AI FOR TECH LEADERS

AI Adoption and Operationalisation for Technology leaders

Gain insight into Strategic AI implementation, AI security, team skills development, and ethics.

Effective AI risk management involves a systematic approach to identifying, evaluating, and mitigating AI risks within an organisation. It is essential for protecting sensitive data, ensuring compliance, and maintaining seamless AI operations. It also fosters innovation, provides a competitive advantage, and bolsters supply chains.

What you'll learn

DURATION: 4 HOURS

AI Strategy and Implementation for IT Leaders: Focused on guiding AI adoption within the organisation, including planning, deployment, and aligning with business goals.

AI Security and Ethical AI: Specialised training on AI-specific security risks, ethical concerns, and best practices for safe implementation.

Skill Development and Team Building: Courses that outline the technical skills required for AI security, helping Helen identify and develop the necessary competencies in her team.

Course Overview

    • Developing a roadmap for AI adoption within IT infrastructure

    • Aligning AI deployment with overall business objectives

    • Integrating AI projects with existing systems and workflows

    • Technical requirements for implementing AI solutions

    • Infrastructure and resource planning for AI applications

    • Managing the lifecycle of AI projects, from pilot to production

    • Understanding unique security challenges in AI systems

    • Protecting data and privacy in AI applications

    • Mitigation strategies for AI vulnerabilities and attack vectors

    • Ethical considerations in AI system design and deployment

    • Addressing bias and fairness in AI algorithms

    • Guidelines for implementing transparent and explainable AI

    • Identifying required skills for AI support and maintenance

    • Training on essential AI tools, frameworks, and technologies

    • Establishing team roles and responsibilities for AI operations

    • Fostering collaboration between IT, security, and AI teams

    • Ensuring secure practices across departments for AI use

    • Building a culture of awareness and continuous improvement in AI security

    • Methods for measuring AI effectiveness and value

    • Scaling successful AI projects across the organisation

    • Continuous monitoring and adaptation of AI systems

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