AI Adoption & Enablement Lead Analyst

Brown & Brown Insurance•Daytona Beach, FL

1d•Hybrid

About The Position

Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers. Brown & Brown is seeking an AI Adoption & Enablement Lead Analyst to join our growing team in Atlanta, GA, Dallas, TX, or Daytona Beach, FL! Lead, scale AI adoption across retail B&B businesses by delivering hands-on workshops, coaching employees on practical AI solutions, and improving the overall AI enablement program. This is an opportunity to join a small, high-performing team at the forefront of enterprise AI adoption. Helping teams integrate AI into their day-to-day workflows and unlock measurable business value alongside training delivery, you'll support the design and implementation of custom AI solutions, partnering closely with technical teams and stakeholders. This role focuses on building AI literacy, driving adoption, and supporting teams integrating AI into their day-to-day work. The goal is real behavior change, where AI becomes part of how work is performed, not just a tool that is available. This role translates business needs into actionable AI opportunities and provides input into prioritization to help the organization focus on solutions that will drive adoption and deliver impact.

Requirements

7+ years in technology enablement, product, operations, consulting, or transformation roles.
Experience driving adoption of new tools or technologies at scale
Strong experience in: Workflow/process design
Change management or transformation
Stakeholder engagement across business teams
Strong technical fluency and understanding of AI tools and capabilities (e.g., Copilot, LLMs)
Ability to translate business needs into practical usage of technology; Experience scaling AI or advanced technology use cases from pilots into sustained adoption
Proven ability to drive behavior change and adoption, not just deployment
Strong communication, facilitation, and influence skills across all levels of the organization
Ability to translate strategy into practical execution
Enthusiastic, personable, patient, and encouraging; able to adapt to beginners, power users, and senior leaders
Strong business judgment and ability to translate business problems into practical AI solutions
Ability to quickly learn new capabilities and help others adopt them effectively

Nice To Haves

Insurance broking business operations experience is a plus
AI adoption or enablement specialist
Former consultant, business analyst, operations lead, or PM with strong AI skills
Tech-savvy professional who enjoys teaching and coaching others
Experience in global or multi-entity organizations
Teammate

Responsibilities

Deliver AI workshops, AI training, enablement program, office hours, and coaching sessions for retail associates across varying levels of experience
Facilitate workshops with executives, managers, and frontline employees
Help users build practical AI solutions using approved tools such as Copilot, ChatGPT, Gemini, Claude, and NotebookLM, following guidelines
Manage workshop operations, including intake, scheduling, waitlists, participant communications, follow-up, and reporting
Track outcomes, adoption metrics, value creation, user feedback, and success stories; maintain program dashboards and summary reporting
Stay current on emerging AI capabilities and identify opportunities to improve training, adoption, and change management efforts
Support the AI champion community, including onboarding, communications, training tracking, and recognition updates
Drive Enablement, Adoption, and Effective Use of AI
Experience delivering training, workshops, enablement programs, or educational content
Ability to explain technical concepts to non-technical audiences
Ensure AI tools are consistently used and integrated into daily work, not just explored; Identify and remove barriers to adoption
Deliver enablement at scale, including role-based learning journeys, toolkits, office hours/coaching, and a champion network in partnership with training and operations
Help establish AI COE framework to promote responsible AI use, best practices, training and enablement programs, success metrics, and communication
AI & Technical Skills
Hands-on experience using modern AI tools and large language models
Understanding of prompt engineering, retrieval systems, and AI-powered workflows
Working knowledge of Python
Ability to translate business challenges into practical AI solutions
Build Practical AI Literacy
Partner with training and operations teams to develop role-based enablement across the enterprise (sales, service, ops, leadership)
Equip teams to effectively use AI platforms, Copilot tools, AI agents, and prompt & agent libraries
Provide ongoing support through office hours, coaching, and trainings materials
Reinforce expectations for when and how AI should be used; Ensure responsible AI usage by incorporating governance and guardrails into training, communications, and playbooks
Support Integration of AI Into Workflows
Partner with business and operations teams to roll out AI capabilities and integrate them into daily work; Develop change management strategies & educate teams on AI benefits.
Identify where AI can meaningfully improve workflows, quality, and speed; Help define roles of AI (automate, augment, or escalate) vs human
Ensure AI usage is clear, repeatable, and consistent to shift from manual to AI-assisted workflows
Shape and Prioritize High-Value AI Opportunities
Understand pain points and translate needs into clear, actionable AI use cases; Identify where AI can deliver meaningful workflow improvements and practical impact
Bring structured recommendations to inform prioritization and sequencing of AI efforts
Act as a bridge between business users and AI/product teams to ensure solutions reflect real needs, are adopted, and deliver value; Provide insight into what will drive adoption and proactively identify where solutions are likely to stall
Support business teams in owning outcomes and driving adoption; Ensure success metrics are defined and use data to continuously refine prioritization and enablement strategies
Drive Continuous Improvement and Scalable Adoption
Gather feedback from users on what’s working, where friction exists, & where trust is low
Partner with engineering to improve usability and effectiveness of AI solutions
Continuously refine enablement materials, guidance, and approach
Enable acceptable AI usage, citizen development, and sharing & reuse of AI tools
Share success stories, use cases, best practices, and lessons learned to accelerate adoption across teams