  Cyber threats continue to evolve in complexity, thereby traditional Cyber
Threat Intelligence (CTI) methods struggle to keep pace. AI offers a potential
solution, automating and enhancing various tasks, from data ingestion to
resilience verification. This paper explores the potential of integrating
Artificial Intelligence (AI) into CTI. We provide a blueprint of an AI-enhanced
CTI processing pipeline, and detail its components and functionalities. The
pipeline highlights the collaboration of AI and human expertise, which is
necessary to produce timely and high-fidelity cyber threat intelligence. We
also explore the automated generation of mitigation recommendations, harnessing
AI's capabilities to provide real-time, contextual, and predictive insights.
However, the integration of AI into CTI is not without challenges. Thereby, we
discuss ethical dilemmas, potential biases, and the imperative for transparency
in AI-driven decisions. We address the need for data privacy, consent
mechanisms, and the potential misuse of technology. Moreover, we highlights the
importance of addressing biases both during CTI analysis and AI models
warranting their transparency and interpretability. Lastly, our work points out
future research directions such as the exploration of advanced AI models to
augment cyber defences, and the human-AI collaboration optimization.
Ultimately, the fusion of AI with CTI appears to hold significant potential in
cybersecurity domain.
