MyDataWork’s AI helps you understand analytical work, connect it to business priorities and identify useful next steps. It uses asset metadata and the work context you record. The judgment stays with you.
Analysts have been “disrupted” before — by BI suites, self-service tools, the cloud. Each wave multiplied the tools and pushed the analyst’s value up: framing the question, validating the output, owning what “correct” means. AI is the next wave — it can draft the SQL, but not know whether Finance will recognize the number. Value relocates; it doesn’t disappear. MyDataWork captures the work and its context so AI has something trustworthy to stand on — and the human keeps the seat only a human can hold.
Summaries of recorded work, patterns across linked assets and use cases, reuse and automation suggestions, and first-pass reviews of your analytical estate.
Framing the real question, validating what the model returns, knowing what “correct” means in your business, and owning the decision — and the politics around it.
AI supports each step: understand your estate, sharpen a use case, find opportunities across the portfolio and prepare context for agents. Features use relevant metadata and authored work context, including descriptions and objectives. Review what you record and the recommendations you receive.
A context-aware assistant on every screen. Ask how to navigate, what a metric means, or what to do next — answered from your own workspace, not a generic chatbot.
A senior-analyst-style audit of your whole estate — connections worth documenting, use-case opportunities, and health issues. Your first eligible assessment is free; subsequent runs use AI credits.
“What am I missing?” — concrete, specific improvements drawn from a use case’s own assets, notes, and progress. Save the ones worth keeping to its action plan.
Develop modernization proposals from recorded asset structure, relationships and business objectives. Review suggested benefits, effort and risks before implementing a plan.
Find where work overlaps and can be consolidated, which processes are real automation candidates, and external datasets from your cloud marketplaces that could change the answer.
Workspace Agent reviews your workspace when you run it, flagging work that needs attention. Agent Studio helps scope an agentic use case; it designs the workflow rather than executing it. Agent Access gives approved agents selected structure and authored work context over MCP.
AI controls are available in Setup → AI configuration. Usage follows your plan’s allowance: direct plans use per-person credits, while AWS Marketplace uses a monthly workspace pool. Turning AI off leaves the non-AI workspace features available.
AI features use relevant metadata and authored context; the exact inputs depend on the feature. Agent Access separately exposes the selected structure plus descriptions and objectives you have written. It excludes source file contents and values from connected sources. Free text can contain names or figures, so review it before sharing.
Built-in AI uses OpenAI for commercial workspaces and Amazon Bedrock in AWS GovCloud (US-West) for GovCloud workspaces. See Security & IT for processing and sharing details.
Explorer, Solo and direct Team plans have per-person daily allowances; Solo and Team also have weekly limits. AWS Marketplace pools credits monthly across the workspace, resetting on the first at 00:00 UTC. See Pricing for current allowances and eligible top-ups.
And where it matters most, there’s no AI at all: Architecture & Value and Solution Packs use zero AI credits and work from recorded information and editable starter content. Their value figures depend on the assumptions and evidence you enter.