Issued by POMIAGER
In today’s rapidly evolving business landscape, staying ahead of the curve requires embracing innovation and leveraging new technologies. Innovation is a social process within and across companies. It requires visionaries, challengers, communicators, champions and many more contributors who are prepared to share, evaluate and elevate ideas. At Pomiager we incentivize and support you in your innovation journey. Our comprehensive approach covers process tracing and mapping to pinpoint value opportunities, architecting a modern data foundation, leveraging agentic architecture, and upskilling your workforce to drive sustainable growth and operational excellence.
Description:
Agentic AI empowers autonomous decision-making, reshaping industries through enhanced efficiency, innovation, and adaptability, crucial for competitive edge in today's dynamic professional landscape.
Goals:
1. Understand and implement autonomous AI systems.
2. Develop decision-making capabilities in AI agents.
3. Enhance skills in ethical AI design and deployment.
4. Address AI integration challenges in organizational roles.
5. Foster innovation and strategic thinking through AI.
Competences:
Competence in agentic AI involves understanding AI that acts autonomously, making decisions and performing tasks. It requires knowledge in AI programming, decision-making algorithms, and ethical implications, enabling professionals to develop, implement, and manage AI systems effectively.
Knowledge :
1. Fundamentals of AI agents and their architecture.
2. Theoretical foundations of agent behavior and decision-making.
3. Principles of autonomous systems and their application.
4. Ethical considerations in AI agent deployment.
5. Methods for evaluating AI agent performance.
6. Theories behind machine learning models and their training.
Skills:
1. Analyze complex datasets using agentic AI tools to extract meaningful insights.
2. Design and implement AI algorithms that mimic human decision-making processes.
3. Develop predictive models to anticipate outcomes and support decision-making.
4. Apply ethical frameworks to evaluate AI-driven decisions in organizational contexts.
5. Integrate agentic AI solutions into existing workflow processes for optimization.
6. Troubleshoot and solve technical issues related to AI system implementations.
7. Conduct simulations and evaluations to refine AI systems' effectiveness.
8. Communicate AI solutions and findings effectively to stakeholders.
9. Adapt AI strategies based on dynamic environmental and computational changes.
10. Collaborate cross-functionally to enhance AI application outcomes.
Evaluation criteria:
test