Project Manager, AI Adoption

DataArt•Belgrade, MT

25d

About The Position

Our client is an international association of financial industry professionals, bringing together over 200,000 investment experts and utilizing more than 100 diverse applications. The project aims to embed AI capabilities and strategies into multiple business streams, enhancing operational efficiency, decision-making, and innovation. The Project Manager will oversee the integration of AI tools, coordinate between technical and business teams, and drive AI adoption initiatives across departments to deliver measurable business value.

Requirements

5+ years of project or program management experience with a track record of driving technology adoption or innovation projects.
Experience working with AI, machine learning, or data science teams, ideally in enterprise environments.
Strong understanding of AI concepts, tools, and implementation challenges.
Proven ability to manage cross-functional teams and build consensus among diverse stakeholders.
Excellent communication and interpersonal skills.
Familiarity with Agile and change management methodologies.
Ability to translate complex technical concepts into business value.
Background in technology, data science, or AI-related projects.
Experience in organizational change management or digital transformation initiatives.
Comfortable working in a fast-paced, evolving environment with multiple concurrent initiatives.

Nice To Haves

PMP, Agile certification, or equivalent is an advantage.

Responsibilities

Lead planning, coordination, and execution of AI adoption initiatives across diverse business and technical streams.
Collaborate closely with stakeholders to understand business objectives and identify opportunities for AI-enabled solutions.
Drive the implementation of AI tools and technologies, ensuring alignment with organizational goals and readiness for change adoption.
Manage the end-to-end delivery of AI integration projects, including scoping, resource allocation, scheduling, and risk management.
Facilitate communication and collaboration between AI specialists, data scientists, IT teams, and business units.
Monitor AI adoption progress, gather feedback, and implement continuous improvement processes.
Develop and execute change management plans to ensure smooth adoption and user acceptance.
Track and report on key metrics to demonstrate the impact of AI initiatives on business performance.
Foster a culture of innovation and AI literacy within the organization through workshops, trainings, and evangelism.

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