01Bible Translation AI Advisory
AI is already entering Bible translation. The question is whether it is entering wisely.
AI can accelerate research, checking, drafting, reporting, and other parts of the translation process. But adopting a tool is not the same as improving the work.
Responsible AI adoption starts with the translation process itself. Before asking what AI can do, we establish what quality, human accountability, community ownership, consultant oversight, and publication integrity must remain protected.
Translation leaders still have to answer harder questions:
- Where should AI participate?
- Where should human judgment remain decisive?
- How will translation quality be protected?
- Who is accountable for AI-influenced decisions?
- How will we know whether AI is creating value — or simply moving work downstream?
Human + Machine Works helps Bible translation organizations answer those questions before, during, and after AI adoption.
- Assess before you adopt.
- Pilot before you scale.
- Govern before complexity grows.
- Assure before value quietly leaks away.
5 minutes · Preliminary self-assessment · No cost
02The starting point
Where are you today?
You do not need to buy all four services. Start with the problem your organization actually needs to solve. Choose the statement that sounds most like you.
“We are considering AI, but we don't know what is appropriate.”
Start with AI Readiness & Translation Integrity Assessment
Establish the strength of your existing translation process, determine what AI should improve, and identify which AI uses should proceed, require safeguards, or remain human-led.
Explore Package 1 02“We already want to use AI. We need a responsible workflow.”
Start with Human–AI Workflow Implementation
Design the workflow, establish decision rights, train the team, run a controlled pilot, and measure whether it actually works.
Explore Package 2 03“Different teams and projects are using AI differently.”
Start with Organizational AI Governance
Create one organization-wide approach to AI tools, data, projects, agents, quality, security, and accountability.
Explore Package 3 04“AI is already operating across multiple projects. We need ongoing oversight.”
Start with AI Translation Assurance
Continuously verify that approved workflows remain effective and that quality, security, human capability, and accountability are being protected.
Explore Package 403Practical Tools
Start with evidence, not assumptions.
You may not be ready for a consulting engagement yet. Use these diagnostic tools to identify the question your organization needs to answer first.
Is this AI use actually ready?
Assess one proposed Bible translation AI use across purpose, community authority, translation integrity, governance, data, people, technology, evaluation, and value.
Results
- Preliminary nine-domain profile
- Potential critical-review areas
- Strengths and priority gaps
- Recommended next step
Preliminary self-assessment. Formal readiness requires evidence review and consultant calibration.
Which AI policies should you build first?
Answer questions about your organization, data, AI and agent use, and current security controls. Receive a prioritized policy roadmap rather than another generic checklist.
Results
- Risk exposure
- Security maturity
- Build First priorities
- Build Next priorities
- Policy sources
Governance guidance, not legal advice. Policy applicability depends on organizational structure, activities, contracts, jurisdiction, and risk.
04The roadmap
One framework. Four decisions.
- 01AssessWhat must AI protect — and where does it belong?Package 1 — AI Readiness & Integrity Assessment
- 02ImplementHow should humans and AI work together?Package 2 — Human–AI Workflow Implementation
- 03GovernHow should AI operate across the organization?Package 3 — Organizational AI Governance
- 04AssureIs the system still operating as intended?Package 4 — Ongoing AI Translation Assurance
You can enter at any stage.
- A project considering AI may begin with Package 1.
- An organization already piloting AI may begin with Package 2.
- An agency with fragmented AI use may begin directly with Package 3.
- An organization with established policies and multiple active projects may begin with Package 4.
AI Readiness & Translation Integrity Assessment
Know what must remain true before deciding where AI belongs.
AI readiness cannot be assessed in isolation from the translation process it will enter.
Before leadership decides whether AI should assist research, checking, back translation, or drafting, it needs to know whether the existing translation process is strong enough, what quality and publication controls already exist, who holds decision authority, whether community and church participation are protected, what problem AI is expected to solve, and how improvement will actually be measured.
The real question is not simply, “Is AI good for Bible translation?” It is: is this project ready for this particular AI task, using this technology, with this team, at this stage, under these safeguards?
Start with the translation — not the technology.
Before assessing AI, we establish the controls the translation process must preserve.
Professional quality
Was it done and checked well?
Translation team, exegetical review, linguistic review, consultant checking.
Community legitimacy
Do the people understand and own it?
Representative speakers, comprehension testing, community participation.
Ecclesial accountability
Have the appropriate churches participated and accepted it?
Church review and defined authority.
Publishing integrity
Can the exact text be responsibly released?
Rights, correction closure, final version, release authorization.
These four forms of authorization are distinct — one cannot substitute for another. Package 1 evaluates the evidence around these controls before recommending where AI should enter.
