Webinar Description
Key Takeaways
- Explores how artificial intelligence is reshaping both cyber defence capabilities and threat actor methodologies
- Designed for cybersecurity professionals, threat intelligence analysts, SOC teams and security decision-makers
- Addresses practical integration of AI technologies into existing security workflows
- Relevant to high-security sectors including finance, government, critical infrastructure and technology
- Hosted by Recorded Future as a virtual webinar with expert speakers and interactive discussion
Introduction
Recorded Future is hosting a webinar examining the convergence of artificial intelligence and cybersecurity, addressing how AI technologies are fundamentally altering the threat landscape while simultaneously offering new defensive capabilities. The session targets cybersecurity professionals, threat intelligence analysts and security leaders seeking to understand both the risks and opportunities presented by AI in security operations. As threat actors increasingly incorporate machine learning and automation into their attack methodologies, organisations face mounting pressure to adopt AI-driven intelligence capabilities to maintain effective defences.
About This Event
This virtual webinar brings together expert speakers to discuss real-world applications of AI in cybersecurity contexts. The format combines presentation content with interactive question-and-answer segments, allowing participants to engage directly with subject matter experts on specific challenges facing their organisations. Recorded Future, a threat intelligence platform provider, hosts the session as part of its ongoing efforts to share research and operational insights with the broader security community.
The programme focuses on delivering actionable guidance rather than theoretical discussion, with speakers drawing on practical experience to illustrate how AI-driven intelligence can enhance threat detection and incident response capabilities.
AI as Both Defensive Tool and Emerging Threat Vector
The dual nature of artificial intelligence in cybersecurity presents organisations with a complex strategic challenge. On the defensive side, machine learning algorithms can process vast quantities of threat data at speeds impossible for human analysts, identifying patterns and anomalies that might otherwise escape detection. AI-powered systems can correlate indicators of compromise across multiple data sources, prioritise alerts based on contextual risk factors, and automate routine investigative tasks that would otherwise consume significant analyst time.
However, the same capabilities that make AI valuable for defenders are increasingly being exploited by threat actors. Adversaries are using machine learning to craft more convincing phishing campaigns, automate reconnaissance activities, and develop malware that can adapt to evade detection systems. This arms race dynamic means that organisations cannot afford to view AI adoption as optional; those who fail to incorporate intelligent automation into their security operations risk falling behind adversaries who face no such hesitation.
The webinar addresses this tension directly, examining how security teams can leverage AI-driven threat intelligence while remaining alert to the evolving tactics of AI-equipped adversaries.
Integrating AI Into Security Operations
One of the persistent challenges facing security operations centres is the volume of alerts generated by modern detection systems. Analysts frequently contend with thousands of notifications daily, many of which prove to be false positives or low-priority events. This alert fatigue can lead to genuine threats being overlooked or investigated too slowly to prevent damage.
AI-driven intelligence platforms address this challenge by applying contextual analysis to incoming data, automatically enriching alerts with relevant threat intelligence and assigning risk scores based on multiple factors. This allows analysts to focus their attention on the incidents most likely to represent genuine threats, improving both detection rates and response times.
The webinar explores best practices for integrating these capabilities into existing workflows, recognising that technology adoption alone is insufficient without corresponding changes to processes and team structures. Effective implementation requires careful consideration of how AI tools complement human expertise rather than attempting to replace it entirely.
Industry Context and Regulatory Considerations
The growing sophistication of cyber threats has prompted increased regulatory attention across multiple sectors. Financial services organisations face stringent requirements around operational resilience and incident reporting. Critical infrastructure operators must comply with evolving frameworks designed to protect essential services from disruption. Government agencies operate under specific mandates regarding threat information sharing and defensive capabilities.
For organisations in these sectors, AI-driven threat intelligence offers a means of meeting regulatory expectations while managing the practical constraints of limited security budgets and persistent talent shortages. Automated analysis and response capabilities can help smaller teams achieve coverage levels that would otherwise require significantly larger headcounts.
The webinar content is particularly relevant to these high-security environments, where the consequences of successful attacks extend beyond financial losses to potential impacts on public safety and national security.
Who Should Attend
The session is designed for professionals with direct responsibility for cybersecurity strategy and operations. This includes threat intelligence analysts seeking to understand how AI can enhance their investigative capabilities, SOC team members looking to improve detection and response workflows, and security managers evaluating technology investments for their organisations.
Chief Information Security Officers and other senior decision-makers will find value in the strategic perspective on AI adoption, including discussion of how to balance innovation with risk management. The content assumes familiarity with fundamental cybersecurity concepts but does not require deep technical expertise in artificial intelligence or machine learning.
Professionals from sectors with elevated security requirements—including financial services, government, critical infrastructure and technology—will find the discussion particularly applicable to their operational contexts.
The Evolving Threat Intelligence Discipline
Threat intelligence has matured significantly as a discipline over the past decade, evolving from simple indicator feeds to sophisticated analytical programmes that inform strategic decision-making. Modern threat intelligence operations require the ability to collect, process and analyse data from diverse sources at scale, correlating technical indicators with geopolitical developments, criminal ecosystem dynamics and sector-specific risk factors.
AI technologies are accelerating this evolution by enabling analysis at volumes and speeds that exceed human capacity. Machine learning models can identify emerging threat campaigns before they reach widespread deployment, track the evolution of adversary infrastructure, and predict likely attack vectors based on historical patterns and current conditions.
This webinar contributes to the ongoing professional development of threat intelligence practitioners by examining how these capabilities are being applied in operational contexts and what they mean for the future of the discipline.