Question 203 of 506
AI FundamentalshardMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the scoreThreshold of 70 excludes many actions, so fewer than 5 meet the criteria. This occurs because the scoreThreshold parameter acts as a hard filter, discarding any recommendation with a score below 70 before the system considers the maxRecommendations limit. Even though the JSON sets maxRecommendations to 5, the actual number returned is capped by how many actions survive the threshold; if only two actions score 70 or higher, only two will appear. On the Salesforce AI Associate exam, this scenario tests your understanding of how Einstein Next Best Action prioritizes scoring over count—a common trap is assuming maxRecommendations guarantees that many results, when in reality the scoreThreshold can reduce output. Remember the mnemonic: “Threshold trumps count; low scores drop out.”

AI Associate AI Fundamentals Practice Question

This AI Associate practice question tests your understanding of ai fundamentals. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

Refer to the exhibit.

{
  "type": "EinsteinNextBestAction",
  "recommendationStrategy": "Most Likely to Convert",
  "filters": {
    "object": "Lead",
    "field": "Status",
    "operator": "equals",
    "value": "Open"
  },
  "maxRecommendations": 5,
  "scoreThreshold": 70
}

Refer to the exhibit. An admin configures Einstein Next Best Action with the above JSON. The expected behavior is to recommend the top 5 actions for open leads with a score of at least 70. However, only 2 recommendations appear for some leads. Which is the most likely cause?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "best"

    Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

  • Clue: "most likely"

    Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

  • Clue: "least"

    Why it matters: You want the option with minimum overhead, fewest steps, or lowest impact — not the most feature-rich or comprehensive answer.

Question 1hardmultiple choice
Full question →

Exhibit

Refer to the exhibit.

{
  "type": "EinsteinNextBestAction",
  "recommendationStrategy": "Most Likely to Convert",
  "filters": {
    "object": "Lead",
    "field": "Status",
    "operator": "equals",
    "value": "Open"
  },
  "maxRecommendations": 5,
  "scoreThreshold": 70
}

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

The scoreThreshold of 70 excludes many actions, so fewer than 5 meet the criteria.

Option B is correct because the scoreThreshold of 70 filters out any actions with a score below 70. If fewer than 5 actions meet this threshold, the system returns only those that qualify, resulting in fewer than 5 recommendations. The maxRecommendations setting defines the upper limit, but the actual number returned is constrained by the scoreThreshold.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • The filter on Lead Status is incorrectly excluding actions.

    Why it's wrong here

    The filter is on the lead object, not actions.

  • The scoreThreshold of 70 excludes many actions, so fewer than 5 meet the criteria.

    Why this is correct

    Score threshold filters out low-scoring actions.

    Clue confirmation

    The clue words "best", "most likely", "least" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • The recommendation strategy is misconfigured for this object.

    Why it's wrong here

    The strategy is valid.

  • The maxRecommendations is set to 2 instead of 5.

    Why it's wrong here

    It is set to 5 in the JSON.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Salesforce often tests the interaction between scoreThreshold and maxRecommendations, where candidates mistakenly assume maxRecommendations is the sole determinant of the number of recommendations, overlooking that scoreThreshold can reduce the count below that limit.

Detailed technical explanation

How to think about this question

In Einstein Next Best Action, the scoreThreshold parameter acts as a minimum score filter that is applied before the maxRecommendations limit. If only 2 actions have a score of 70 or higher, the system returns exactly those 2, ignoring the maxRecommendations of 5. This behavior ensures that low-scoring actions are never recommended, even if the desired count is not met, which is critical for maintaining recommendation quality in CRM scenarios like lead scoring.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A practitioner preparing for the AI Associate exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this AI Associate question test?

AI Fundamentals — This question tests AI Fundamentals — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: The scoreThreshold of 70 excludes many actions, so fewer than 5 meet the criteria. — Option B is correct because the scoreThreshold of 70 filters out any actions with a score below 70. If fewer than 5 actions meet this threshold, the system returns only those that qualify, resulting in fewer than 5 recommendations. The maxRecommendations setting defines the upper limit, but the actual number returned is constrained by the scoreThreshold.

What should I do if I get this AI Associate question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "best", "most likely", "least". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.