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About the role
- Workplace AI Specialist focusing on AI solutions to improve efficiency at Alimentiv. Responsibilities include needs assessments, training, solution development, and performance measurement.
Responsibilities
- Conducts needs assessments across departments to identify opportunities where AI tools can improve operational efficiency or research outcomes.
- Monitors emerging AI technologies and evaluates their relevance to Alimentiv's operational context.
- Develops roadmaps that align AI opportunities with organizational priorities and realistic implementation timelines.
- Synthesizes industry trends into actionable recommendations tailored to Alimentiv's business environment.
- Evaluates AI platforms and tools against defined use cases, documenting findings in structured assessments.
- Develops lightweight solution prototypes to validate feasibility before full implementation is pursued.
- Prepares business cases that articulate the value and feasibility of proposed AI initiatives for non-technical stakeholders.
- Designs and delivers structured training programs that build AI proficiency across diverse teams and skill levels.
- Produces plain-language reference materials, guides, and job aids that support independent tool use.
- Facilitates workshops and demonstrations that connect AI capabilities to team-specific workflows.
- Provides hands-on support during tool rollouts to accelerate user proficiency and resolve adoption barriers.
- Identifies and addresses adoption obstacles through targeted follow-up and adjusted delivery approaches.
- Establishes communities of practice to enable peer learning and sustained engagement with AI tools.
- Monitors usage data and initiates proactive outreach where additional training or support is indicated.
- Designs and builds proof-of-concept AI solutions that demonstrate practical value to specific business functions.
- Develops working prototypes using no-code and low-code AI platforms to illustrate how AI can be applied to real operational challenges.
- Presents and demonstrates prototype solutions to stakeholders, translating outputs into clear business value.
- Builds demonstrations and prototypes using no-code and low-code AI platforms; production development and system integration remain the responsibility of technical IT and development teams.
- Gathers departmental requirements and communicates them to technical teams in plain language.
- Coordinates cross-functional stakeholders to ensure AI tool configurations align with operational workflows.
- Develops standard operating procedures that integrate AI tools into established team workflows.
- Establishes success metrics that capture both adoption rates and measurable business impact.
- Analyzes usage and performance data to assess initiative effectiveness and identify areas for improvement.
- Prepares reports that communicate AI initiative outcomes clearly to leadership audiences.
- Conducts post-implementation reviews to capture lessons learned and apply findings to future rollouts.
Requirements
- 3+ years of related experience
- (Honours) Bachelor’s degree
- Fluent in English (verbal and written)
- Ability to communicate complex or technical concepts clearly to non-technical audiences (verbal and written)
- Demonstrated ability to build effective working relationships across all organizational levels, including frontline staff and senior leadership
- Experience designing and delivering training programs for diverse adult learners
- Knowledge of change management principles and technology adoption frameworks
- Ability to identify underlying user needs and develop practical, targeted support solutions
- Experience producing user documentation, guides, and job aids that reduce barriers to tool adoption
- Proficiency with no-code and low-code platforms (e.g., Microsoft Copilot Studio, Power Automate, Claude.ai) to configure and demonstrate AI-powered workflows without custom development
- Ability to develop functional proof-of-concept solutions demonstrating AI applicability to specific business problems
- Familiarity with prompt engineering and understanding of large language model capabilities and limitations
- Ability to define and communicate the boundary between enablement-level prototyping and production development requiring IT or developer involvement
- Strong cross-functional collaboration skills and ability to align stakeholders around shared objectives
- Ability to interpret adoption metrics and usage data to prioritize support efforts
- Working knowledge of AI tools sufficient to guide end-user adoption (deep technical expertise not required)
- Familiarity with data privacy principles and responsible AI use in regulated environments
- Experience in clinical research or healthcare is considered an asset
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