New opportunity

Asst Director, AI Healthcare Projects Delivery

Tan Tock Seng Hospital · Singapore

About this role

The Assistant Director, AI Healthcare Projects Delivery, reports to the HEAL Programme Lead and is responsible for guiding clinical and operational teams in transforming AI opportunities into implemented, value-driven solutions. This role involves leading a project delivery team, managing project lifecycles, and ensuring that AI initiatives are successfully integrated into routine healthcare operations. Responsibilities include: Project Delivery and Management: Define project scope, resources, and milestones; manage risks, budgets, and dependencies; and provide direct project leadership. Stakeholder Partnership: Collaborate with clinical, operational, and technical teams, including data scientists and the Digital Innovation Studio, to shape practical solutions and navigate conflicting priorities. Adoption and Utilisation: Oversee workflow changes, user engagement, training, and readiness, while tracking utilisation and addressing adoption barriers. Value Tracking and Reporting: Establish benefit measures, track costs and realised value, and report outcomes to sponsors. AI Implementation: Coordinate specialist input for AI project planning and delivery. Team Leadership: Lead, train, and coach the project delivery team to build capability and independent delivery. Requirements: Candidates should possess relevant qualifications in healthcare, business, IT, or project management, along with substantial experience leading complex digital or transformation projects through implementation. Essential skills include solving operational problems, managing difficult stakeholder relationships, and demonstrating sound judgement in unfamiliar situations. A working understanding of AI concepts, model limitations, evaluation, and human oversight is required. Preferred qualifications include PMP certification, formal change management training, and prior experience in AI project delivery, healthcare, or software development.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Project ManagementChange ManagementAI ImplementationStakeholder ManagementHealthcare OperationsDigital TransformationBenefits TrackingTeam LeadershipWorkflow Optimization

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Operationalizing AI Solutions
The core priority is moving AI from concept to routine clinical practice. You must bridge the gap between technical data science outputs and frontline healthcare workflows, ensuring that AI tools are not just implemented but actively adopted and utilized by clinical staff.
Stakeholder Alignment and Conflict Resolution
You must navigate complex relationships between clinical, operational, and technical teams. Success depends on your ability to secure commitments from stakeholders with competing priorities and translate technical AI requirements into practical, value-driven outcomes.
Benefits Realization and Value Tracking
You are responsible for defining, tracking, and reporting the tangible value of AI projects. This requires establishing clear benefit measures and baselines with sponsors and finance teams to distinguish between expected and evidenced outcomes.
Team Capability Building
Beyond project delivery, you must lead, train, and coach a project delivery team. The goal is to improve their independent delivery capabilities and judgment, ensuring the team can handle complex digital transformation tasks with minimal oversight.

Likely challenges to think through

Managing Resistance to Workflow Changes
Healthcare environments are often resistant to changes that disrupt established clinical routines. Prepare by demonstrating your experience in change management, specifically how you identify adoption barriers and engage frontline users to ensure readiness and sustained utilization.
Navigating Ambiguity in AI Implementation
AI projects often face technical limitations or unexpected model performance issues. Prepare by highlighting your ability to exercise sound judgment in unfamiliar situations, specifically how you escalate issues to sponsors with clear, actionable options rather than just identifying problems.
Influencing Without Direct Authority
You must coordinate across various departments where you may not have direct line authority over clinical or technical staff. Prepare by providing examples of how you have negotiated commitments and maintained project momentum through setbacks by building consensus and trust.

Practice your answers

Technical practice

AI Implementation Lifecycle

What to coverDescribe the end-to-end process of integrating an AI solution into a clinical environment. Focus on the transition from pilot to routine operations, including the necessity of human oversight, model monitoring, and the specific challenges of healthcare workflows.

Benefits Tracking and Realization

What to coverExplain how you establish and track benefit measures for digital transformation projects. Discuss the importance of setting baselines with finance or evaluation teams and how you distinguish between expected and evidenced value when reporting to sponsors.

Managing AI Model Limitations

What to coverHow do you account for model limitations and potential performance drift during the project planning phase? Suggestion: Address how you communicate these technical constraints to non-technical clinical stakeholders to manage expectations and ensure patient safety.

Change Management in Healthcare

What to coverDetail your approach to driving user adoption for new digital tools in a clinical setting. Focus on strategies for managing workflow changes, training, and addressing resistance from frontline staff.

Project Risk and Dependency Management

What to coverWhen managing complex digital projects, how do you identify and mitigate dependencies between technical teams, such as data scientists, and operational stakeholders? Explain your process for escalating unresolved decisions to sponsors.

