Agentic – ABCDQI

Agentic AI: Enhancing Citizen Services for Agencies

Definition: Agentic AI refers to autonomous AI systems that proactively make decisions and gather information to assist with tasks, such as facilitating citizen inquiries or applications.
Benefits for Agencies and Citizens: Enhances government interactions by expediting application processes and improving the overall citizen experience through chatbots and internal tools.
Implementation Challenges: Agencies face security and fairness concerns while implementing agentic AI, necessitating adherence to strict data handling and privacy policies.
Employee Integration: Training programs are crucial to help employees adapt to agentic AI, emphasizing that it will augment their roles rather than replace them, while also considering cost implications.
Future of Government Services: Agentic AI has the potential to revolutionize government services by improving efficiency, but must prioritize data security and privacy to be effective.

Emerging Technology: Agentic AI is becoming a transformative system capable of independent reasoning, planning, remembering, and acting without ongoing human oversight, enhancing efficiency and service quality in software systems.
Organizational Readiness: At GovInsider’s Festival of Innovation 2025, no audience members felt prepared for agentic AI adoption, despite widespread recognition of its potential benefits, as highlighted by survey results.
Human-AI Collaboration: In the public sector, agentic AI can work alongside human roles, such as facility managers, to streamline processes and provide time-efficient solutions by autonomously diagnosing and addressing issues.
Strategic Frameworks: A strategic assessment of an organization’s goals and capabilities is crucial for effective AI deployment, emphasizing the need for integration, quality data availability, and alignment with business objectives.
Workforce and Regulatory Preparation: Leaders stress the importance of fostering a culture of readiness and regulatory frameworks to ensure successful agentic AI adoption, highlighting the need for clear value understanding to avoid ineffective implementations.

Leadership in AI Adoption: Singapore leads the way in public sector AI adoption, fueled by strategic investments in digital infrastructure and robust data governance.
Emergence of Agentic AI: Agentic AI represents a shift towards autonomous systems capable of nuanced judgment and real-time responsiveness, augmenting human capabilities rather than replacing them.
Importance of Quality Data: The effectiveness of AI agents relies on high-quality, well-structured contextual data to align with policy objectives and ensure adaptability.
Real-World Applications: Early use cases in Singapore demonstrate Agentic AI’s value in streamlining processes, identifying policy bottlenecks, and providing decision support in critical situations.
Strategic and Ethical Challenges: As Singapore explores Agentic AI, it faces strategic and ethical questions regarding autonomy, accountability, and ensuring that these systems deliver measurable benefits to citizens.

AI agents incur costs for models, GPUs, cloud storage, and virtual avatars, which can escalate quickly with usage.
IT departments will face substantial expenses related to agentic AI implementation within the next 3-5 years.
Key cost considerations include tracking agent interactions, resource utilization, and overall returns on investment.
Financial oversight is essential; utilizing "financial agents" and implementing budget monitoring mechanisms can help manage expenses.
Collaborative planning involving stakeholders from various sectors is necessary to identify viable agentic AI projects and avoid costly missteps.