AI Innovation Analyst

AI Innovation Analyst

Publish Date 07.02.2026

• Roofing Corp of America
• Atlanta, GA
• Posted 6 hours ago

Roofing Corp of America

Job Description - AI Innovation Analyst

Roofing Corp of America (RCA) is a subsidiary of FirstService Corporation (NASDAQ and TSX: FSV), a North American leader in the essential outsourced property services sector. Since inception, RCA has added 16 roofing services companies to its growing portfolio with 29 branch locations across the United States, each differentiated by a unique and localized commercial strategy. RCA has united some of the most respected regional roofing companies into a single, scalable platform - allowing our companies to maintain their local identity while gaining access to resources, technology, and operational excellence. RCA's seasoned and growing Field Support Office drives strategic development, enhances operational efficiencies, and leverages the organization's expanding scale. This central team also facilitates extensive best-practice sharing across our high-performing network of local contractors, ensuring exceptional service and continuous improvement across the organization.

RCA is committed to innovation, safety, and sustainability, empowering our partners to deliver high-quality results with exceptional customer service. For additional information on Roofing Corp of America, please visit www.roofingcorp.com.

Position Details:

The AI Innovation Analyst is a hybrid business, technology, and project execution role responsible for helping RCA identify, evaluate, prototype, implement, and communicate practical AI use / use case development / education across the organization. This role will work directly with executives, business unit leaders, functional managers, frontline staff, IT, Security, Data, and external vendors to turn AI ideas into well-defined, secure, measurable solutions. This role is part business analyst, part project manager, part AI technical resource, and part AI innovation catalyst. The ideal candidate is comfortable facilitating conversations with C-level executives about strategic priorities, while also sitting with field, operations, sales, finance, service, HR, marketing, or IT users to understand how work actually gets done and where AI can remove friction. This includes capturing use cases, documenting requirements, assessing feasibility, coordinating pilots, supporting technical configuration, testing AI tools, measuring outcomes, and helping users adopt approved AI capabilities safely. This is not a pure data scientist, machine learning engineer, or research role. It is a practical enterprise AI enablement role focused on business value, secure adoption, project execution, and hands-on solution facilitation.

Positioning Statement

The AI Innovation Analyst will help RCA turn AI from an emerging technology into a practical, secure, and measurable business capability. This role will work across all levels of the organization - from C-level leaders to frontline staff - to identify opportunities, shape use cases, coordinate pilots, support technical enablement, promote responsible AI use, and help RCA safely scale AI-driven innovation across the enterprise.

Role Purpose

The AI Innovation Analyst will help RCA:

Identify high-value AI use cases with business users

Translate business needs into AI solution requirements

Facilitate AI workshops with executives, managers, and staff-level employees

Support development and configuration of AI prototypes and pilots

Coordinate AI projects from intake through pilot and production readiness

Help ensure AI solutions meet RCA security, governance, and data access requirements

Build prompt templates, AI playbooks, and user enablement materials

Track AI adoption, outcomes, risks, issues, and lessons learned

Serve as a practical translator between business teams, IT, Security, Data, vendors, and leadership

Required Qualifications

Bachelor's degree in Business, Information Technology, Computer Science, Data Analytics, Engineering, Cybersecurity, or a related field; equivalent experience may be considered

4+ years of experience in business analysis, project management / coordination, technology implementation, data/analytics, automation, innovation, or digital transformation

Demonstrated interest in and working knowledge of generative AI, automation, analytics, or enterprise AI tools

Experience gathering requirements, documenting workflows, facilitating stakeholder discussions, and translating business needs into solution requirements

Experience coordinating cross-functional projects with business, technical, and leadership stakeholders

Ability to work with both senior executives and staff-level users in a clear, credible, and practical manner

Strong analytical skills with the ability to assess business value, feasibility, risk, and adoption considerations

Excellent written and verbal communication skills

Strong organizational skills and ability to manage multiple pilots, tasks, stakeholders, and deadlines

Working knowledge of Microsoft 365 tools, SharePoint, Teams, Excel, PowerPoint, and collaboration platforms

Ability to learn new tools quickly and explain them to others in simple, practical terms

Preferred Qualifications

Experience with multiple AI or automation platforms, such as:

ChatGPT Enterprise or Business

Microsoft Copilot

Claude / Claude Code

Azure AI

Power Automate / Power Apps

AI-enabled SaaS tools

Experience creating prompts, GPTs, AI assistants, automations, dashboards, or workflow prototypes

Familiarity with AI concepts such as LLMs, RAG, AI agents, prompt engineering, embeddings, APIs, and human-in-the-loop workflows

Familiarity with AI security concepts such as data oversharing, prompt injection, hallucination, DLP, least privilege, audit logging, and approved tool governance

Experience working in construction, field services, commercial services, industrial operations, or multi-business-unit organizations

Experience supporting M&A integration, operational standardization, or enterprise transformation programs

Familiarity with business systems such as ERP, CRM, field service, estimating, service management, or ticketing platforms

Core Competencies:

Business Analysis

Understands business processes quickly

Asks strong discovery questions

Documents workflows and requirements clearly

Identifies root causes, not just symptoms

Converts business needs into actionable use cases

Project Management

Organizes work into plans, tasks, owners, deadlines, and risks

Keeps stakeholders aligned

Tracks issues and follows through

Communicates status clearly

Escalates blockers early

AI Technical Curiosity

Experiments safely with AI tools

Understands practical AI capabilities and limitations

Can build simple prototypes or demos

Learns emerging tools quickly

Knows when to involve deeper technical resources

AI Security & Governance Awareness

Understands why data access, privacy, identity, logging, and approval controls matter

Recognizes high-risk use cases

Supports responsible AI practices

Helps users avoid unsafe or unapproved AI usage

Stakeholder Communication

Can speak credibly with executives about business value

Can speak practically with staff about daily workflow pain points

Can translate between business, IT, Security, Data, and vendor teams

Builds trust with users who may be unfamiliar with AI

Innovation Mindset

Looks for practical ways to improve how work gets done

Balances creativity with control

Focuses on measurable outcomes

Challenges assumptions constructively

Turns ideas into structured pilots

Success Metrics:

Metric

How It Is Measured

Metric

How It Is Measured

Use Case Pipeline

Number and quality of AI use cases captured, documented, and advanced

Stakeholder Engagement

Participation from executives, managers, and staff-level users in AI discovery and pilots

Pilot Execution

Pilots delivered with clear scope, timeline, success metrics, and lessons learned

Business Value

Measured productivity, cycle-time, quality, revenue, margin, or risk improvement

AI Adoption

Growth in use of approved AI tools, templates, and workflows

Governance Compliance

Use cases documented, reviewed, approved, and inventoried according to RCA standards

Security Awareness

Reduction in unapproved AI usage and improved understanding of responsible AI practices

Enablement Impact

Training participation, prompt library usage, and user satisfaction

Portfolio Visibility

Accurate tracking of AI ideas, pilots, tools, owners, costs, risks, and outcomes

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