool that typically exceeds 3,000 applicants, making it one of the more competitive entrepreneurship networks operating on the continent. Applicants can find further details on the organisation’s approach and support structure on its About Us page ahead of submitting. https://lnkd.in/evTU4rpD

Every funding announcement out of Lagos, Nairobi, or Cape Town tends to get outsized attention; venture capital has become the default measure of startup credibility across the continent. But underneath that headline economy sits a quieter one: founders who built real, revenue-generating businesses without ever taking a term sheet and, in several cases, without wanting one. Kenya’s Pesapal is probably the clearest example of what patient, self-funded growth looks like at scale. The payments company built its business through direct partnerships with banks and mobile money platforms rather than chasing institutional capital. Muvment By AUTOGIRL, a vehicle-sharing platform sometimes described as the “Airbnb of vehicles,” paid out roughly N1 billion to car owners in 2024 alone, and its founder Chinazom Arinze describes the business as bootstrapped and profitable. Nimbus Media Limited, founded by Wale Adegoke in 2011, has grown for over a decade without taking outside investment, expanding from a single advertising site to eighteen proprietary locations across the country. Agosta Liko https://lnkd.in/e_4nwPcN

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According to the latest findings by Check Point Research (CPR) of Check Point Software, Microsoft remains the most impersonated brand, accounting for 23% of all brand phishing attempts during the quarter, nearly double the next-closest brand. The findings also show that cybercriminals continue to exploit the trust users place in widely-used technology, social networking, banking and now AI platforms to steal credentials, payment details and personal information. In Q2 2026, LinkedIn ranked second at 11.6%, followed by Google at 6.7%, Apple at 5.8% and Amazon at 5.2%. Together, the top five most impersonated brands accounted for more than half of all brand phishing activity tracked this quarter, underscoring how attackers are focusing on a small group of globally recognised platforms that people use and trust every day. Notably, OpenAI’s ChatGPT made the top 10 list for the first time, marking a clear signal that AI tools are now firmly on cybercriminals’ radar. https://lnkd.in/e7K6RVv5

Organisations are moving quickly from AI ambition to AI use cases. Employees are already using AI tools in their daily work, while leadership teams want practical ways to improve efficiency, customer experience, decision-making, and competitiveness. “AI confidence starts with the data estate behind the model,” says Nathi Dube, Director: Innovation at PBT Group. “Before an organisation can rely on AI, it needs to understand what data it has, where that data comes from, who owns it, how sensitive it is, and whether it can be trusted for the use case in front of it.” AI can accelerate work and open new possibilities, while also exposing weaknesses that have often been tolerated inside fragmented data environments. Trusted data starts close to the source.  Business owners understand how data is generated, how KPIs are defined, which exceptions exist, and which systems carry the most reliable information. Data teams need that business knowledge to build quality measures, document definitions, and create a common understanding across the organisation. AI confidence is built by creating the conditions that enable responsible AI use. https://lnkd.in/eJA_u9NS

Most of the rules now shaping how artificial intelligence gets built were written somewhere else. The European Union has its AI Act. The United States has a patchwork of executive orders and state laws. China has its own regulatory architecture entirely.  Africa, home to 1.2 billion people and some of the fastest-growing digital economies on earth, has largely adopted frameworks designed around problems it doesn’t have, while living with gaps around problems it does. Most large language models are trained on text scraped predominantly from the English-speaking internet, and the imbalance is stark. English alone can make up more than half the text in major pretraining datasets, while all African languages combined often account for less than 0.1 percent. A governance framework built for Africa has to start from those realities — informal finance, linguistic diversity, thin regulatory capacity, and data infrastructure still being built, rather than treating them as edge cases added later. https://lnkd.in/epiBDJn4

Africa’s food security problem has never really been a land problem. The continent holds roughly a quarter of the world’s arable land, yet contributes only about a tenth of global agricultural output. The gap sits between the farm and the market, in the tractors smallholders can’t afford, the credit they can’t access, the fertiliser they buy on guesswork, and the harvests that spoil before reaching a buyer. A cluster of agritech startups across Nigeria, Kenya and beyond has spent the last decade trying to close that gap. Hello Tractor built its business around that shortfall. Its model works like a ride-hailing app for farm equipment: tractor owners list idle capacity, and smallholders book services through a mobile app or, where smartphones aren’t available, SMS. Kenya’s Apollo Agriculture assesses farmer creditworthiness using satellite imagery, soil data and machine learning rather than land titles or bank statements, then delivers a bundled package of inputs, insurance and advisory support through local agents and agro-dealers. Babban Gona https://lnkd.in/eGjSwwV6

A South African judge recently sat down to verify nine legal citations submitted in a supplementary court notice. Only two turned out to exist, and one of those had the wrong reference. The rest were fictions, generated with total confidence and formatted to look exactly like real case law. AI hallucination: the tendency of large language models to generate false information with the same fluency they use for true information. A global tracking database maintained by legal researcher Damien Charlotin has now logged well over a thousand court cases worldwide involving suspected or confirmed AI-hallucinated material, with entries from South Africa, the UK, Israel, and beyond. There is a second, distinctly African dimension to this problem: most large language models are trained overwhelmingly on English, French, and a handful of other high-resource languages. Research cited by Nature found that African languages have the least support of any region among the roughly 670 languages tested for chatbot performance. https://lnkd.in/evW3xWZj