AI Business Analyst

Quick Facts

• Business role focused on intake, assessment, and delivery alignment for AI/automation and related software/reporting/data fixes.
• Partners with business leaders (e.g., Sales, Sourcing, Product Lifecycle, ERP/Warehouse, International Sales) and with AI engineers and developers.

Description

Own the request intake process and decide which requests become AI solutions, quick builds, domain projects, data/reporting fixes, or should not be built. Turn ideas into measured briefs with scope, acceptance criteria, exceptions, data sources, and clear ownership of business rules. Validate outcomes after launch by measuring results against an established baseline.

Responsibilities

• Own the intake: assign an owner, make a decision, and reply within agreed timelines.

• Observe and document real workflows to identify frequency, cycle time, bottlenecks, failure points, and downstream impacts.

• Establish baselines using time per run, run frequency, people involved, error rates, and cost.

• Classify each request in writing with the AI Engineering Lead (AI solution, quick build, domain development, reporting/data fix, or none).

• Write developer-ready briefs: scope, acceptance criteria, exceptions, data sources, and business-rule ownership.

• Recommend “no” or “not yet” with evidence when building is not worthwhile or the real issue is elsewhere.

• Track project status and keep business and developers aligned across whichever team delivers.

• Close the loop after launch by re-measuring against the baseline and determining whether to retire solutions.

• Maintain visibility in the business so ideas are brought to the team instead of creating workarounds.

Requirements

• 3+ years as a business analyst, process analyst, or similar role; ideally in IT or digital transformation.
• Proven ability to translate vague requests into clear requirements and separate what was asked for from what is actually needed.
• Strong numerical capability to build baselines and a simple business case.
• Enough understanding of software, data, and AI to judge whether the best path is AI, ordinary development, reporting, or a data fix (no coding required).
• Confidence working with VPs and senior managers, including advising that a project should not proceed.
• Experience with Jira and Confluence (or similar tools).
• Clear English writing for short, decision-ready briefs.

Benefits

• Early hire in a new AI Engineering team, owning request intake and helping establish how projects are assessed and tracked.
• Structured first-year milestones focused on intake quality, baseline-driven delivery, and post-launch measurement.

Your First Year

• 3 months: Every incoming request has an owner and a written brief; leadership reviews decisions, not raw ideas.
• 6 months: Each approved project has a baseline and an agreed delivery team; weak ideas are closed with recorded reasons.
• 12 months: Post-launch measurement proves returns; intake-to-results process runs without prompting.