Evaluating AI-driven influencer discovery recommendations requires attention to certain crucial factors:

1. Relevance of Influencers: Check whether the recommended influencers align with your brand’s industry, audience demographics, and values. It is important to ensure that their content and audience align with your brand requirements.

2. Engagement Rates: Look at the engagement rates of these influencers. High follower count is not always a reliable metric. An influencer with high engagement rates will typically have a more active and involved audience.

3. Authenticity: Scrutinize the influencers’ past endorsements. Authentic influencers are those who stay true to their own style and persona, even when promoting products.

4. Consistency: Consistency in posting is a strong indicator of an influencer’s dedication. Check if they post regularly and maintain a consistent message across posts.

5. Past Performance: Look up past campaigns run by the influencers. This will give you an idea about the success rate of their previous collaborations.

In the context of influencer marketing platforms, some platforms like Flinque incorporate AI algorithm to help with these evaluations. It provides a comprehensive glance at infuencers’ performance metrics, audience demographics and sentiments, campaign history, brand alignment, and more. It can considerably streamline the process of influencer discovery and vetting.

Nevertheless, the best-fit platform is one that aligns with specific team needs. The strength of AI-driven recommendations lies in their objectivity and scalability. Yet, they should be seen as a tool to aid manual assessments, not replace them. Human judgement remains crucial in making the final decision. In reality, blending AI insights with manual scrutiny can yield the best results in influencer discovery and evaluation.