AI marketing & MarTech
AI video localisation: the Enel result and your process
Understand the reported Enel cost result. Plan an AI video localisation workflow with language review, voice permissions and complete cost measures.
My professional profile reports a 75% cost reduction for AI multilingual video localisation at Enel. The measure concerns cost. It should not be described as a 75% reduction in hours, workload or production time.
The available record does not publish source languages, suppliers, volumes, the cost baseline or a formal quality comparison. Those details cannot be reconstructed from the headline. The result is owner-reported career context, not a public comparative study.
For your project, the useful question is how to evaluate the complete localisation process. Translation, spoken output, review, timing, accessible alternatives and publishing all affect whether the final asset is acceptable.
This article gives you a practical approach to that evaluation. The workflow is proposed guidance and the worked example is hypothetical. Neither describes undocumented technical choices in the Enel initiative.
For the broader context, read AI for marketing.
Separate translation, dubbing and localisation
Translation transfers meaning between languages. Dubbing adds spoken delivery to an existing video. Localisation also considers audience, terminology, conventions and presentation. These tasks overlap, but success in one does not prove success in the others.
A sentence can preserve the basic meaning and still sound unnatural when spoken. A fluent spoken line can omit a necessary condition. A correct line can be too long for the visual segment where it needs to appear.
Define the intended audience and purpose before production. An internal training video, an external product explanation and a short campaign asset need different review priorities. Specify which wording must remain exact and which parts may be adapted.
Also define the output package. The task may include audio, captions, transcripts, descriptions and publishing metadata. If the comparison covers only the audio generation step, call it that rather than reporting it as full localisation cost.
Prepare a source that reviewers can trust
Use an approved source script or transcript. Check that it matches the current video and includes information necessary to understand the message. If the source is ambiguous, resolve the ambiguity before translating.
Create a terminology record for names, product terms and approved phrasing. Explain why a term is fixed and where adaptation is allowed. This supports consistency without forcing unnatural word-for-word translation.
Keep source ownership explicit. Someone must decide whether a product claim, condition or date is current. The AI system and language reviewer should not need to invent that authority.
The AI content workflow guide covers factual hand-offs. A sound localisation process begins before the translation tool receives the script.
Evaluate meaning in each language
Give the reviewer the original and adapted text. Ask them to assess preserved meaning, required conditions, terminology, tone and naturalness. Separate material errors from stylistic preferences.
Include difficult cases in the evaluation: ambiguous phrasing, abbreviations, names and sentences that depend on visual context. The easy passages alone cannot establish readiness for the whole asset.
NIST's Generative AI Profile identifies confidently incorrect content as a risk. For localisation, the practical concern is an output that sounds plausible while changing the source message.
The AI localisation quality guide offers a more detailed bilingual rubric. The reviewer needs enough context to identify consequences, not just enough language knowledge to correct grammar.
Check spoken delivery and synchronisation
Listen to the rendered audio rather than approving the script alone. Inspect pronunciation, emphasis, pauses, speed and consistency. A text revision can alter spoken timing and require another production pass.
Check the relationship between audio and visuals. Important information may appear on screen while the narration discusses something else. A natural voice does not make that mismatch understandable.
Avoid shortening a translation by deleting conditions. If the line is too long, revise the phrasing with a language reviewer or adjust the production where possible. Timing should not silently override meaning.
Define who approves the final combination. The language reviewer may judge meaning; a production reviewer may judge synchronisation. The publishing owner needs to know that both have been checked. Record the version they approved.
Plan voice use and permissions
Clarify the source of the voice and the intended use. A licensed stock voice, a customised voice and a voice resembling a known person raise different questions. Check relevant permissions and supplier conditions before using the material.
Microsoft's custom voice documentation describes a voice-talent consent statement for its service. This is a concrete supplier requirement, not a claim that every platform has identical conditions.
Do not imply that a person spoke or endorsed a message when they did not. Give the audience an appropriate explanation of the production where needed, and assign responsibility for reviewing that presentation.
Retain the permission record with the asset and its permitted contexts. A workflow that can generate many versions quickly also needs to know where those versions may be distributed.
Include accessibility in the production plan
Prepare captions and transcripts for the appropriate media context. Review their accuracy, timing and usability. Automatically generated text can contain the same terminology and meaning errors as the audio.
