ARTIFICIAL intelligence (AI) agents will be a buzz-phrase in tech during 2025. There is a difference between an AI agent and general “AI” as we have always known it, though they are related concepts.
Last week, I introduced this topic and gave attention to its relevance to developing nations such as Zimbabwe. This week we shall look at it from another angle and dwell on its general significance on the global economy.
Agentic AI is set to become one of the most transformative technological advancements of 2025. Unlike traditional AI, which primarily analyses data or generates content, agentic AI introduces a new level of autonomy. These intelligent agents are designed to perceive their environment, make decisions, and take actions independently to achieve specific goals.
This evolution represents a significant leap forward in how businesses leverage AI, with profound implications for operations, decision-making, and strategy.
AI agents will dominate tech discussions in 2025, marking a shift from traditional AI. Unlike conventional AI, which analyses data or generates content reactively, agentic AI introduces autonomy, adaptability, and goal-driven behaviour.
Their transformative potential spans industries, enhancing decision-making, efficiency, and customer experiences globally.
Understanding agentic AI
To appreciate the significance of agentic AI, it is essential to distinguish it from conventional AI. Traditional AI encompasses systems that perform tasks requiring human-like intelligence, such as speech recognition or data analysis.
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However, these systems typically require human input to act on their outputs. Agentic AI, on the other hand, is designed to act autonomously. It observes its surroundings, processes information, and executes tasks without constant human oversight.
For example, a traditional AI system might predict weather patterns based on historical data. In contrast, an agentic AI system could integrate this weather data with soil moisture readings and autonomously decide when to irrigate crops in an agricultural setting.
This ability to not only analyse but also act makes agentic AI uniquely suited for dynamic and complex environments.
Defining theme for 2025
Agentic AI is emerging as a defining theme for 2025 due to advances in generative AI technologies and increased demand for automation in business processes.
Industry leaders have identified this year as pivotal for the technology’s adoption. The rise of multi-agent systems — teams of autonomous agents collaborating to solve intricate problems — marks a significant milestone in this evolution.
These systems can tackle challenges at a scale and complexity that single-agent systems cannot manage alone.
Moreover, agentic AI systems are equipped with continuous learning capabilities. They adapt based on real-world experiences, ensuring they remain effective even as business conditions evolve.
This adaptability makes them particularly valuable in industries where agility and responsiveness are critical.
Transforming business operations
The integration of agentic AI is transforming business operations by enabling organisations to move beyond basic automation into more sophisticated workflows and decision-making processes.
One of its most significant contributions is enhanced efficiency. By automating complex tasks traditionally handled by humans, agentic AI allows businesses to scale operations without proportionally increasing costs or workforce size.
In industries such as finance, agentic AI enables real-time decision-making by processing vast amounts of data instantaneously. For example, financial institutions can use these agents to monitor market trends and execute trades autonomously based on pre-defined objectives.
Similarly, manufacturing companies benefit from optimised resource allocation; Siemens AG has reported a 15% increase in production uptime and a 20% reduction in maintenance costs through the use of intelligent agents.
Another advantage is cost reduction. Companies such as AT&T have achieved significant savings — up to 15% in operational expenses — by deploying agentic AI solutions that streamline workflows and eliminate inefficiencies.
Practical industrial applications
Agentic AI’s versatility is evident in its applications across diverse sectors:
Customer service: Intelligent agents are revolutionising customer interactions by learning from past engagements and providing personalised responses. These systems operate around the clock, enhancing customer satisfaction while reducing operational costs;
Supply chain management: In logistics, agentic AI optimises delivery routes, monitors inventory levels, and predicts demand fluctuations. This capability is particularly valuable in today’s global supply chains, where disruptions can have cascading effects;
Healthcare: In medicine, agentic AI supports personalised care by analysing patient data and autonomously adjusting treatment plans based on real-time health metrics;
Financial services: From fraud detection to risk assessment, agentic AI enhances the speed and accuracy of financial operations while offering tailored financial advice to customers;
Manufacturing: In industrial settings, these agents manage production schedules, detect equipment issues before they escalate into failures, and optimise resource utilisation; and
These examples highlight how agentic AI is not just improving efficiency but also enabling entirely new capabilities that were previously unattainable with traditional automation tools.
Future outlook
As businesses increasingly adopt agentic AI, its role in shaping strategy and operations will only grow. One key development is the shift towards treating AI as a collaborator rather than merely a tool.
By the end of 2025, many organisations will rely on agentic systems to work alongside human employees, enhancing their productivity by automating routine tasks and enabling them to focus on higher-value activities.
Another promising area is autonomous workflow management. Agentic AI will soon be capable of overseeing entire workflows — from planning through execution — without requiring human intervention.
This capability will allow businesses to respond more swiftly to changing market conditions while maintaining operational efficiency.
Predictive capabilities are also set to improve dramatically. By analysing complex datasets and running simulations, agentic systems will enable organisations to anticipate disruptions — such as supply chain bottlenecks — and take proactive measures to mitigate risks.
Additionally, personalisation at scale will redefine customer engagement across industries. By leveraging large datasets, agentic AI can tailor interactions for individual customers on an unprecedented level.
Challenges, considerations
Despite its potential benefits, the adoption of agentic AI comes with challenges that businesses must address carefully.
Governance remains a critical concern as organisations grapple with questions about how much autonomy should be granted to these systems and how decisions made by agents can be audited for accountability.
Data quality and security are equally important considerations. Since agentic systems rely heavily on accurate data inputs, any errors or breaches could compromise their effectiveness or lead to unintended consequences. Ethical considerations also loom large. The ability of these agents to act autonomously raises questions about transparency in decision-making processes and the potential for unintended biases embedded within algorithms.
Workforce adaptation presents another hurdle. While widespread job losses are not anticipated — only 7% of executives predict overall headcount reductions — there is an urgent need for re-skilling employees so they can work effectively alongside intelligent agents. Currently, less than one-third of companies have up-skilled even a quarter of their workforce for this purpose.
Finally, integration challenges must be addressed as businesses seek to incorporate agentic systems into existing infrastructures seamlessly. This requires investments in modernising technology stacks and ensuring compatibility across platforms.
Conclusion
Agentic AI represents a paradigm shift in how businesses approach automation and decision-making. Its ability to operate autonomously while continuously learning makes it uniquely suited for tackling complex challenges across industries.
However, its successful implementation requires careful planning — balancing innovation with governance, ethics, and workforce readiness.
As we progress through 2025 — the year predicted to define this technology’s trajectory — it is clear that organisations embracing agentic AI stand poised to unlock unprecedented levels of efficiency, innovation, and competitive advantage in an ever-evolving global economy.
Bangure is a filmmaker with a media degree and substantial experience in media production and management. He previously served as the chairperson of the National Employment Council for the Printing, Packaging, and Newspaper Industry. A dedicated enthusiast and scholar of artificial intelligence, Bangure combines his creative and technical skills to delve into innovative advancements. — [email protected].
