NAIROBI, Kenya, Aug 14 — Artificial intelligence is rapidly moving from research laboratories into offices, factories, hospitals, banks and classrooms, transforming how businesses operate and redefining the skills employers expect from their workforce.PwC’s 2025 Africa Workforce Hopes and Fears Survey found that 64 per cent of workers across five African countries, including Kenya, used artificial intelligence in their jobs over the previous year, compared to a global average of 54 per cent. The African Union estimates AI could contribute up to USD1.5 trillion to Africa’s economy by 2030.For Kenya, the opportunity extends beyond adopting AI-powered tools. The country hopes to position itself as a regional technology hub capable of developing and exporting AI-driven solutions.Whether it achieves that ambition will depend heavily on people.The next generation of software engineers, data scientists, cybersecurity specialists, AI researchers and digital technicians will determine whether Kenya becomes a creator of artificial intelligence or remains largely a consumer of technologies developed elsewhere.That places universities and Technical and Vocational Education and Training (TVET) institutions at the centre of the country’s digital transformation.The question is whether Kenya’s education system is moving fast enough to prepare graduates for an economy being reshaped by AI.A race against a moving targetUnlike previous technological shifts, artificial intelligence is evolving at extraordinary speed.Generative AI platforms now assist with software development, financial analysis, customer service, content creation and scientific research, while employers increasingly seek graduates with skills in machine learning, cloud computing, data engineering and AI ethics alongside traditional programming.Yet university curricula can take years to review and implement, creating a potential mismatch between what students learn and what employers need.A World Bank analysis of more than 60,000 online job advertisements posted on Kenyan recruitment platforms between 2015 and mid-2019 found differences between labour-market demand and computer science programmes at the University of Nairobi and Moi University.The study identified gaps in areas including machine learning, big-data analytics, cloud computing and Python programming.It also found employers were seeking more than technical expertise: about 47 per cent of demanded skills were technical, while nearly one-third related to business and interpersonal capabilities such as communication, teamwork and problem-solving.The World Bank recommended stronger university-industry links and curriculum reforms to narrow the gap.Several years later, the challenge remains relevant.The Federation of Kenya Employers’ 2023 Skills Needs Survey, conducted across 521 enterprises, found that one in five employers struggled to fill vacancies requiring specialised skills, while more than 73 per cent reported investing in additional workplace training to bridge gaps left by formal education.Information technology remained among the sectors experiencing sustained demand, while computer and software engineering accounted for nearly one-third of engineering skills employers sought.For graduates entering an AI-driven workplace, a degree alone is therefore increasingly insufficient.Employers want more than AI literacyCarolyn Nyokabi Mungai, Training and Capacity Development Lead at Simplify IT, says Kenya is moving in the right direction but needs to deepen understanding of what AI can actually do.“AI is not a future technology; it is a present technology,” Mungai said.Simplify IT Training and Capacity Development Lead Carolyn Nyokabi Mungai says Kenyan graduates need stronger digital foundations and practical AI skills to meet the demands of an increasingly AI-driven workplace/CFMShe pointed to platforms such as ChatGPT, Microsoft Copilot and Gemini, which are already being used in work and research.But Mungai said meaningful use of AI requires more than knowing how to enter a prompt.“You cannot just go and just ‘do’ AI. You must have a background in using digital environments or IT,” she said.Her point highlights a broader challenge for universities: graduates need a strong technical foundation that allows them to understand, adapt and build with AI rather than simply consume AI-generated answers.That also means preparing students for continuous learning.As new AI models and applications emerge, the skills acquired at graduation may need to be updated repeatedly throughout a professional career.Are universities catching up?Kenyan universities have begun expanding programmes and courses in artificial intelligence, data science, cloud computing and cybersecurity, while increasingly partnering with technology companies to expose students to practical applications.The Open University of Kenya (OUK), for example, entered into a five-year partnership with BCS Technology in 2025 to strengthen AI education.The programme combines training in areas ranging from introductory AI concepts to advanced large language models with laboratory work, hackathons and a job-placement pathway for top-performing participants.OUK-BCS Technology partnership also includes plans for an AI laboratory to support applied research and collaboration with international researchers.The approach reflects a growing recognition that employability depends on more than theoretical knowledge.But the extent of the national transformation remains difficult to measure.There is no reliable consolidated public figure establishing exactly how many Kenyan universities currently offer dedicated AI or Data Science programmes, how many students are enrolled nationally in them, or whether graduate tracer studies show a nationwide improvement in employment outcomes.A 2026 study published in Discover Education, using more than 46,000 real-time Nairobi job postings, found continued differences between academic preparation and changing industry demand and called for mechanisms capable of continuously updating curricula as labour-market needs evolve.The study is not a national audit, but it reinforces the broader concern that curriculum development must become more responsive to technological and labour-market change.Teaching the teachersIf universities are redesigning what students learn, they must also ensure those teaching them can keep pace.In 2024, the Microsoft Africa Development Centre completed an artificial intelligence and software engineering upskilling programme involving twenty-four lecturers from leading Kenyan universities.The 12-week programme exposed lecturers to AI, software engineering, industry practices and project-based learning.Peter Muturi, a programming lecturer at Multimedia University who completed the programme, said it forced lecturers to reconsider whether their teaching was sufficiently aligned with industry needs.