Generative AI (GenAI) is no longer just a futuristic concept but a tangible tool transforming businesses across the globe. In Kenya, its integration into daily operations is becoming increasingly common, whether through tools like ChatGPT, Microsoft Copilot or Bard.
These applications often assist in automating mundane tasks such as drafting documents, summarising meetings, or even creating presentations.
While these are impactful at a micro level, the question remains: Can GenAI truly reshape business operations and deliver significant returns on investment?
The answer lies in the approach. The full potential of GenAI extends far beyond routine tasks, and many organisations in Kenya are on the cusp of leveraging this technology to drive enterprise-wide transformation. However, some are still hesitant, viewing GenAI as more hype than substance. This reluctance may cause them to lag behind competitors already incorporating AI into their operations.
In an era where global markets are moving swiftly toward AI-driven solutions, businesses in Kenya must act with urgency to avoid being left behind.
The rapid evolution of GenAI is undeniable. A Gartner study predicts that by 2025, over 30 percent of outbound marketing messages from large organisations will be synthetically generated, a significant leap from just two percent in 2022. GenAI offers Kenyan businesses a unique opportunity to leapfrog competitors, especially in industries where digitalisation is still catching up.
In Kenya, sectors such as banking, insurance, and healthcare are already exploring the capabilities of GenAI. 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.
A retailer, for instance, can forecast inventory needs based on customer behaviour, a financial institution can streamline compliance checks through AI-powered systems and a manufacturer can improve supply chain by dynamically optimizing distribution of goods.
To realize these benefits, businesses need a clear strategy that aligns GenAI implementation with core business objectives. Without this, GenAI could easily become another fleeting trend.
Building a comprehensive roadmap requires both an understanding of the technology and a deep awareness of the specific needs of the business. Expert partners can offer tailored solutions that help scale GenAI initiatives from proof of concept to full-scale deployment.
However, the path to successful GenAI adoption is not without its challenges. One of the primary hurdles is moving from small-scale pilot programs to production-ready solutions. This requires substantial investments in data governance and infrastructure, areas where many Kenyan businesses are still lagging.
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 implementations and ultimately hinder business transformation.
Additionally, concerns around governance, risk, and ethics must be addressed to ensure that AI systems are both secure and trustworthy. Kenyan businesses must invest in long-term infrastructure upgrades and develop robust data strategies to avoid these pitfalls.
Fortunately, the cost of adopting GenAI is becoming more manageable, with new consumption models allowing businesses to pay only for the tokens used in a given query.
The other hurdle is user enablement. The impact of a good product on your organization depends not only on the product itself, but also on how well the business users can incorporate the capabilities of the product into their everyday work.
This is called ‘People First’ strategy. The questions asked here include ‘When can I use AI in my everyday work?’, ‘How does AI make my work easier?’. It is about gaining trust from the users of the AI as well as prioritizing user experience and satisfaction over mere usage statistics. The users of the AI-enabled systems must gain the necessary knowledge to use AI effectively and drive business goals.
Several key trends are shaping the future of GenAI, the first of which is “prompt engineering.” This field involves crafting precise prompts to ensure that AI generates meaningful results. As this practice evolves, two other technological approaches—retrieval-augmented generation and agentic modelling—are also gaining traction.
Retrieval-augmented generation enhances GenAI’s accuracy by integrating it with existing data. This allows businesses to train AI models on specific data sets, generating more relevant and context-specific insights. For instance, a Kenyan bank could fine-tune a large language model (LLM) to better assess the creditworthiness of local borrowers based on historical data.
Agentic modelling, on the other hand, refers to AI systems that automate complex workflows with minimal human intervention. This can significantly improve efficiency, as seen in the insurance sector, where AI-powered virtual assistants are now capable of processing claims, freeing up human agents for more strategic tasks.
Kenya is well-positioned to leverage GenAI for transformative business outcomes, but this will require more than just purchasing the technology. To succeed, organizations must align their GenAI strategies with broader business objectives, develop strong data governance frameworks, and ensure their teams are equipped with the necessary skills to manage these systems.
Ultimately, GenAI is not just a trend but a critical business imperative. Kenyan companies that embrace this technology now will be well-positioned to thrive in an increasingly AI-driven future.
The writer is Automation and Data Engineer at NTT DATA in East Africa.
