Everyone is talking about AI but very few are actually implementing it end-to-end.

This role is not about building models in isolation. This is a senior transformation role focused on enterprise adoption of AI and intelligent automation, not a pure technical AI research or model-building position.

Candidates with strong backgrounds in digital, data, automation, or large-scale transformation — and recent exposure to AI-driven initiatives — are highly relevant, even if their career did not start in “AI-specific” roles.

What You Will Actually Be Solving (Not Just Managing)

• Disconnected AI pilots that never scale beyond POCs

• Legacy systems blocking AI integration

• High OPEX in customer support, network operations, and manual workflows

• Lack of AI strategy alignment between tech, product, and business units

• Pressure from leadership to modernise while maintaining operational stability

This is a transformation mandate, not a research role.

Core Responsibilities

1. Enterprise AI Strategy & Execution

• Define and drive AI transformation roadmap across business units (Network, CX, Digital, Operations)
• Identify high-impact AI use cases tied directly to revenue, efficiency, and customer retention
• Partner with C-suite to align AI investments with commercial priorities

2. AI Use Case Deployment (Real, Not Theoretical)

Lead implementation of AI initiatives such as:

• Predictive network maintenance
• AI-driven customer service automation
• Churn prediction and retention models
• Intelligent pricing & personalisation engines
• AI-enabled fraud detection and risk systems

You will be accountable for scaling solutions beyond pilot stage.

3. Cross-Functional Stakeholder Leadership

• Work with CTO, CDO, Product, and Operations teams
• Translate technical AI capabilities into business language
• Align vendors, internal AI teams, and external partners
• Navigate organisational resistance to change (very real in telco)

4. Vendor & Ecosystem Management

• Evaluate AI vendors, platforms, and solutions (GenAI, MLOps, automation tools)
• Avoid overinvestment in hype-driven tools with low ROI
• Build scalable AI partnerships within the telco ecosystem

5. Operational Transformation & Cost Optimisation

• Reduce manual workflows using AI automation
• Improve operational efficiency across network and service operations
• Drive measurable KPIs (cost savings, speed, CX improvements)

Experience & Background

• 10–15+ years of experience in Digital Transformation, Data, Technology, Product, or Enterprise Change roles within Telco, Tech, Consulting, or large-scale enterprise environments
• Proven track record leading complex, cross-functional transformation programmes (e.g. digitalisation, automation, data transformation, or AI-enabled initiatives)
• Hands-on involvement in deploying advanced analytics, automation, machine learning, or AI-driven solutions in real business settings — not just conceptual strategy
• Strong foundation in technology, data, digital, or AI-related disciplines through formal education and/or substantial enterprise experience
• Ongoing learning in AI and emerging technologies is welcomed, including formal degree programmes or structured postgraduate study
• Surface-level certifications, short bootcamps, or purely theoretical AI credentials without proven large-scale implementation experience will not be considered a substitute for hands-on transformation leadership
• Consulting (McKinsey, BCG, Accenture, etc.) + AI programmes with proven track record delivering large-scale tech or AI initiatives (not just strategy decks)

This role does not require a decade of pure AI experience. It requires senior leaders who have evolved alongside emerging technologies and successfully integrated new capabilities into legacy and enterprise environments.

AI & Technology Exposure

• Demonstrated experience implementing AI, automation, advanced analytics, or data-led initiatives within operational or customer-facing functions
• Strong understanding of how AI integrates into enterprise systems (CX platforms, network operations, CRM, billing, digital channels, etc.)
• Ability to translate AI capabilities into measurable business outcomes such as cost optimisation, service automation, customer experience enhancement, and operational efficiency
• We are not looking for a research scientist or pure AI engineer but we are looking for a transformation leader who can operationalise AI at scale. (Practical, Not Academic)

Leadership & Stakeholder Capability

• Experience working directly with C-suite stakeholders (CTO, CIO, CDO, COO, CEO) on strategic technology or transformation agendas

• Strong ability to align technical teams, business units, and external vendors within large, matrixed organisations

• Credibility to influence both technical specialists and non-technical leadership in a traditionally structured industry such as telecommunications

Industry & Environment Fit

• Experience in Telco, Digital Infrastructure, SaaS, Consulting, or other large-scale, regulated, or legacy-heavy environments is highly preferred
• Prior exposure to enterprise-scale systems, legacy integration challenges, and organisational change management
• Familiarity with vendor ecosystems, system integrators, and enterprise technology deployment cycles

What Will Make a Candidate Stand Out

• Experience scaling initiatives beyond pilot stage into enterprise-wide adoption
• Background in digital transformation, data transformation, or automation programmes prior to recent AI initiatives
• Ability to balance innovation with operational stability in complex, legacy environments
• Commercial mindset with a focus on ROI, efficiency, and measurable transformation impact