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AI Business Partner

Job in Alpharetta, Fulton County, Georgia, 30239, USA
Listing for: Expert Technical Solutions
Full Time position
Listed on 2026-03-06
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer, Data Science Manager, Data Security
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Expert Technical Solutions has an outstanding opportunity for a n AI Business Partner with an Award Winning, industry leading company in Alpharetta, GA. This person will be responsible for architecting and executing our client’s enterprise-wide AI and data strategy. There will be an initial focus on intra-department and cross-departmental data optimization and scalable AI enablement. This role is intentionally designed as both strategist AND builder.

This role will report directly to our client’s CEO.

This is a Permanent, Hybrid (3 days onsite in Alpharetta 30022) opportunity offering competitive salary, excellent benefits, and outstanding growth opportunities!

Duties And Responsibilities
  • Conduct structured listening sessions with the CEO, CTO, CRO, CMO, and leaders across Professional Services, Customer Support, and Product to understand strategic priorities, operational friction points, and AI aspirations.
  • Map our client’s current enterprise data ecosystem across Sales (Gong, Salesforce CRM), Finance (Net Suite), Customer Support, Customer Success, Marketing Automation, Product Usage Data, MDM infrastructure, and other critical systems to create a clear view of how data flows across the business.
  • Evaluate how each department and individuals are currently leveraging AI, distinguishing experimentation from scalable deployment, and identify potential AI Champions to help accelerate adoption.
  • Review existing security, data governance, and management policies and prepare forward-looking recommendations to ensure responsible, secure, and compliant AI implementation.
  • Assess our client’s data quality readiness for the purpose of improving the overall quality and usability of critical internal information to be leveraged for competitive advantages and operational efficiencies.
Target quick and substantial Data and AI wins
  • Identify high-impact, quick-win AI use cases across revenue generation, RFP acceleration, support automation, and internal knowledge retrieval to demonstrate early value and deliver 1-3 use cases in production.
  • Assess data quality, accessibility, integration gaps, governance standards, and overall, AI readiness to identify both constraints and untapped opportunities.
  • Present a next 30/60/120‑Day AI Opportunity Brief to the Executive Leadership Team outlining the top five highest‑impact AI initiatives, required data integrations, estimated ROI and revenue enablement potential, and associated risks and governance considerations.
Design the AI operating Model and data integration strategy to deliver tangible business value
  • Define and socialize a clear enterprise AI strategy framework aligned to revenue growth, product differentiation, operational scale, and market positioning.
  • Serve as both AI orchestrator and hands‑on builder, partnering directly with Revenue, Marketing, Product, Support, Professional Services, and Finance to move from concept to implemented solutions that demonstrate the art of the possible.
  • Develop and execute a cross‑department data integration roadmap aligned to the MDM foundation as the trusted data layer, establishing enterprise data management standards, identifying data gaps and hygiene issues, and implementing corrective plans to improve data quality, consistency, and integration across the organization.
  • Launch and deploy both departmental and cross‑functional AI use cases (e.g., AI‑powered RFP assistant, centralized customer intelligence hub, or internal product knowledge assistant) with defined business success metrics.
  • Create a centralized, structured repository of customer proof points by vertical (Banking, Financial Services, Healthcare, Manufacturing) enabling Revenue to access consolidated product feedback, customer journey insights, and referenceable stories.
  • Define and track measurable AI impact metrics such as support ticket close times, customer story retrieval and formulation time, RFP response time improvement, win‑rate improvement, support ticket deflection, and knowledge‑retrieval speed.
  • Promote and celebrate implemented AI successes across the organization to reinforce momentum, recognize contributors, and inspire broader adoption.
Technical Skills
  • Bachelor’s…
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