Position Summary:
The Chief AI Officer (CAIO) is responsible for defining and leading the organization's enterprise-wide Artificial Intelligence strategy, driving AI-enabled transformation, innovation, and business value creation across all functions.
The CAIO will oversee the development and deployment of Generative AI, Machine Learning, and Intelligent Automation capabilities to enhance decision-making, optimize operations, and create differentiated customer experiences.
As a key member of the Executive Leadership Team, the CAIO partners closely with the CEO, CIO, CTO, CDO, and business leaders to embed AI into the organization's core operating model, products, and services. The role also ensures that AI is developed and deployed in a responsible, ethical, and compliant manner, balancing innovation with risk governance and regulatory requirements.
Job Descriptions:
1. AI Strategy & Enterprise Transformation
- Define and execute the enterprise AI strategy aligned with business vision and digital transformation roadmap.
- Identify high-impact AI use cases across business units to drive efficiency, growth, and competitive advantage.
- Establish AI as a core capability embedded across products, operations, and decision-making processes.
2. Generative AI & Intelligent Automation
- Lead the adoption of Generative AI, Machine Learning, and Intelligent Automation across the organization.
- Develop AI platforms, models, and frameworks to enable scalable deployment of AI solutions.
- Drive automation of business processes through AI-powered workflows and decision systems.
3. AI Platform, Data & Ecosystem Enablement
- Define AI architecture, platforms, and tooling in collaboration with Data and Cloud functions.
- Ensure availability of high-quality data, MLOps capabilities, and scalable AI infrastructure.
- Build internal and external AI ecosystems, including partnerships with technology providers and startups.
4. Responsible AI Governance & Risk Management
- Establish Responsible AI framework covering ethics, fairness, transparency, privacy, and security.
- Ensure compliance with regulatory requirements related to AI usage and data protection.
- Manage AI-related risks including model bias, hallucination, misuse, and operational risk.
5. AI-driven Innovation & Business Value Creation
- Drive AI-enabled innovation across products, customer experience, and operational excellence.
- Partner with business leaders to translate AI capabilities into measurable business outcomes.
- Develop AI-powered insights, personalization, and decision intelligence to enhance competitiveness.
Qualifications:
- MBA/ Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, Engineering, or a related field. PhD is highly preferred.
- Minimum 12–15 years of progressive experience in AI/ML, Data Science, Advanced Analytics, or Technology leadership roles.
- At least 5 years of executive or senior leadership experience driving enterprise AI, data-driven transformation, or digital innovation initiatives.
- Proven track record in building and scaling AI/ML platforms, data products, or intelligent automation at enterprise scale.
- Strong experience in Generative AI, Machine Learning, Deep Learning, NLP, and AI-driven decision systems.
- Solid understanding of AI architecture, MLOps, model lifecycle management, and AI platform engineering.
- Demonstrated experience in translating AI capabilities into measurable business outcomes and commercial value.
- Strong background in AI governance, Responsible AI, model risk management, and regulatory compliance.
- Experience working closely with data, cloud, product, and engineering teams in complex enterprise environments.
- Industry experience in Financial Services, Fintech, Banking, Insurance, Telecommunications, E-commerce, or Digital Platforms is strongly preferred.
- Strong executive presence with the ability to communicate AI strategy, risks, and opportunities to CEO, Board, and non-technical stakeholders.
- Ability to lead high-performing, multidisciplinary teams across AI research, engineering, and applied AI domains.
