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Imagine if your business could deploy a team of virtual agents that not only execute repetitive tasks but also make strategic decisions, learn, collaborate and adapt in real-time to changing conditions — all at a scale that was once unattainable due to limitations in hiring, capitalization or other constraints. This is the power of agentic AI, a transformative technology that automates business processes, enabling organizations to scale operations, decision-making and innovation exponentially.
In recent years, tools like Robotic Process Automation (RPA) have been deployed to automate repetitive, low-value human tasks such as data entry or simple workflows. While incredibly functional, bottlenecks occur when processes become too complex or require human judgment. These systems lack the flexibility to adapt to dynamic business environments or complex, strategic decision-making processes. Agentic AI changes that. It introduces systems that automate tasks, make informed decisions, and continuously learn and collaborate with humans and other agents to scale and improve outcomes far beyond what was previously possible.
Related: AI for the Underdog — Here’s How Small Businesses Can Thrive With Artificial Intelligence
From thought to exponential action
Agentic AI is differentiated by its ability to move beyond simple, prompt-based AI toward executing complex, multistep workflows at scale. Agentic systems are powered by large language models (LLMs). These can act autonomously across varying digital ecosystems, interact with tools and work seamlessly with other agents. This capability shift enables AI systems to perform strategic tasks at a level that scales with growing operational demands, adapting to unforeseen challenges and managing variability systematically.
Instead of relying solely on human inputs, agentic AI systems can plan, execute and iteratively improve upon tasks — scaling business processes exponentially — and freeing up human resources for higher-order strategic thinking and innovation.
In my industry, when you think of AI’s impact on software development, your mind gravitates towards a scenario where the engineers writing code get automated away by AI bots doing the work. Yet, software development involves more than coding. Most of the problems that emerge in this process stem from either a poor set of inputs (requirements and designs) or poor engineering of the solution (organizing software into logical, reusable and scalable components).
Instead, envision an agentic software development team, several AI agents collaborating to handle the entire software development lifecycle, that streamlines product design and planning, architecture, engineering, coding, testing and deployment across multiple projects simultaneously and allows human teams to focus on the creative and commercial aspects of these projects.
AI in discovery
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