Associate Director, Data Systems & AI, Enterprise Competitive Intelligence

Job description

Job Description Summary #LI-Hybrid Location: Hyderabad, India About The Role: Enterprise Competitive Intelligence (ECI) is responsible for gathering, assessing, organizing, and delivering timely, relevant, high-quality competitive intelligence that supports Novartis pipeline, portfolio, and strategic decision-making. As ECI moves from a service-provider model toward a strategic partnership model, the function needs scalable data systems, governed repositories, and AI-enabled workflows that make validated CI accessible, reusable, and useful across business units. In this role you will shape and govern the ECI data systems and AI agenda: building and leading the CI knowledge layer, ensuring CI data is available, searchable, API-ready and usable by AI, and enabling repeatable AI-assisted workflows that improve speed, quality, consistency and enterprise leverage. The role will act as the bridge between ECI, business-unit insights teams, Data Digital & IT (DDIT), enterprise knowledge management teams (e.g. NKC), and relevant external partners to deliver pragmatic solutions while preparing ECI for future AI-enabled ways of working.  Job Description Key Responsibilities: Strategic Vision and Roadmap • Drive the ECI Data Systems and AI vision, roadmap and delivery plan, aligned to ECI priorities, Novartis business-unit needs and enterprise technology direction. • Translate ECI’s ambition for a single, trusted CI knowledge layer into sequenced initiatives, milestones, governance forums and investment decisions. • Maintain a balanced build/buy/partner perspective, evaluating whether capabilities should be built internally, sourced from vendors, or co-developed with partners. • Represent Data Systems and AI on the ECI Leadership Team and support ECI Steering Committee discussions on AI, repositories, data governance, interoperability, prioritization and funding. CI Repository and Knowledge Layer • Lead the design and implementation of the ECI repository / knowledge layer, consolidating curated CI outputs and enabling clear navigation across TAs, business units, congress outputs, Strategic CI, and other CI domains. • Ensure CI data and outputs are findable, reusable, appropriately tagged and governed, including metadata, taxonomy, ownership, access rights and archival rules • Drive interoperability with key enterprise and business-unit systems • Ensure the repository is not only a document store, but evolves toward an AI-ready data product that can be consumed by humans, AI agents and other approved enterprise applications. AI-Enabled Workflows and Automation • Identify, prioritize and deliver AI-assisted workflows that reduce manual effort and improve quality in recurring ECI activities • Develop reusable templates, prompts, workflow patterns and validation checkpoints that ECI associates can apply consistently across therapeutic areas and business-unit requests. • Partner with ECI leaders and specialists to define future-state workflows before tool selection, ensuring AI augments expert judgement rather than replacing critical CI interpretation. • Support pilots and MVPs over validated CI content and potential CI agent capabilities anchored in governed internal data. Governance, Quality and Access Management • Establish data governance standards for CI assets, including lineage, ownership, lifecycle, metadata, access policies, quality checks and decision rights. • Ensure CI data is accurate, current, appropriately curated and protected, with expert oversight and clear escalation routes for sensitive or uncertain content. • Coordinate access management across ECI, insights teams and broader approved user groups, balancing enterprise accessibility with confidentiality, compliance and business-unit needs. • Work with Legal, ERC, DDIT, knowledge-management teams and business owners to ensure AI-enabled CI workflows comply with Novartis policies, privacy, security and responsible AI expectations. Stakeholder Engagement and Enterprise Partnership • Serve as the primary ECI interface for data systems and AI topics with business-unit CI / insights leaders, ECI TA Leads, Strategic CI, DDIT, NKC, and other platform owners • Build alignment across stakeholders on data standards, workflow priorities, repository design, access model, change-management needs and success measures. • Create feedback loops with end users to ensure systems and AI workflows improve usability, relevance, trust and adoption across ECI and its stakeholders. • Actively promote cross-BU reuse of CI outputs and reduce duplication by making the right intelligence easier to find, compare and apply. Delivery, Vendor and Financial Discipline • Run a lightweight but rigorous delivery model across Data Systems and AI workstreams, including backlog management, MVP demos, milestone tracking, dependency management and risk escalation. • Evaluate and manage vendors and pilots in the AI for CI space, including clarity on expected value, data requirements, procurement implications, integration feasibility and exit criteria. • Manage the Data Systems and AI budget / project spend once approved, supporting timely forecasting, vendor decisions and efficient allocation of scarce resources. • Help ECI leadership make transparent trade-offs across repository build, AI workflow development, vendor pilots, external data feeds and internal technical capacity. Talent, Capability Building and Change Management • Build ECI capability in data systems, AI literac