Driving automation, smarter decision-making, and digital innovation through agentic AI.
AI with Purpose: Exploring Agentic Intelligence
Agentic AI refers to artificial intelligence systems designed to operate independently, making decisions and taking actions to achieve specific goals, especially in complex, ever-changing environments.
Key Characteristics:
Autonomous: Operates with minimal human input, making its own decisions and executing tasks.
Goal-Driven: Pursues defined objectives using reasoning, planning, and execution.
Adaptive: Continuously adjusts to real-time changes in its environment.
Persistent: Functions over extended periods, not just in response to isolated prompts.
Agentic AI vs Generative AI
Agentic AI
Achieves goals through decision-making and action
Generative AI
Generates creative or informative content based on prompts
Agentic AI
High – can operate continuously and interact with systems
Generative AI
Low – Requires a user prompt to function
Agentic AI
Persistent, long-term memory used for reasoning and planning
Generative AI
Varies – some generative AI has session based or persistent memory, but does not autonomously reason over long-term goals
Agentic AI
AI agents that automate workflows, trading bots, self-driving vehicles
Generative AI
ChatGPT, DALL-E, Copilot
Agentic AI in Healthcare
Agentic AI is transforming healthcare — not by replacing people, but by enhancing their ability to deliver high-quality, patient-centred care.
By supporting a range of operational and clinical tasks, agentic AI allows providers to spend more time where it matters most: with patients.
As healthcare systems continue to evolve, we can expect agentic AI to drive more personalized and sophisticated treatment plans, stronger predictive analytics to support early intervention, greater access to care in underserved and remote communities, lower healthcare costs without compromising quality, and improved work-life balance for clinicians and care teams.
Smarter Systems, Better Care: The Power of Agentic AI
Greater Specialization
Agentic models are explicitly designed to carry out very granulartasks, enabling greater specialization of roles compared toprevious automation systems
Multiple agentic roles can be created rapidly and work in tandem
Improved Informational Trustworthiness
Greater cognitive reasoning of Agentic AI systems reduceslikelihood of suffer from ‘invented information’
Significantly greater ability to sift and differentiate information sources for quality & reliability
Enhanced Innovation
Enhanced judgement and powers of execution make Agentic AI systems ideal for experimentation and innovation
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