What can you prove today?
Establish your current-state baseline across the evidence chain.
- Governance
- Community
- Provenance
- Exegesis
- Language
- Comprehension
- Church Review
- Consultant Check
- Corrections
- Rights
- Production
- Release
- Stewardship
Translation Integrity Baseline
A current-state view of what your project can already demonstrate, what is incomplete, and what must be strengthened before AI adoption expands.
Define value before choosing the AI.
What is AI actually expected to improve?
| Don't stop at | Measure instead |
|---|---|
| AI draft speed | Time to consultant-acceptable material |
| Number of outputs | Useful work accepted after review |
| AI usage | Total workflow improvement |
| Machine score | Quality evidence plus human judgment |
| Initial time saved | Rework and downstream correction |
| More automation | Human capability retained or increased |
We establish the baseline before implementation so that a later pilot can distinguish real value from faster output that simply transfers work downstream.
AI Value & Measurement Baseline
One project. Different AI-readiness decisions.
A project does not receive one generic AI-readiness score.
- ResearchReadyConditionalNot Ready
- Back TranslationReadyVerification RequiredNot Ready
- CheckingReadyPilotRestricted
- Alternative DraftingReady After Human DraftRestrictedNot Ready
- AI-First DraftingPilot CandidateConditionalNot Recommended
How the assessment works
Establish the translation baseline
We assess:
- Existing translation workflow
- Quality and publication controls
- Decision rights
- Consultant oversight
- Community and church participation
- Documentation and evidence
Outcome: Translation Integrity Profile
Determine AI fit and value
We assess:
- Problem AI is expected to solve
- Current performance baseline
- Project type
- Translator capability
- Language resources
- Cultural and theological complexity
- Proposed AI tasks
- Technology and data risk
- Human-development risk
Outcome: AI Readiness & Value Profile
Make the decision
We determine:
- Which AI uses are appropriate
- Which require safeguards
- Which should remain pilot-only
- Which require redesign
- Which should not proceed
- What should be measured next
Outcome: AI Use Decision + Roadmap
See your assessment develop as we work.
Clients receive access to a secure assessment workspace where they can:
- Complete live diagnostic checks
- Provide evidence
- See current findings
- Review translation-integrity gaps
- Establish measurement baselines
- See readiness by AI task
- Track safeguards
- Review consultant recommendations
- Access final deliverables
Translation Integrity Check
What can your project prove today?
AI Value Check
What problem are you actually trying to solve?
Measurement Check
Are you measuring activity or real value?
Human Authority Check
Who decides, reviews, approves, and remains accountable?
Translation Integrity Profile
See where your existing translation and eventual publication controls are strong, incomplete, or missing.
Project Classification
Understand the translation context in which AI would operate.
AI Value & Measurement Baseline
Define what AI is expected to improve and how improvement should be measured.
Task-Readiness Profile
Separate findings for research, checking, back translation, alternative drafting, and AI-first drafting.
AI Use Decision Matrix
See what is approved, conditional, pilot-only, restricted, or not recommended.
Human Accountability Map
Identify who recommends, evaluates, decides, approves, and can stop AI use.
Risk & Safeguard Plan
Know what must change before adoption expands.
90-Day Pilot Recommendation
Know what should be tested next and what evidence should be collected.
Leadership Decision Brief
Give senior leadership a concise decision document.
- ✓
Approved
Evidence supports the proposed use.
- ⚠
Approved with safeguards
Proceed once specified controls are established.
- ◐
Pilot only
Promising, but insufficient evidence exists for broader adoption.
- ↺
Redesign
AI may be appropriate, but not in the proposed task or workflow.
- ✕
Not recommended
Current quality, governance, capability, data, or formation risks do not justify the use.
Make the right decision before investing in implementation.
- Unsuitable AI investment
- Premature AI-first drafting
- Downstream rework
- Increased consultant correction
- Sensitive-data exposure
- Translator dependence
- Weakened community ownership
- Unclear publication accountability
- Lower-risk AI uses
- Consultant capacity recovery
- Stronger checking
- Better research access
- Repetitive-task reduction
- Measurable pilots
- Clearer organizational decisions
The goal is neither to approve AI nor reject AI. The goal is to know where it produces defensible value and where human judgment must remain decisive.
This service does not:
- Certify a Bible translation as accurate or inspired
- Replace qualified consultant checking
- Replace community or church authorization
- Grant publishing approval
- Treat a machine score as proof of translation quality
- Claim certification on behalf of FOBAI, SIL, UBS, NIST, ISO, or UNESCO
Starting at $12,500
Human–AI Workflow Implementation
Move from experimentation to a tested operating model.