The W3C media planning guidance explains why accessibility should be planned during creation. Consider relevant visual information and the usability of the player as well as the spoken track.
A translated caption file is not automatically equivalent to the localised audio. Check consistency between script, narration and captions. If one changes, identify which companion assets need updating.
Name an owner for the accessible package. Otherwise it can become a final hand-off with no acceptance criteria. Measure the task through publication readiness rather than celebrating that the audio export finished.
Hypothetical example: localising an internal tutorial
Imagine a company adapting a short internal tutorial into Italian and English. This is a fictional example and is not an Enel production. The video explains an ordinary workflow with several on-screen steps.
The team approves the source and identifies terms that must remain consistent. A tool creates draft translations. Language reviewers check meaning and adapt spoken phrasing. A permitted synthetic voice then produces the audio.
Production review checks that each instruction aligns with the on-screen action. The team corrects a line that was accurate in text but too fast to understand when spoken. It also updates the captions to match the approved audio.
The evaluation records effort through an acceptable final package, including corrections. It does not count the first audio export as a completed task. If a language requires much more review, that difference stays visible in the cost comparison.
Calculate cost on a comparable unit
Choose the unit: an approved minute, an approved asset or a defined output package. Use the same unit and acceptance criteria for the current and proposed processes.
Include source preparation, translation, audio generation, editing, review, retries, accessibility and publication work. A lower supplier charge can be offset by more internal checking. Count both where they affect the decision.
As a purely hypothetical arithmetic example, reducing a comparable completed-task cost from €400 to €100 would be a 75% reduction. These figures are not Enel costs or supplier prices. They only illustrate how a relative cost change is calculated.
Do not convert that percentage into hours saved. A cost change can arise from several factors and says nothing specific about task time without separate measurements. The marketing automation ROI guide explains that benefit distinction.
A localisation-readiness worksheet
Use this before scaling the workflow.
Swipe or use the arrow keys to see every column.
| Area | Evidence to check | Decision question |
|---|---|---|
| Source | Approved script and current video | Is the starting information reliable? |
| Language | Bilingual review and error categories | Is meaning preserved for this audience? |
| Voice | Permissions and supplier conditions | Is the intended use supported? |
| Production | Listening and visual alignment | Is the spoken package understandable? |
| Accessibility | Checked companion assets and player | Can the intended audience access it? |
| Cost | Comparable completed-task records | Does the net benefit remain worthwhile? |
| Updates | Versions and source ownership | Can changed information be corrected? |
Complete the table with actual records. An attractive average score should not conceal a material meaning error or missing permission. Those conditions may block a particular release.
The worksheet also helps define a narrower supported use. You may be ready for internal tutorials with stable terminology but not external claims requiring different expertise. Keep the approval tied to the tested scope.
Compare tools without borrowing the headline
Run the same suitable tasks through candidate approaches. Give reviewers the same rubric and record setup and correction work. The AI marketing tool evaluation guide explains the comparison.
Check export, version control and integration with the approval route. A tool can generate acceptable audio and still make publishing or updates difficult. Evaluate the process around the output.
Do not assume the reported Enel percentage identifies the right tool. The public profile does not disclose the supplier or detailed workflow, and the result does not predict another project's economics.
The article on enterprise AI video and podcasts examines the related production questions while keeping the reported initiatives separate.
Maintain the localised asset after release
Assign ownership for changes to the source. When a condition or step changes, identify the affected scripts, audio tracks and companion files. A localised asset can become outdated even if it was accurate on approval.
Preserve a link between the source, language review and final version. It should be possible to identify what was approved and which materials need correction. Avoid retaining only the latest generated audio with no context.
Include a withdrawal route when the asset is no longer suitable. People should not continue using an old instruction because the team knows how to create content but has no process for retiring it.
Make the next commitment proportionate
The Enel result remains an owner-reported 75% cost reduction in AI video localisation. For your workflow, the next step is a bounded evaluation with comparable quality and cost measures.
Choose representative assets, agree the rubric and name the owners. Expand when the evidence supports the next scope, rather than importing another project's percentage into the business case.
Discuss your AI video localisation workflow if you need to connect language quality, production, permissions and measurable operating value.
Apply this to your project
Tell me the decision you are facing, the constraints and what you have already tried.
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