AI and automation for teams working in Workiva
Reduce the manual work behind your reports, controls, and recurring data processes. Lockfield helps you identify useful applications, connect the information they need, and build workflows your team can operate and review.
Make the whole process easier to run
A useful workflow connects the inputs, the work, and the review. We look at those together, then scope the change your team can put to use.
- The work
- Reporting, data preparation, controls, and the recurring processes around Workiva.
- The approach
- Match the process to native Workiva AI, an approved connected tool, or conventional automation.
- You receive
- A recommendation, a scoped implementation, and instructions your team can use each cycle.
- First step
- A free conversation, followed by a paid, fixed-fee diagnostic quoted in writing.
Where does the work get stuck?
These are applications we can assess with your team. The right approach depends on your sources, available tools, and the people who own and review the work.
Reports take too much assembly
Look at the steps from source data to the finished report. Connect recurring inputs, update linked figures, and prepare draft commentary from approved information for your reviewer.
A report has not updated
Trace the available source, query, refresh, and Chain evidence. Identify what failed, what is still unknown, and the next check or repair.
Reviewers repeat the same checks
Use repeatable checks for totals, links, and missing inputs. Where AI fits, use it to help explain exceptions and identify narrative inconsistencies for review.
Answers are scattered across files
Organize approved policies, prior reports, and operating instructions so an assistant can answer from relevant sources. Give the content an owner and a refresh schedule.
Evidence work slows the audit
Assess where evidence organization, draft test documentation, and issue summaries could reduce preparation work. Keep testing conclusions and sign-off with your audit team.
Your team needs a place to start
Compare opportunities by effort, expected value, data quality, and maintenance. Decide what to build first and what needs preparation before it will be useful.
What a monthly reporting workflow could look like
Illustrative workflow with fictional figures. This is an example to discuss, not a customer result or a packaged integration.
The inputs are the period’s source data and approved explanations. The output is an updated reporting pack with draft commentary and exceptions for the reviewer.
Prepare the inputs
Bring the period’s actuals, budget, and approved explanations together. Check the period, account mapping, and source totals before updating the reporting model.
Update and check the figures
Refresh the connected data and linked report. Repeatable calculations and checks flag missing inputs or differences for someone to resolve.
Prepare the commentary
An approved AI tool uses the checked figures and source explanations to draft variance commentary. Missing explanations stay open for follow-up.
Review and approve
The reviewer checks the figures, supporting sources, and draft language, resolves exceptions, and approves the report through the team’s normal process.
Actuals against budget
| Account | Actual | Budget |
|---|---|---|
| Revenue | 1,240,000 | 1,180,000 |
| Operating costs | 920,000 | 880,000 |
| Operating profit | 320,000 | 300,000 |
Draft commentary
Revenue is $60,000 above budget. The supporting explanation needs follow-up.
For the reviewer
- Check figures against the source.
- Resolve the missing explanation.
- Approve the final language.
We agree which steps can run automatically, which require a person, and how a failed check stops the affected output from moving forward.
What Lockfield delivers
The engagement covers the process and the implementation needed to improve it. Your proposal states the deliverables and how they will be tested.
- A recommendation grounded in your process
- We inspect the sources, handoffs, and review steps. You receive findings, priorities, and a proposal that identifies the tools, dependencies, and work in scope.
- Prepared data and source content
- We address the source connections, labels, and approved reference material the agreed workflow needs. Unresolved data or mapping questions stay visible for your team to decide.
- A working implementation
- We configure available Workiva features or build supported connections and automation within the agreed scope. Access and product availability are confirmed before implementation.
- Checks and exception handling
- We test against known results, define what happens when inputs are missing or a run fails, and agree what the reviewer checks before output is used.
- A handoff your team can operate
- Your team runs a real cycle with us and keeps written instructions. Ownership, reruns, and maintenance are agreed; follow-up support is scoped separately.
Choose the tools that fit the work
A workflow may combine native Workiva features, an approved connected tool, and conventional automation. We assess what your organization already has and what it can maintain.
Our Workiva AI guide explains the native features, settings, and availability, with links to Workiva’s documentation. For data connections and recurring updates, see our custom Workiva solutions.
Lockfield’s own Workiva plugin is a separate private pilot for scoped report diagnostics and data checks. Its page describes the tested capabilities, access requirements, and limits; the plugin workflow help explains how a supported pilot works.
Build checks and review into the workflow
Figures come from reconciled sources and numeric models. Repeatable checks test totals and links; AI-assisted commentary and findings go to a reviewer with their supporting sources. Unexplained differences remain open.
Before handoff, we compare the workflow with known results and check how it handles missing inputs and failed runs. We agree who approves output and which records your team keeps. Read how to review Workiva AI output.
Start with the process you want to improve
Talk through the process
Tell us where work gets stuck, what your team wants to improve, and the next deadline. You can bring a reporting problem without knowing which AI tool it needs.
Get findings and a scope
The paid diagnostic examines an agreed report, control process, or data flow. You receive a recommendation and a fixed-scope proposal before committing to implementation.
Build and test
We implement the agreed workflow and compare its output with known results. Your team reviews exceptions and the approval steps before using it in a real cycle.
Run it with your team
Preparers and reviewers use the workflow with us, then take over with written instructions and an agreed owner.
The Workiva diagnostic is quoted in writing after the free first call. Implementation and follow-up support are agreed separately.
Your policy governs the data and access
We agree which systems, files, and tools the work may use. Before your data is processed by an AI tool we use, the approved tools and terms excluding training on your data are agreed in writing.
Access is limited to the agreed work and removed when it ends. Working copies are returned or deleted, with written confirmation; routine backups expire on their normal schedule. The diagnostic’s data-handling terms apply to every engagement.
Common questions
Do we need to know which AI tool we want?
You can start with the process you want to improve. We assess the sources, available tools, and review steps, then recommend an approach and scope before implementation.
Does every workflow need AI?
Many data transfers, calculations, and checks are best handled with repeatable automation. We assess where AI can help with drafting, questions, or interpretation and choose the tools for the work.
Can you work with the tools we already have?
We first assess your Workiva setup and approved tools. Any connection depends on supported interfaces, administrator-approved access, and your data policy. Workiva AI features also depend on your subscription, tier, and early access terms.
How are the numbers and conclusions checked?
Figures come from reconciled source data and numeric models. The workflow is tested against known results, exceptions remain visible, and your reviewers approve AI-assisted commentary and conclusions before use.
What happens after implementation?
Your preparers and reviewers run a real cycle with us and keep written instructions. The handoff identifies the owner, rerun steps, and maintenance needs. Follow-up support is agreed separately.