The world of artificial intelligence (AI) is evolving at an extraordinary pace, transforming science fiction into everyday reality. In just under a decade, we have seen AI systems that perform fundamental data analysis transitioning to those that generate stunning visuals and can “talk” to us. We are now about to enter the era of “agentic AI”, a revolutionary form of artificial intelligence that does not just respond to prompts but proactively makes decisions and drives actions to achieve preset goals. This paradigm shift is poised to redefine business operations and human-technology interaction in ways we are only beginning to comprehend, offering unprecedented opportunities for innovation and efficiency.
What is agentic AI?
Agentic AI represents systems capable of autonomous action for human users or other AI systems. Unlike traditional AI and even generative AI (GenAI) such as ChatGPT, which requires explicit instructions for every task, agentic AI assesses situations, formulates plans, and executes them with minimal – but not entirely free from – human oversight. Put differently, one of its defining features is the “flipped interaction” model, in which the AI takes initiative rather than waiting for user instructions. Think of it as having a highly skilled personal assistant who understands your objectives and proactively works towards achieving them without constant direction, a shift from a “do-it-yourself” approach to one that is “do-it-for-me.”
Key characteristics of agentic AI include autonomy in operation, adaptability through interacting with humans and feedback from past actions, clear goal orientation, proactive information search and analysis, and taking actions without further prompting. The ability to operate autonomously while aligning with user goals sets agentic AI apart from prior AI tools, making it a powerful force for workplace transformation.
Until recently, most of the use of GenAI was to generate a response – output that is understandable and useful to the users. But instead of calling the GenAI only once in a process to create output solely, can we use it to do more such as selecting which database to draw information from for the responses or determining the type of response to the user? Such rethinking makes AI agents possible, all of which share the following five general steps to management workflows and accomplish goals: perceiving (gathering and processing data from various information sources), reasoning (using GenAI to understand tasks, generate solutions and coordinating specialised AI models for specific functions), acting (executing tasks in using tools such as spreadsheets or customised user interfacing platforms), learning (improving through feedback and experience), and collaborating (sharing information with other AI agents and users to enhance overall performance).
Such architecture enables seamless integration with existing business processes while maintaining the flexibility to adapt to changing requirements and circumstances. This breakthrough is not to be underestimated. Humans are staggeringly adaptive and versatile: for instance, we can structure a YouTube video’s content into an Excel spreadsheet. This is undoubtedly time-consuming but not undoable. In contrast, getting machines to perform the same task is far more complicated, not least because we first have to build a way for YouTube to interface with Excel. And this may not be repeatable if different spreadsheets are necessary for different YouTube content.
Such new-found adaptability for machines is crucial for organisations operating in dynamic business environments, where agility and responsiveness are essential for success. While both agentic AI and GenAI are transformative technologies, they serve distinctly different purposes. GenAI excels at creating content like text, images, and music in response to specific prompts. In contrast, agentic AI specialises in autonomous problem-solving and action, handling complex, multi-step tasks with sophisticated reasoning and planning capabilities. As an analogy, GenAI is much like a recipe generator. On the other hand, agentic AI is more akin to a personal chef who manages the entire meal preparation process end-to-end, from menu planning to serving.
Transforming the modern workplace
Agentic AI is fundamentally changing how we work and think about professional roles. Automating routine tasks allows humans to focus on higher-value activities requiring critical thinking, creativity, and emotional intelligence, which in turn can lead to more fulfilling work and higher job satisfaction. In addition, this evolution in workplace dynamics creates opportunities for professionals to develop new skills and expertise in AI system management and strategic oversight, fostering a more dynamic and innovative work environment.
AI agents at work
Across industries, agentic AI is set to open up new opportunities. In customer service, AI agents automate routine interactions and provide personalised responses, even predicting potential issues before they arise. Software developers benefit from automated coding tasks and debugging, allowing them to focus on creative challenges. In healthcare, AI agents assist in analysing medical data, diagnosing, and providing round-the-clock patient support, significantly improving the quality and efficiency of care delivery.
The technology is equally impactful in sales and marketing, where AI agents manage leads and optimise campaigns, book meetings, and answer queries. In supply chain management, they optimise inventory, predict disruptions, and reconfigure supply chains in real-time. Manufacturing operations benefit from AI agents that analyse sensor data to predict equipment failures and improve product design.
In finance, Nexus FrontierTech, the company I co-founded, uses AI agents to collect and analyse environmental and sustainability data, enabling major lenders to efficiently approve new loans and monitor existing ones. My colleagues and I are currently developing a highly customisable AI agent system that can help small and medium-sized businesses automatically accomplish specific tasks, such as a chatbot that can answer unanticipated questions or an agent that can read invoices (which can come in countless styles and formats) and produce a structured output. While in their nascent stage of development, these applications demonstrate how agentic AI is not just a theoretical concept but a powerful tool already delivering tangible benefits across diverse sectors.
Navigating challenges
Despite its potential, agentic AI presents significant challenges that require careful consideration and proactive management. A key concern is accountability for AI-made decisions: If the AI agent makes a mistake, who is responsible? The AI? The company itself? Or the technology provider? Another concern is transparency in decision-making processes. We need to ensure that the AI-generated output and decisions are explainable. Just as important is security against misuse or interference. Human agents are corruptible, but AI agents are both corruptible and hackable.
Organisations must also consider the human impact of implementing these systems, ensuring that automation enhances rather than diminishes human roles. Addressing these challenges demands robust regulatory frameworks, clear guidelines and guardrails, and continuous oversight. This balanced approach is essential for building trust and ensuring sustainable adoption of agentic AI technologies.
The road ahead
Agentic AI stands poised to revolutionise industries and redefine technological innovation. As these systems become more sophisticated, they will tackle increasingly complex problems, driving unprecedented efficiency and creativity. Companies that embrace agentic AI will be better positioned to adapt to the evolving digital landscape, gaining a competitive edge in an increasingly complex world. However, successful adoption requires a balanced approach that maximises benefits while addressing ethical and operational challenges. Organisations must invest in training, infrastructure, and governance to ensure responsible and effective deployment.
As we enter the age of “do-it-for-me,” agentic AI represents more than just technological advancement. It signals a fundamental shift in how we approach work and problem-solving. By moving beyond simple task execution to become autonomous problem-solvers, these AI systems are set to transform industries, enhance productivity and drive innovation. Businesses that embrace this new wave of intelligent revolution will likely thrive more and better in an increasingly automated world.
Summary
- Agentic AI is a new form of AI that autonomously makes decisions and takes actions to achieve goals.
- It transforms workplaces by automating routine tasks, allowing humans to focus on higher-value activities.
- Agentic AI is already impacting industries like healthcare, finance, and customer service by improving efficiency and personalisation.
- Challenges include accountability, transparency, and security, requiring robust frameworks and oversight.
- Embracing agentic AI offers a competitive edge in the digital landscape, driving innovation and productivity.