Generative Artificial Intelligence (GenAI) is no longer just a futuristic concept, but a tangible tool to transform businesses around the world. In Kenya, its integration into daily operations is becoming increasingly popular, whether through tools like ChatGPT, Microsoft Copilot or Bard.
These apps often help automate mundane tasks like drafting documents, summarizing meetings, or even creating presentations.
While these are impactful at the micro level, the question remains: Can GenAI reshape business operations and deliver significant returns on investment?
The answer lies in the approach. The full potential of GenAI extends beyond routine tasks, and many organizations in Kenya are poised to leverage this technology to drive enterprise-level transformation. However, some remain hesitant, viewing GenAI as more hype than substance. This hesitation could cause them to fall behind competitors who are already integrating AI into their operations.
In an era where global markets are moving rapidly towards AI-driven solutions, businesses in Kenya must act urgently to avoid being left behind.
The rapid development of GenAI is undeniable. A Gartner study predicts that by 2025, more than 30 percent of marketing messages from large organizations will be generated synthetically, a big jump from just 2 percent in 2022. GenAI offers Kenyan businesses a unique opportunity to leapfrog competitors, especially in industrial Which depends on digitalization. Still catching up.
In Kenya, sectors such as banking, insurance and healthcare have already begun exploring GenAI’s capabilities. For example, banks are deploying AI-powered chatbots to enhance customer service while healthcare providers are using AI to recommend treatment plans and improve patient outcomes.
Beyond these front-end applications, the real value of GenAI lies in its ability to enhance back-end processes such as data processing and workflow automation.
For example, a retailer can predict inventory needs based on customer behavior, a financial institution can streamline compliance checks through AI-powered systems and a manufacturer can optimize the supply chain by dynamically optimizing the distribution of goods.
To achieve these benefits, companies need a clear strategy that aligns GenAI implementation with core business goals. Without it, GenAI could easily become another passing trend.
Building a comprehensive roadmap requires an understanding of the technology and a deep awareness of the specific needs of the business. Expert partners can provide customized solutions that help scale GenAI initiatives from proof of concept to large-scale deployment.
However, the path to successful GenAI adoption is not without challenges. One of the primary hurdles is moving from small-scale pilots to production-ready solutions. This requires significant investments in data management and infrastructure, areas where many Kenyan companies still lag behind.
Effective AI systems rely on access to clean, well-organized data, and many organizations still struggle with fragmented data systems. This can limit the success of AI applications and ultimately hinder business transformation.
Additionally, governance, risk, and ethics concerns must be addressed to ensure AI systems are safe and trustworthy. Kenyan companies must invest in long-term infrastructure modernization and develop robust data strategies to avoid these risks.
Fortunately, the cost of adopting GenAI is becoming more manageable, with new consumption models that allow companies to pay only for the tokens used in a specific query.
The other hurdle is user empowerment. The impact of a good product on your organization depends not only on the product itself, but also on how well business users are able to integrate the product’s capabilities into their daily work.
This is called the “people first” strategy. Questions asked here include “When can I use AI in my daily work?”, “How does AI make my work easier?”. It’s about gaining the trust of AI users as well as prioritizing user experience and satisfaction over mere usage statistics. Users of AI-enabled systems must acquire the knowledge necessary to use AI effectively and achieve business goals.
Several key trends are shaping the future of GenAI, the first of which is “agile engineering.” This field involves crafting precise claims to ensure that AI achieves meaningful results. As this practice evolves, two other technological approaches are also gaining traction – retrieval-enhanced generation and operant modeling.
Augmented retrieval generation improves the accuracy of GenAI by combining it with existing data. This allows companies to train AI models on specific data sets, generating more relevant and context-specific insights. For example, a Kenyan bank could improve its Large Language Model (LLM) to better assess the creditworthiness of local borrowers based on historical data.
Agent modeling, on the other hand, refers to artificial intelligence systems that automate complex workflows with minimal human intervention. This can significantly improve efficiency, as we have seen in the insurance sector, where AI-powered virtual assistants are now able to process claims, freeing up human agents to undertake more strategic tasks.
Kenya is well positioned to leverage GenAI to achieve transformative business outcomes, but this will require more than just purchasing the technology. To succeed, organizations must align their GenAI strategies with broader business goals, develop robust data management frameworks, and ensure their teams are equipped with the skills needed to manage these systems.
Ultimately, GenAI is not just a trend but a critical business necessity. Kenyan companies that embrace this technology now will be well positioned to thrive in an increasingly AI-driven future.
The writer is an automation and data engineer at NTT DATA in East Africa.
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