Selecting an AI tool does not answer when AI enters the process, what humans must complete first, who evaluates AI output, which decisions require consultant involvement, what should be documented, or whether the workflow actually improves the work.
We do not just train people on a tool. We design how the work should operate — mapping the current workflow for bottlenecks, repeated work, missing controls, quality problems, unclear responsibilities, work suitable for automation, and work essential to translator development.
Then we design the future workflow: human-first drafting, controlled AI-first drafting, or AI-assisted checking. The technology follows the translation need — not the other way around.
- We measure time to acceptable work, not time to machine output
- AI can produce Draft Zero fast while increasing translator revision
- …and consultant correction, rechecking, and source verification
- …and community retesting, training, and downstream repair
- Polished output can transfer effort downstream instead of creating productivity
- So Package 2 evaluates the whole workflow, not generation speed
Human–AI Workflow
See exactly where AI participates and where humans retain authority.
Task & Decision Matrix
Know who generates, reviews, interprets, recommends, approves, escalates, and suspends.
Project AI Use Policy
Define approved, restricted, and prohibited uses.
Approved Tool Framework
Evaluate tools against the actual use case, language, data, and security requirements.
Translator & Consultant Training
Train people not merely to operate AI — but to challenge it.
Controlled Pilot
Test the workflow on representative translation material.
Performance Dashboard
Measure more than initial drafting speed.
Final Adoption Recommendation
Adopt, modify, limit, retest, suspend, or discontinue.
- ✓
Adopt
The workflow demonstrated appropriate value.
- ⚠
Adopt with safeguards
Benefits exist, but additional controls are required.
- →
Expand gradually
Use the workflow only for selected projects, books, genres, or tasks.
- ◐
Limit AI
Use AI for checking, research, or back translation — but not initial drafting.
- ↺
Redesign & retest
There is potential, but the current model failed important criteria.
- ✕
Suspend or discontinue
The demonstrated risks outweigh the benefits.
Capture AI's useful efficiencies without transferring hidden costs to translators, consultants, or communities.
- Time to consultant-acceptable material
- Human rework
- Critical errors
- Consultant capacity
- Translation quality
- Translator capability
- Community response
- Workflow compliance
Starting at $45,000
Organizational AI Governance
Stop governing AI project by project.
As AI adoption expands, organizations accumulate personal AI accounts, unapproved tools, different standards across projects, bots and agents with unclear access, inconsistent data handling, duplicated software, unmanaged vendor relationships, undocumented AI influence, inconsistent consultant capability, and unclear accountability.
Package 3 moves the organization from asking “Should we use AI?” to asking “Where is AI already being used, what can it access, what is it permitted to do, and who is accountable?”
- AI landscape — what tools, models, agents, bots, integrations, and vendors exist
- Projects — which AI uses suit which translation contexts
- Data — what AI can access
- People — who owns each consequential decision
- Translation quality — what standards AI-assisted work must satisfy
- Governance maturity — are your rules visible, enforceable, measurable, repeatable
Organizational AI Policy
Define appropriate use across the agency.
AI and Agent Inventory
Know what is connected to organizational work and data.
Approved & Prohibited Tool Framework
Stop every project from independently deciding what is safe.
Project & Data Classification
Connect ministry context with AI and information risk.
Human Accountability Model
Establish named decision owners.
Translation Quality Standard
Make quality criteria explicit for AI-assisted work.
AI and Agent Security Guardrails
Control data access, identity, permissions, and consequential actions.
Consultant Competency Framework
Define the capability required to govern AI-assisted translation.
Pilot Governance
Require evidence before wider deployment.
Incident Response
Know how to respond when something fails.
Executive & Board Dashboard
Give leadership visibility into material AI risks and decisions.
12-Month Governance Roadmap
Move from policy creation into operating practice.
- 01
Which AI systems are we using?
And which are approved.
- 02
What data can they access?
And what agents are allowed to do.
- 03
Which project types may use AI drafting?
And which decisions require human approval.
- 04
Who owns the risk?
What requires escalation, and what would cause us to stop AI use.
Replace fragmented experimentation with one organizational system.
- Duplicate tools
- Shadow AI
- Inconsistent policies
- Repeated project-level governance
- Excessive permissions
- Avoidable security exposure
- Unclear ownership
- Duplicated evaluation effort
- Unmanaged AI agents
Starting at $95,000
Ongoing AI Translation Assurance
Governance should not end when the policy is published.
AI environments change continuously. Models change. Teams change. Projects enter new genres. Consultants change. Vendor terms change. Agents gain new connections. Exceptions become habits. Documentation declines.
