In 2026, AI is transforming performance reviews. Factorial's 2026 guide describes AI that "summarizes employee data, goals, past reviews, and 1:1 notes into a clear outline" and "suggests improvements for tone, clarity, and actionable feedback." AIHR reports that LLMs "automatically generate summaries of multiple feedback sources." Betterworks describes AI producing "performance reviews or conversation points that are professional and unbiased." Teamflect says AI-assisted wording "translates observations into clear, actionable feedback that employees can actually use." SHRM reports the rise of "personalized AI coaches" as the next evolution beyond annual reviews.

But Forbes' 2026 analysis captures the tension: "Whether AI becomes a tool for fairer, more consistent feedback — or a mechanism that amplifies existing blind spots and erodes trust — depends on the choices executives and HR leaders make right now."

One of those choices is whether AI-generated feedback is readable. A performance review the employee cannot understand does not drive improvement. It generates frustration, erodes trust, and wastes the entire review process.

The performance review readability problem

1. Corporate HR jargon

AI-generated performance reviews tend to use HR terminology: "demonstrates competency in cross-functional collaboration," "opportunities for growth in stakeholder management," "shows alignment with organizational values and strategic objectives." These phrases are precise for HR professionals and meaningless to the employee who needs to understand what they did well and what to improve.

2. Vague feedback

TechnologyAdvice's 2026 review of AI performance review generators tested 8 tools against a profile of "a solid employee with clear wins, useful strengths, and a few development gaps." The finding: some tools produce "balanced feedback" while others produce vague generalities. AI-generated reviews that say "demonstrates strong performance in key areas while continuing to develop in growth opportunities" do not tell the employee anything actionable.

3. Formal register in a personal context

Performance reviews are personal — they are about an individual's work, behavior, and growth. AI-generated reviews tend to sound like organizational assessments: "The employee has exhibited consistent adherence to process guidelines and demonstrated satisfactory compliance with organizational standards." The employee needs to hear: "You follow our processes well. Keep it up." The formal version is accurate but alienating.

4. The comprehension-action gap

The purpose of a performance review is behavior change: the employee should understand what they did well, what they need to improve, and how to improve it. Teamflect's guide emphasizes "actionable feedback that employees can actually use." If the employee cannot understand the feedback, they cannot act on it. The review becomes a documentation exercise, not a development tool.

Why AI-generated performance reviews are hard to read

1. HR documentation as training data

AI review tools train on performance review templates, HR policy documents, and corporate competency frameworks — all written in HR-speak at a professional reading level. The generated reviews reproduce this register.

2. Completeness over actionability

AI tools optimize for covering all the competencies, all the goals, all the feedback sources. This produces comprehensive reviews that cover everything but highlight nothing. The employee reads 2,000 words of feedback and cannot identify the 3 things they should focus on.

3. The bias toward "professional" language

Factorial's AI "suggests improvements for tone, clarity, and actionable feedback." But "improved tone" in the HR context often means "more formal and professional" — which is the opposite of "more readable." The AI makes the review sound more professional, which makes it less personal and less actionable.

4. The Lattice warning

Lattice's 2026 guide warns about "the frightening scenario of having an employee find out that their manager cared so little about them and their review that they punted the task to ChatGPT." AI-generated reviews that sound like AI — formal, generic, dense — erode trust. Readable, personal feedback builds trust.

The fix: readable, actionable feedback

The fix is to make performance reviews readable and actionable:

1. Lead with 3 key takeaways — what the employee did well, what

to improve, and one specific action to take

1. Use plain language — no HR jargon, no corporate terminology,

no vague generalities

1. Be specific — cite specific behaviors, specific projects,

specific outcomes

1. Be actionable — every piece of feedback should include a

specific action the employee can take

1. Be personal — the review should sound like it was written by

a person who knows the employee, not generated by a system

How ELI5 AI helps HR teams

ELI5 AI is a free, no-login text simplifier that takes any performance review feedback and rewrites it at a 5th-grade reading level with four levels side-by-side: 5-year-old, 10-year-old, teenager, and adult.

For HR teams, the workflow is:

1. AI generates the performance review (using Factorial, AIHR

tools, or ChatGPT/Claude)

1. Paste the review into ELI5 AI — get a plain-language version

at four reading levels

1. Use the appropriate level:

• Adult level for the full review (professional but clear)
• Teenager level for the key feedback summary (direct and

actionable — the version the employee reads first)

• 10-year-old level for the 3 key takeaways (what you did well,

what to improve, one action to take)

• 5-year-old level for the one-sentence takeaway (the single

most important piece of feedback)

1. Add specific examples — the simplified review should include

specific behaviors and projects, not just generalities

1. Make it personal — review the simplified version and add

personal context that shows the manager knows the employee

What HR teams should do now

• Audit your AI-generated performance reviews for readability.

Sample 10 recent AI-generated reviews. Read each one as if you were the employee. Can you identify what you did well, what to improve, and one action to take? If not, the review needs a readability pass

• Simplify the key feedback. Use

ELI5 AI to produce a plain-language version of every AI-generated review. The simplified version should be the one the employee reads first

• Lead with 3 takeaways. The employee should not have to read

2,000 words to find the 3 things that matter. Put them at the top

• Remove HR jargon. "Demonstrates competency in cross-functional

collaboration" means "works well with other teams." Use plain language

• Be specific and actionable. Teamflect's guide emphasizes

"actionable feedback that employees can actually use." Every piece of feedback should include a specific action

• Follow the Lattice principle. Lattice warns about employees

discovering their review was "punted to ChatGPT." The review should sound like a person wrote it — and the best way to ensure that is to write it in plain language, which is how people actually communicate

• Track improvement against readability. Compare performance

improvement after reviews at different reading levels. If employees who receive simplified reviews improve more, readability is a performance management metric

• Prepare for AI coaching. SHRM reports the rise of AI coaches

replacing annual reviews. AI coaching feedback needs the same readability layer — the employee needs to understand the coaching to act on it

The bottom line

Performance reviews exist to drive improvement. But a review the employee cannot understand does not drive improvement — it drives frustration. AI can generate comprehensive, professional, unbiased reviews. But if the review is in HR jargon at a college reading level, the employee cannot act on it, and the review process has failed its purpose.

The HR teams that add a readability layer to their AI-generated performance reviews will produce feedback that employees can understand, act on, and trust. The HR teams that do not will keep generating professional but incomprehensible reviews — and wondering why performance improvement is flat.

A performance review the employee cannot read is not feedback. It is an HR document. Plain language turns it into feedback that drives improvement.

Try it: paste any performance review feedback into ELI5 AI and get a plain-English version that employees can understand and act on — four reading levels, no account required.