“Through the programme, we have learned what the industry is looking for. It has allowed us to see that we might not have been preparing students adequately for the current market needs,” Muturi said.That admission may be one of the most revealing findings in the debate over Kenya’s AI talent pipeline.Curriculum reform is important, but it cannot succeed if lecturers themselves lack access to current technologies, industry practices and opportunities for continuous professional development.Where theory meets practiceThe gap between academic knowledge and workplace competence is illustrated by the experience of Kenyan technology professional Kennedy Kamande Wangari.While studying at Jomo Kenyatta University of Agriculture and Technology, Wangari developed an interest in business intelligence, data mining and analytics.Kenyan technology professional Kennedy Kamande Wangari, who transitioned from university training in data science and analytics to applying his skills in a professional workplace, says practical experience is critical in preparing graduates for the AI-driven labour market/FILEIn 2019, he was part of a four-member team that won the Data Science Track during the Oracle Student Hackathon, but an internship at a local bank became the turning point in translating his academic knowledge into practical capability.Working with real organisational data showed him how technology could solve actual customer problems rather than simply satisfy academic assignments.The transition, however, was not seamless.Wangari found that working on real projects required more than technical knowledge. He had to learn how to structure projects, collaborate with multidisciplinary teams, communicate with non-technical stakeholders and keep pace with rapidly changing technologies.His experience demonstrates why internships, competitions, mentorship and workplace exposure increasingly form part of professional preparation rather than optional extras.Faith Muasyo, a graduate of Moringa School, makes a similar observation from the student perspective.She says students receive a strong foundation in programming, databases, algorithms and software engineering, but practical exposure to modern AI tools does not always keep pace with the technology’s development.“Students learn important concepts such as programming, databases, algorithms and software engineering, but there is still a gap when it comes to practical exposure to modern AI tools such as generative AI, AI-assisted coding platforms and machine learning applications,” Muasyo said.Students seeking deeper AI exposure, she added, often have to learn independently, experiment with AI tools and build projects outside the formal curriculum.Internships can help bridge that gap by exposing students to professional workflows, real-world requirements, collaboration and workplace expectations.For Muasyo, the priority is not to abandon the fundamentals but to apply them using current technologies.“The fundamentals remain extremely important, but students also need opportunities to apply those fundamentals using modern tools and real-world problems,” she said.Bringing industry onto campusUniversities are increasingly turning to industry partnerships to provide that practical exposure.The University of Nairobi’s 2024 partnership with Sama was designed to expose students and faculty to the generative AI environment through part-time employment opportunities, workplace projects and industry engagement.Sama committed to providing training, equipment, materials and work areas, while UoN said the partnership would allow students to apply academic knowledge in real-world settings.Sama Vice President for Global Service Delivery Annepeace Alwala said the partnership was intended to foster the next generation of AI talent and give students practical experience.The publicly available information however does not establish how many students have participated, how many subsequently moved into permanent employment or which skills gaps remained among participants.That absence of outcome data is significant because the ultimate test of such partnerships is not how many agreements are signed, but whether they produce graduates who are more employable.TVET joins the AI raceThe AI talent pipeline extends beyond universities.Kenya’s digital economy will also require technicians capable of installing, maintaining and supporting the infrastructure behind artificial intelligence, including cloud computing, networking, cybersecurity and telecommunications.The State Department for Technical and Vocational Education and Training entered into a three-year partnership with Huawei in 2025 aimed at strengthening digital skills.The initiative plans to establish 150 Huawei ICT Academies across TVET institutions, offering training in networking, cloud computing, artificial intelligence and cybersecurity.It also targets 1,000 professional certifications annually and plans to train about 150 instructors each year.At OUK, Huawei Kenya and Equity Group Foundation launched a Huawei ICT Academy in May 2025, targeting 10,000 students for training and professional certification in AI, cloud computing, cybersecurity and coding.The programmes also include innovation activities intended to expose students to real-world challenges.But, as with university-industry partnerships, available announcements do not provide sufficient employment data to establish how many participants ultimately secure internships or jobs.Kenya is expanding its AI training pipeline, but national systems for measuring whether that training translates into employment remain limited.Can Kenya build AI, not just consume it?The talent question also extends beyond employment.If Kenya is to become an AI hub, its universities must contribute research, local applications and technologies designed around Kenyan and African problems.The National Artificial Intelligence Strategy 2025–2030 identifies education, workforce upskilling, innovation and startup incubation among the pillars needed to build the human capital required for AI adoption.There are signs that universities are beginning to pursue that ambition.In February 2025, JKUAT held discussions with a delegation from the University of Tokyo led by Professor Yutaka Matsuo on potential collaboration in AI research, innovation and academic exchanges.At JKUAT’s 2025 AI Summit, Dr Lawrence Nderu, Chairperson of the university’s Department of Computing and founder of JHUB Africa, argued that Africa should use AI to create profitable ventures addressing local challenges.The university also hosted a World Intellectual Property Organization programme in May 2026 focused on intellectual-property commercialisation for deep-tech ventures.But the available evidence does not provide a reliable national figure for the number of AI research projects underway in Kenyan universities or how many university-developed AI projects have been successfully commercialised.That leaves research funding, infrastructure and commercialisation as significant gaps in the country’s emerging AI ecosystem.Kenya is making progress in building an AI talent pipeline. Universities are expanding AI training, technology companies are investing in lecturer development, industry partnerships are creating workplace opportunities, and TVET institutions are adding advanced digital skills.But progress should not be confused with readiness.Employers still invest in additional workplace training, students report gaps between classroom learning and industry tools, and Kenya lacks sufficient data to show how many AI-trained graduates secure relevant jobs. AI research and commercialization also remain at an early stage.Kenya’s education system has recognized the AI shift and begun adapting, but not yet at the pace of the technology or labour market.The country is preparing tomorrow’s AI workforce, but tomorrow is already here.The test will be whether graduates can apply their skills, keep learning and create value—not simply consume AI tools.