Governance and Specialist Coordination

What to coverHow do you navigate governance structures when coordinating between diverse groups like the Digital Innovation Studio and clinical departments? Discuss how you ensure specialist input is integrated effectively without stalling project momentum.

Utilisation Monitoring

What to coverWhat metrics do you prioritize to track the successful adoption of an AI tool post-implementation? Explain how you use user feedback and utilization data to recommend iterative improvements or necessary workflow adjustments.

Resource and Scope Definition

What to coverDescribe your methodology for defining project scope and resource allocation in an environment with competing priorities. Suggestion: Emphasize how you balance technical requirements with operational capacity and budget constraints.

Behavioural practice

Navigating Conflicting Stakeholder Priorities

What to coverDescribe a situation where you had to reconcile conflicting requirements between clinical, operational, and technical stakeholders. Explain the steps you took to secure commitment and maintain project momentum.

Leading Through Ambiguity

What to coverProvide an example of a project where you faced an unfamiliar problem or a significant setback. Detail how you exercised independent judgment to develop a practical recommendation and how you adapted your strategy.

Coaching and Team Development

What to coverShare an experience where you coached a team member to improve their delivery capability or decision-making. Focus on the specific feedback you provided and the resulting impact on their independence.

Influencing Without Direct Authority

What to coverGive an example of a time you had to secure buy-in from stakeholders who did not report to you. Explain how you built the relationship and navigated the organizational structure to achieve the desired outcome.

Sharpen your knowledge

Topics to prepare

AI Implementation Lifecycle in Healthcare
Review the stages of AI deployment from pilot to routine clinical operation. Exercise: Map a hypothetical AI tool (e.g., a diagnostic support algorithm) to the specific clinical workflow, identifying where human oversight and model monitoring are required to ensure safety and adoption.
Benefits Realization and Value Tracking
Understand how to distinguish between projected and realized value in digital health projects. Exercise: Create a template for a project dashboard that tracks both quantitative metrics (e.g., time saved per patient) and qualitative feedback, ensuring alignment with sponsor expectations.
Change Management in Clinical Environments
Study frameworks for managing resistance to new technology in high-pressure healthcare settings. Exercise: Develop a communication plan for a clinical team that addresses potential workflow disruptions caused by a new AI tool, focusing on user engagement and training readiness.

Skills to revise

Stakeholder Negotiation and Conflict Resolution
Practice navigating conflicting priorities between technical teams and clinical staff. Exercise: Role-play a scenario where a data scientist and a clinician disagree on model performance versus clinical utility, focusing on how to secure commitments and move the project forward.
Project Risk and Dependency Management
Develop techniques for managing complex project interdependencies in a hospital setting. Exercise: Create a risk register for an AI implementation project that specifically accounts for technical dependencies (e.g., data integration) and operational dependencies (e.g., staff training schedules).
Team Coaching and Capability Building
Refine the ability to mentor junior project staff to work independently. Exercise: Draft a structured feedback session plan for a team member who has struggled with a difficult stakeholder, focusing on coaching them to exercise independent judgment in future interactions.

Your preparation checklist

Prepare a case study on AI-driven clinical workflow transformation
Develop a structured walkthrough of a past digital transformation project. Focus on how you identified an operational problem, managed conflicting stakeholder priorities between clinical and technical teams, and successfully integrated a new tool into routine operations.
Draft a framework for AI project benefit tracking
Create a sample template or methodology for measuring the success of an AI implementation. Include how you would establish baselines, track realized value versus expected outcomes, and report these findings to senior leadership or project sponsors.
Formulate examples of managing resistance to change
Prepare specific anecdotes demonstrating your change management approach. Focus on instances where you navigated adoption barriers, secured buy-in from frontline staff, and provided training or support to ensure long-term utilization.
Develop a leadership philosophy for project delivery teams
Outline your approach to coaching and mentoring junior project managers. Provide evidence of how you have improved a team's independent delivery capability, delegated tasks effectively, and maintained quality standards during complex project lifecycles.
Prepare strategic questions for the HEAL Programme Lead
Draft thoughtful questions regarding the current governance structure for AI projects at Tan Tock Seng Hospital, how the Digital Innovation Studio interacts with clinical teams, and the primary challenges the organization faces in scaling AI solutions.

Availability has not yet been verified. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

KEEP EXPLORING

Similar AI jobs

Related skills and specializations in Singapore. Matched to this role, not your profile.

Explore more jobs

Finding similar opportunities…