GenAI only delivers at scale when teams can access the right data, trust what they retrieve, and govern how it is used. Strengthen your foundation and turn enterprise data into a true competitive advantage.
Your GenAI solution is only ready for prime time if the data behind it is too. To build confidence before scaling, leaders need to ask questions like:
Are we...
…treating metadata as a core operating capability?
…systematically ensuring our data is accurate, complete, timely, and consistent?
…continually reinventing embedding and retrieval logic?
…building a governed retrieval layer that gets the right context to the right use case?
…showing data readiness is improving GenAI outcomes?
Our Solution - Build the data capability GenAI scale demands
Built to turn fragmented data into a governed, retrieval-ready enterprise asset, our Data Readiness Playbook helps leaders remove the data friction that slows delivery, weakens answers, and limits GenAI scale.
Your GenAI Data Readiness Playbook @ a Glance
- Structured 1:1 discovery sessions to clarify priorities, adoption maturity, and scaling constraints
- A targeted readiness scan to assess your baseline readiness
- An executive brief outlining data readiness best practices and their implications
- Aligning leaders on the data conditions GenAI scale actually requires
- Exploring applied Use Cases, adoption best practices, and key “Watch Outs”
- Aligning on an actionable scaling plan
- Idnetifying and prioritizing key Data Readiness gaps
- Exploring our 24 Enterprise GenAI Data Acceleration Guides
- Leveraging a GenAI Strategist-led planning session to define your action plan
- Implementing Value Scoring for In-Scope GenAI Data
- Ensuring Your GenAI Data is Trustworthy
- Enterprise GenAI Search Best Practices
- Enterprise GenAI Data Explorability Best Practices
- Enterprise Data Entitlements Management Best Practices
- GenAI Data Definition Best Practices
- GenAI Metadata Management Best Practices
- Co-deliver quick wins that build confidence, improve adoption, and accelerate target-state delivery
- Configuring and customizing your GenAI Data Readiness scaling playbook
- Defining the operating model, ownership, and governance rhythms needed to sustain readiness at scale
- Optimizing and evolving your TOM as priorities, data sources, and use cases change
- Configuring and customizing your GenAI Data Readiness metrics and insights plan
- Defining the metrics, governance signals, and operating reviews needed to track readiness, surface friction early, and prove progress
- Optimizing and evolving your insights as readiness improves, risks shift, and new gaps emerge
- < 30 Days Wins: Lightly configurable resources and solutions
- 30 – 60 Day Wins: Lightly customizable Quick Wins
- 60 – 90 Day Wins: Increasingly high value Quick Win deliverables
- Baseline your GenAI data readiness, friction points, and retrieval foundations
- Tailor the plan to the retrieval priorities, data bottlenecks, and governance gaps that most affect answer quality
- Deliver Quick Wins, build capability, and scale priority solutions through one integrated plan
- Identify your priority stakeholders, communication needs, and the data-readiness gaps
- Configure and deliver a tailored GenAI Data Readiness communications plan, and role-specific enablers
- Build and sustain momentum with demos, videos, and proof points.
- Define your quarterly GenAI Data Readiness review, optimization, and adaptation process
- Enable quarterly strategy and scaling plan updates, double down on what’s working and address what’s not
- Rapidly align to sustain and accelerate your momentum
- Identify where teams need targeted coaching to overcome readiness, prioritization, retrieval, or execution gaps
- Deliver tailored expert support, working sessions, and practical guidance
- Help teams strengthen GenAI Data Readiness, and keep their efforts moving forward
Choose Your On-Ramp...
Choose the right on-ramp for your GenAI Data Readiness journey—whether you’re looking to rapidly align and mobilize, solve targeted challenges, or scale your GenAI Data Readiness holistically.
An Accelerated Alignment & Action Planning Sprint
A fast-paced leadership alignment and action planning sprint to:
- Baseline your current GenAI data readiness
- Expose the highest-impact readiness gaps
- Align on the priorities that matter most
- Define your path forward
- Identify near-term Quick Wins
Build the Data Capability GenAI Scale Demands
Confidently scale your GenAI Data Readiness with a tailored TOM that helps you turn fragmented data into a governed, trusted, retrieval-ready advantage.
Targeted GenAI Data Readiness Quick Wins
Rapidly solve a targeted GenAI Data Readiness challenge, including:
- Baseline your readiness and quality gaps
- Solve a high-priority data challenge
- Clarify your data priorities
- Align on practical actions to move forward
- Deliver focused progress in a matter of weeks
Outcomes you can expect
Create a clearer view of what data you have, where it lives, how it’s used, and what’s needed to support GenAI.
Improve confidence in the quality, reliability, and suitability of the data your GenAI solutions depend on.
Make data easier for teams to interpret, evaluate, and use effectively in GenAI contexts.
Strengthen how well data, knowledge, and context connect across systems, sources, and workflows.
Improve your ability to monitor data readiness, detect issues early, and respond as GenAI needs evolve.
Complimentary Resources
Curious About What “Great Looks Like”?
Review our “GenAI Data Readiness” Whitepaper
Want to See How You Compare?
Complete our GenAI Data Readiness Scan or Assessment
Want an easy way to come up to speed?
Click here to listen to our GenAI Data Readiness Podcast
Want to dig deeper?
Click here to check out our library of YouTube videosFrequently Asked Questions
- Why do we need to improve GenAI data readiness now?
Because GenAI can’t perform well on data that is hard to trust, find, understand, or connect. - What outcomes should we expect from this work?
Stronger data trust, better usability, clearer context, and more confidence in GenAI outputs. - What happens if we don’t address GenAI data readiness early?
Weak outputs, slow delivery, and rework persist because the data foundation isn’t ready.
- What do you mean by “GenAI data readiness”?
Making priority data clear, trusted, connected, and usable for GenAI. - What are the main deliverables from this work?
A view of readiness gaps, improvement actions, and a data roadmap. - What do “Quick Wins” look like in GenAI Data Readiness work?
Identify high-value sources, resolve trust gaps, and improve access to key content.
- Does this only apply to highly structured data environments?
No—it matters in structured and unstructured environments wherever GenAI depends on trusted data. - Can this work even if our data environment is complex or fragmented?
Yes—it helps teams prioritize the data that matters most instead of fixing everything at once. - Does this cover more than data quality?
Yes—it covers accessibility, context, workflow fit, and observability—not just data quality.
- How do you decide which data readiness issues to address first?
We prioritize the data gaps most likely to improve usefulness, trust, and delivery speed. - How do you keep this from turning into a massive data cleanup effort?
We fix the data issues that matter most, instead of trying to clean everything. - How do you connect data readiness to GenAI solution success?
We tie data improvements to the use cases and workflows that depend on them.
- Who should be involved from our side?
Data leaders, business stakeholders, and product and technology teams that own critical data. - How do you keep data readiness efforts from losing momentum?
We focus teams on clear priorities, ownership, and a manageable improvement path. - How do you sustain this after the initial work is done?
We build a repeatable readiness model that improves as GenAI needs expand.