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About the Role

The AI Business Enablement Lead is responsible for accelerating practical, responsible AI adoption across Raymond James Ltd., focusing on advisor productivity, operational efficiency, service quality, and employee effectiveness. This role owns the RJL AI enablement roadmap and collaborates with various business and technology leaders to increase adoption of approved tools, implement AI use cases in workflows, and prepare the firm for future AI capabilities.

Responsibilities

Participate in the development of the RJL AI strategy, applying functional expertise to test viability and contribute creative ideas.
Maintain and execute the RJL AI strategy and phased roadmap.
Communicate the RJL AI strategy and required actions to inspire workforce commitment.
Partner with RJF AI teams to assess, adopt, and adapt enterprise AI capabilities for the Canadian business.
Advise senior leaders on AI capabilities, trends, risks, vendor developments, and workflow opportunities.
Partner with product management to integrate AI embedded in 3rd party enterprise tools into the RJL roadmap.
Provide regular reporting on adoption, blockers, risks, and emerging opportunities.
Lead AI adoption and literacy programs for advisors, branch teams, operations, supervision, compliance, technology, and corporate functions.
Develop role-based guidance, training, prompt libraries, playbooks, and practical examples for approved AI tools.
Work with RJF AI teams to leverage existing resources, standards, training, and lessons learned.
Establish and lead the RJL AI Enablement Group and AI Community of Practice.
Identify and support AI advocates across business units to increase safe and consistent adoption.
Partner with business leaders, advisor teams, product management, operations, supervision, compliance, risk, and technology to identify AI use cases tied to measurable business outcomes.
Maintain a prioritized AI opportunity backlog, including business owner, expected value, feasibility, data requirements, risk considerations, dependencies, and implementation path.
Facilitate use-case intake, discovery, prioritization, pilot planning, and post-implementation measurement.
Support pilots and controlled rollouts of approved AI capabilities, ensuring adoption plans, training, communications, controls, and success measures are in place.
Coordinate with compliance, risk, privacy, legal, technology, and RJF AI teams to ensure AI use cases follow applicable policies, controls, and Canadian regulatory expectations.
Operate a structured intake and assessment process for AI tools and use cases, including business value, data usage, privacy, supervision, records, model risk, vendor risk, and operational risk considerations.
Maintain clear guidance on approved tools, permitted uses, restricted uses, and escalation paths.
Reduce shadow AI risk by providing approved alternatives, practical training, and transparent communication.

Requirements

Bachelor’s degree in Data Science, Computer Science, Engineering, Business Administration, or related field — or equivalent experience.
Master's degree or MBA preferred.
8+ years of experience in technology enablement, digital transformation, business analysis, product management, consulting, operations transformation, or related roles.
3+ years of experience working with AI, automation, data, analytics, or emerging technology use cases.
Financial services or wealth management experience strongly preferred.
Experience translating business problems into practical technology-enabled solutions.
Experience evaluating, prototyping, or implementing LLM-enabled tools, workflow automation, or productivity solutions.
Experience facilitating workshops, working sessions, pilots, or adoption programs with cross-functional stakeholders.
Knowledge of wealth management business processes, advisor workflows, branch operations, client lifecycle, and service model.
Knowledge of Canadian financial services regulatory environment relevant to AI adoption, including CIRO, OSFI expectations where applicable, privacy, records, supervision, and third-party risk.
Knowledge of AI productivity tools and enterprise platforms, including Microsoft Copilot, ChatGPT/OpenAI-enabled solutions, meeting assistants, knowledge search, workflow automation, and emerging AI capabilities.
Knowledge of Responsible AI practices, data handling, privacy, security, model risk, vendor risk, and human oversight in regulated environments.
Knowledge of change management, adoption measurement, training design, and business-value tracking.
Analysis: Uses data, adoption metrics, and business insight to identify high-impact AI opportunities, understand adoption trends, and drive prioritization decisions.
Communication: Conveys complex AI concepts clearly to technical and non-technical audiences — from advisor teams to executive leadership; strong executive presence.
Client Focus.
Exercising Judgment & Decision Making: Makes timely, risk-informed decisions that balance innovation speed with governance, compliance, and business impact.
Technical & Professional Knowledge: Demonstrates expertise in AI platforms, prompt engineering, automation, and emerging technology — with the ability to personally build working solutions.
Building Effective Relationships: Builds strong partnerships across IT, business units, advisor teams, compliance, and vendor teams to achieve shared goals.
Influence Without Authority: Inspires adoption and drives alignment across complex, cross-functional environments — including executives, architects, advisors, and business leaders — without relying on direct reporting authority.
Encouraged to grow professionally and inspire others.
Encouraged to work with and through others to achieve desired outcomes.
Encouraged to make prompt, pragmatic choices and act with the client in mind.
Encouraged to take ownership and hold themselves and others accountable for delivering results that matter.
Encouraged to contribute to the continuous evolution of the firm.

Skills

AI
Automation
Data Analysis
Emerging Technology
LLM-enabled tools
Workflow Automation
Productivity Solutions
Workshop Facilitation
Prompt Engineering
Change Management
Adoption Measurement
Training Design
Business-Value Tracking

Location

Canada

Work Type

Flexible workstyles

Experience Level

8+ years of experience in technology enablement, digital transformation, business analysis, product management, consulting, operations transformation, or related roles.
3+ years of experience working with AI, automation, data, analytics, or emerging technology use cases.

Education Level

Bachelor’s degree in Data Science, Computer Science, Engineering, Business Administration, or related field — or equivalent experience.
Master's degree or MBA preferred.

Salary/Compensations

$125,000 - $140,000 annually, in addition to competitive performance bonuses/incentives.

Benefits

Flexible workstyles
Competitive compensation and benefits package
Health Benefits
RRSP Matching Program
Employee Stock Purchase Plan
Paid Time Off
Volunteer Days
Discretionary Bonuses
Tuition Reimbursement

About the Company

Raymond James Ltd. is Canada’s leading independent investment dealers offering high quality investment products and services to Canadians seeking customized solutions to their wealth management needs.
Our most important investment is in people.
We support internal promotion and community involvement.
At Raymond James – we honor, value, respect the uniqueness, experiences, and backgrounds of all of our Associates.
When associates bring their best authentic self, our organization, clients and communities thrive, it is part of our people-first culture.

Equal Opportunity

The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.
We demonstrate our commitment to ensuring equal opportunities for all candidates.
To request accommodations, candidates are instructed to contact Human Resources via email at recruitment@raymondjames.ca.
By reaching out to this email address, candidates can communicate their specific requirements and discuss the necessary accommodations they may need to participate fully in the recruitment process.
We may use automated or AI-enabled tools to support parts of our recruitment and screening process, including screening, assessing or selecting applicants where applicable.
These tools help us review applications efficiently, but they do not replace human decision-making.