Revolutionizing Translation with AI – Boost Accuracy and Speed for Medicare Advantage Materials

The Translation Imperative

For MAOs, translation is not optional—it’s a legal and ethical necessity. As Sohail Malik explains, “Medicare Advantage plans are required to translate key mandated communications to ensure that all enrollees, especially those with limited English proficiency, can fully understand their benefits.” These include documents such as the Evidence of Coverage (EOC), Annual Notice of Change (ANOC), Summaries of Benefits (SB), enrollment forms, pharmacy directories, and appeal or grievance notices.

At the federal level, CMS imposes rigorous standards and oversight mechanisms, including routine program audits, beneficiary feedback monitoring, and requirements around language access plans. MAOs must must translate their documents into any language spoken by 5% or more of a plan’s service area population. States often layer on additional rules, particularly for D-SNP plans. In some states, materials must be provided in over 20 languages.

Malik also cited consumer expectations as a growing force: “Forrester research shows 76% of consumers prefer to buy from organizations that serve them in their preferred language. Forty percent won’t buy at all if they’re not served in that language.” Translation quality, in other words, is becoming a competitive differentiator.

The Key Issues with Translation Today

Despite its importance, translation is often treated as an afterthought, tacked onto the end of the content lifecycle. “Most workflows assume a perfect world where everything goes according to plan,” Malik noted. “But in reality, delays and disruptions happen all the time.” The result is a compromise triangle—organizations must sacrifice either cost, speed, or quality.

Current workflows are document-centric, meaning content is translated in full each time. This leads to unnecessary repetition, added cost, and increased risk of errors. Even when translation memory tools are in place, variations in data or formatting can render past translations unusable. “The process is incredibly complex, with multiple rounds of proofreading, remediation, and desktop publishing. It’s expensive, manual, and fundamentally unscalable,” Malik said.

As plan variations and language requirements grow, the inefficiencies of this model become more painful—and more risky. This sets the stage for the next part of the discussion: how generative AI offers a better way forward.

How Generative AI Can Help with Medicare Advantage Translation

Generative AI has the potential to transform how Medicare Advantage Organizations approach translation, but only if it’s applied thoughtfully. As Patrick Kehoe put it, “This is not the metaverse. This is not Google Glass. This is not some passing fad. It’s a foundational shift.” But for highly regulated industries like healthcare, that shift must be supported by structure, not just speed.

When used properly, generative AI reduces the need for costly, fully manual translation workflows. Rather than relying on humans to translate entire documents from scratch, AI can handle first-draft translation, while human reviewers focus on nuanced refinement. Patrick notes “Research has shown this hybrid approach can drive costs down to as little as five percent of traditional methods.”

However, to be used safely, generative AI systems must be guided by guardrails. Kehoe emphasized that “AI in the wild is like a junior employee. They’re eager and confident, but they don’t know your standards. You have to constrain them.” Without those constraints—like embedded glossaries, prompt engineering, and accuracy checks—AI can generate content that looks polished but fails compliance checks or introduces errors in variables, styles, or sentiment.

What to Look for in a Translation Solution

When evaluating solutions, the panel urged attendees to dig deeper than surface-level claims of “AI-powered translation.” Ask whether the vendor is actually using AI to reduce cost or simply to speed up internal processes—without passing the savings on to you. Organizations evaluating their options should consider whether a translation tool supports the following:

• Modular content translation: The system should support content-level translation rather than full document translation to reduce duplication and rework.
• Prompt engineering baked in: Users shouldn’t need to write their own prompts or hope for consistent results from generic AI tools. The system should handle this behind the scenes.
• Glossary support: Incorporating plan-specific and CMS-mandated terminology into the translation engine ensures consistency across languages and documents.
• Variable and formatting preservation: The solution must maintain document formatting, structure, and dynamic variables such as benefit values or contact details—critical for compliant communications.
• Workflow integration: Look for platforms that support simultaneous, role-based workflows for human and machine translation, with built-in visibility and approvals.

Automating QA with AI accuracy checks

One of the most compelling use cases for AI is in automating quality assurance. Manual QA processes—often spreadsheet-driven and error-prone—are a major bottleneck. AI accuracy checks automate comparison between English and translated content, flagging issues like semantic differences, omitted or incorrect variables, and formatting mismatches

AI surfaces only the potential problem areas, allowing human reviewers to focus where they’re truly needed. The result: faster turnaround times and higher quality output. In fact, Patrick noted that when reviewing previously certified client materials, Messagepoint found error rates of 1–5%—errors that had gone undetected through traditional QA alone.

Real-World Impact of AI Translation in Medicare Advantage

The benefits aren’t hypothetical. Organizations adopting purpose-built solutions for managing their CMS-compliance materials with integrated are seeing concrete, repeatable gains:

• Speed: Translations can be completed within 24–48 hours of English content finalization.
• Cost savings: Plans are reducing translation and QA costs by as much as 60%.
• Scalability: Teams can manage simultaneous translations in 20+ languages without additional headcount.
• Compliance confidence: AI QA checks flag issues humans miss, reducing risk in regulated environments.

This impact was especially critical during the 2024 AEP when CMS released a memo which impacted ANOCs just weeks prior to the deadline, which left plans with only days to incorporate changes.

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