AI Market Intelligence & Enablement Analysts

Our client, a major mining organisation, is seeking two highly analytical and commercially aware AI Market Intelligence & Enablement Analysts to support the organisation's enterprise AI journey. This is not a traditional Data Science or AI Engineering role. Instead, the successful candidates will operate at the intersection of AI strategy, research, business enablement, technology scouting, risk evaluation, and executive communication .

The role will act as the organisation's "AI radar", continuously monitoring global developments in artificial intelligence, identifying practical enterprise use cases, evaluating opportunities and risks, and translating emerging AI trends into actionable insights for executive leadership. The successful candidates will play a critical role in shaping the organisation's AI adoption strategy as it evolves from productivity-focused AI tools towards future-state Agentic AI and data-cloud-native architectures.

Reporting directly to the Chief Information Officer (CIO) and the Director: Enterprise Data & AI Solutions , this position offers significant exposure to executive decision-making and enterprise technology strategy.

Key Responsibilities

Market Intelligence & Technology Scanning Continuously monitor global AI developments, including: Generative AI Agentic AI Foundation Models AI Platform Ecosystems Cloud AI Services Regulatory developments Industry adoption trends Research and evaluate emerging AI vendors, products, and platforms. Identify technology opportunities relevant to large-scale enterprise and mining operations.

Distinguish practical business value from market hype. Produce concise executive summaries and recommendations on relevant AI developments.

Requirements

AI Use-Case Evaluation Assess AI use cases proposed by business units across the organisation. Evaluate: Business value Strategic alignment Implementation feasibility Cost-benefit considerations Data readiness Technical complexity Identify existing enterprise capabilities that may address similar requirements. Recommend build, buy, or pilot approaches where applicable.

Risk Assessment & Governance Conduct structured AI risk assessments for all evaluated use cases. Assess: Data privacy implications Security exposure Model reliability Hallucination risks Regulatory and compliance considerations Ethical AI concerns Develop formal risk evaluation documentation for review and sign-off by executive leadership.

Support responsible AI adoption in alignment with enterprise governance practices. Thought Leadership & Internal Enablement Translate complex AI developments into business-friendly insights. Create: Executive presentations Research reports Thought leadership articles Internal newsletters AI awareness content Deliver recurring updates and AI trend briefings to senior leadership.

Assist in building AI literacy across the organisation. Act as a trusted advisor on emerging AI capabilities and business opportunities. Stakeholder Engagement Engage with: CIO Director: Enterprise Data & AI Solutions Business Executives Technology Teams Innovation Teams Governance and Risk Functions Facilitate discussions around AI opportunities and priorities.

Present findings and recommendations to executive audiences. Build strong relationships across business and technology functions. Minimum Requirements Education Bachelor's Degree in one of the following: Information Technology Computer Science Data Science Engineering Business Information Systems Economics Business Management Strategic Management Research-related disciplines Equivalent practical experience will also be considered.

Experience Essential Minimum 3 years' experience in: Research Technology Strategy Market Intelligence Management Consulting Innovation AI Enablement Digital Transformation Demonstrated exposure to AI and Machine Learning technologies. Experience researching and analysing emerging technologies. Ability to distil complex technical concepts into executive-ready communication.

Proven experience evaluating technology opportunities, business cases, and strategic initiatives. Experience engaging with senior stakeholders and leadership teams. Strong written communication and presentation development skills. Technical Knowledge Candidates should possess knowledge of: Artificial Intelligence (AI) Generative AI Large Language Models (LLMs) AI Market Trends AI Platforms and Vendors Product and Technology Evaluation Digital Transformation Enterprise Technology Strategy Responsible AI Data Privacy Cybersecurity Fundamentals Risk Management Governance and Compliance Essential Skills Research & Analysis Technology scouting Market intelligence Competitive analysis Trend identification Strategic evaluation Business case assessment Communication Executive presentations Report writing Storytelling with data Stakeholder engagement Thought leadership development AI & Technology Knowledge of AI ecosystems Understanding of AI tools and platforms Awareness of cloud-enabled AI capabilities Emerging AI architecture trends Governance & Risk AI risk assessment Data privacy principles Security awareness Regulatory considerations Responsible AI practices Advantageous Experience The following will be highly beneficial: Experience within: Mining Resources Manufacturing Telecommunications Financial Services Large enterprise environments Exposure to: Microsoft Copilot Google Gemini OpenAI Claude Azure AI Services AWS AI Services Google Cloud AI Knowledge of: Agentic AI architectures Autonomous AI systems Cloud computing platforms Enterprise Data & AI ecosystems Behavioural Competencies The successful candidate will demonstrate: Strategic Thinking Curiosity and Continuous Learning Commercial Awareness Analytical Thinking Executive Presence Strong Communication Skills Innovation Mindset Stakeholder Management Attention to Detail Critical Thinking Influencing Ability Accountability Collaboration Success Measures Success in this role will be measured through: Quality and relevance of AI market intelligence delivered.

Effectiveness of AI opportunity assessments. Adoption and utilisation of AI insights across the business. Executive stakeholder satisfaction. Quality of AI risk assessments and recommendations. Contribution to the enterprise AI roadmap. Thought leadership and awareness initiatives delivered. Ability to identify and communicate high-value AI opportunities before competitors.