Artificial intelligence (AI) has undergone remarkable progress in recent years, shifting from narrow, task-specific tools to increasingly versatile and adaptive models. Now, agentic AI has entered the fold with capabilities that span planning, execution, and adaptation, achieving complex objectives.
According to industry projections, AI could inject USD 1.5 trillion into the continent’s GDP by 2030, while a recent McKinsey report found that generative AI (GenAI) could contribute USD 60 to USD 103 billion in annual economic value, with over 40% of African institutions already experimenting with, or implementing, GenAI solutions.
This evolution signals a fundamental change in how intelligent systems will operate, with wide-reaching implications for industries, economies, and societies in a ripe African market.
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From Reaction to Initiative
Traditional AI applications, such as recommendation engines or chatbots, perform well within set parameters but rely heavily on human direction. Their intelligence is reactive, delivering responses or predictions only when prompted. Agentic AI transcends this limitation. By integrating autonomy, adaptability, and foresight, it enables machines to act proactively, anticipating needs and executing complex tasks without constant human intervention.
This shift from reactive to proactive systems illustrates how agentic AI, combined with digital infrastructure and strategic partnerships, can redefine service delivery, foster inclusion, and drive sustainable development, particularly in regions where access and resources are limited.
According to Dayn Amade, Entrepreneur and Inventor, Tablet Comunitario, these technologies present “an opportunity for governments to enhance service delivery by integrating technological advancements, ensuring seamless interaction and stronger citizen engagement.”
For example, in the healthcare sector, where diagnostic AI once analyzed scans and highlighted potential risks, agentic AI can automatically arrange follow-up tests, suggest tailored treatments, and update care plans as new information emerges. M-TIBA in Kenya already does this via digital health wallets. In the agricultural sector, where traditional AI once predicted crop yields or monitored soil conditions, agentic AI now coordinates irrigation schedules, distributes inputs, and advises farmers on planting strategies dynamically.
Agentic AI also strengthens cybersecurity, blending autonomous intelligence with human-centered strategies to anticipate, detect, and mitigate threats effectively. According to Anna Collard, SVP of Content Strategy & Evangelist at KnowBe4 Africa, agentic AI can play a transformative role in cybersecurity by enabling systems to act proactively rather than reactively, identifying threats, and responding autonomously while complementing human judgment.
The Building Blocks of Agentic AI
What sets agentic AI apart is the fusion of several advanced capabilities:
- Autonomy: Operating without constant prompts or oversight.
- Strategic Planning: Designing and executing multi-step approaches to achieve objectives.
- Continuous Learning: Evolving in response to outcomes and environmental feedback.
- Collaboration: Engaging with humans and other AI systems to accomplish shared goals.
This blend of functions shifts AI from a passive assistant into an active participant, capable of shaping its environment and outcomes. Although agentic AI enables scalability, this autonomy may misalign with human values. As agentic AI systems grow more complex, their decision making may become harder for humans to interpret or justify.
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Industry Transformation Predictions in Africa
The disruptive potential of agentic AI spans multiple sectors. In the financial sector, self-directed trading systems could optimize portfolios in real time and detect systemic risks before they escalate. Mobile money platforms such as MTN MoMo and M-PESA could leverage agentic AI to proactively prevent fraud, optimize transaction networks, and offer predictive financial guidance to underserved communities.
To optimize the supply chain and manufacturing,intelligent agents could coordinate logistics, mitigate disruptions, and balance cost efficiency with sustainability. African e-commerce giants like Jumia could adopt agentic AI to dynamically reroute shipments based on demand and transport conditions.
Overall, these implementations are governed bytelecom-centric AI agents that predict outages, allocate resources efficiently, and deliver uninterrupted services.
By focusing on overarching missions rather than narrow tasks, agentic AI promises to drive unprecedented levels of resilience, efficiency, and innovation.
Building Responsible Pathways
To unlock the full value of agentic AI while mitigating risks, ethical AI frameworks should be built to ensure accountability, transparency, and safety.Humans should remain in the loop for high-stakes sectors such as medicine, finance, and defenseand fairness, inclusivity, and sustainability should be embedded into system development. For example, agentic AI applications for smallholder farmers must prioritize equitable access and avoid favoring large commercial farms. To achieve this,policymakers, technologists, ethicists, and civil society must work together.
By shifting from reactive to proactive systems with real autonomy, adaptability, and collaborative capacity, AI can begin to mirror the decision-making capabilities of humans.
The future shaped by agentic AI is not about sidelining human intelligence, but amplifying it. With machines managing complexity and scale, humans can focus on vision, creativity, and purpose. In Africa, this could mean accelerated digital inclusion, smarter urban planning, precision agriculture, and improved healthcare delivery, bridging gaps that were previously insurmountable.