What was responsibly approved six months ago may no longer be the system operating today. That is governance drift.
- Translation quality — are quality risks increasing
- Workflow compliance — are teams following the approved human–AI process
- Translator development — is AI developing people or creating dependency
- Consultant oversight — are consultants exercising meaningful judgment
- AI tools & models — have model or vendor changes altered the risk
- Security & data — are approved restrictions still operating
- Community participation — is local ownership being preserved
- Corrective actions — are identified problems actually being fixed
Quarterly Project Assurance Reviews
Independent, risk-based review.
Portfolio Quality & Risk Dashboard
One view across active projects.
Workflow Compliance Reporting
Evidence that approved process is followed.
Consultant Coaching
Sustained capability, not one-off training.
Translator Development Review
Capability growth, not dependency.
Model & Tool Advisory
Reassessment when the technology changes.
Incident & Corrective Action Tracking
Problems closed, on the record.
Executive & Board Risk Reporting
Material risks stated plainly.
- ✓
Effective
Controls are working as designed.
- ✓
Effective with observations
Working, with noted improvements.
- ⚠
Corrective action required
Specific fixes are tracked to closure.
- ⚠
Restricted
AI use narrowed until controls are restored.
- ✕
Suspended
AI use stops pending remediation.
Make sure AI's promised value survives real-world use.
- Rework
- Quality degradation
- Consultant overload
- Tool proliferation
- Shadow AI
- Data exposure
- Translator dependency
- Community-trust loss
- Governance drift
- Model changes
We call this value leakage — the difference between the benefit AI was expected to produce and the value actually realized.
Starting at $7,500 / month
08Side by side
Choose the decision you need to make.
| Decision | 1. Assess | 2. Implement | 3. Govern | 4. Assure |
|---|---|---|---|---|
| Primary question | Should we use AI here? | How should we use it? | How do we govern it? | Is it still working responsibly? |
| Scope | Project | Project | Organization | Portfolio |
| Readiness assessment | Translation + AI readiness | Included | Organization-wide | Continuous |
| Translation integrity baseline | Full | Included | Standardized | Monitored |
| Workflow design | — | Full | Standards | Audit |
| Tool assessment | Initial risk review | Full | Enterprise | Continuous |
| Training | Recommendations | Full | Organizational | Coaching |
| Pilot | Recommended | Run | Governed | Monitored |
| AI policy | Project recommendation | Project | Organization | Updated |
| Accountability | Map current decision rights | Implement | Institutionalize | Verify |
| Quality measurement | Integrity + value baseline | Pilot | Standardize | Monitor |
| Leadership reporting | Decision brief | Adoption decision | Governance dashboard | Recurring dashboard |
| Starting investment | $12.5K | $45K | $95K | $7.5K/mo |
Pricing shown is proposed starting pricing and is confirmed during scoping.
09Value
AI activity is not the same as AI value.
That is why measurement begins in Package 1 — not after the AI workflow has already been implemented.
An organization can increase every one of these and still create little meaningful value. The important question is: what changed because AI was introduced?
- AI users ↑
- Tokens consumed ↑
- AI-generated drafts ↑
- Agents deployed ↑
- Content produced ↑
- Time recovered
- Appropriate automation
- Increased consultant capacity
- Stronger visibility
- Faster research
- Better consistency detection
- Reduced repetitive work
- Increased organizational capability
- Downstream rework
- Consultant correction
- Quality problems
- Tool duplication
- Unapproved AI
- Sensitive-data exposure
- Translator deskilling
- Community distrust
- Policy failures
- Excessive agent permissions
We measure financial return, risk-adjusted return, and mission or human-capability return separately, rather than inventing questionable monetary values for theological formation or community trust.
10Our position
We are not selling AI adoption. We are helping organizations decide where technology belongs.
- Suggest
- Generate
- Compare
- Organize
- Detect
- Retrieve
- Interpreting
- Discerning
- Evaluating
- Deciding
- Approving
- Accepting accountability
That principle runs through the whole package architecture: the consultant and responsible human actors govern the process rather than being displaced by it.
You don't need another AI strategy document. You need to know what decision to make next.
Considering AI?
Start with readiness.
Already experimenting?
Design the workflow.
Scaling across projects?
Establish governance.
Already operating at scale?
Add ongoing assurance.
Not sure where you belong? Start with a 30-minute AI Adoption Conversation.
- Your current stage
- The problem you are actually trying to solve
- Whether an assessment is needed
- Which package fits
- Whether Human + Machine Works is the right partner
Not ready to talk yet?
Take the 5-minute AI Readiness Snapshot