Trusted AI + Human Expertise
How enterprises are redesigning review, quality workflows, and governance for Language AI
A Slator report, produced in collaboration with Vistatec
AI translation reached production faster than most localization teams had planned for. The output is good enough to use, and that is exactly why the difficult questions have changed. Teams now have to decide which content can go out unreviewed, which needs a linguist, and which needs a certified specialist. They also have to show auditors, regulators, and their own leadership how they made those calls.
Slator conducted research with enterprise localization leaders to document how those decisions are being made in practice. As a result, the report works as a guide you can apply to your own program, with frameworks you can lift straight into a planning session.
28% of enterprise buyers name output quality and accuracy as their top priority for Language AI.
18% prioritized compliance, auditability, and risk control.
Online Event
Join the live launch with Slator and Vistatec
On October 29 at 4 PM (GMT) | 9 AM (PDT)
Slator and Vistatec will walk through the findings live and take questions from the audience.
What we will cover
- What Slator’s buyer survey says about enterprise priorities for Language AI
- How localization teams are tiering content by risk and concentrating human review where it counts
- A practical routing matrix for deciding between AI-only, AI-assisted, and human-led workflows
- How to test and requalify a workflow each time a new model is released
Everyone who registers will receive the full report, Trusted AI + Human Expertise, when the session ends.
Speakers
Alex Edwards
Head of Consulting,
Slator
Simon Hodgkins
CMO,
Vistatec
Inside the report
- What enterprise buyers rank as their top priorities for Language AI, and where cost sits against quality and risk
- The governance questions each vertical should be asking, with examples for seven industries including life sciences, finance, and technology
- Seven areas where buyers and Language Solutions Integrators can share the work, starting with classifying content by risk
- A four-tier routing matrix that matches each content type to the right level of review and monitoring
- An eight-step process for testing a new model before it touches production content
Who should read it?
The report is written for heads of localization, globalization program managers, and content operations leads who are scaling AI translation. In addition, it gives quality, compliance, and regulatory colleagues a clear view of how multilingual content can be governed when AI produces the first draft.