I’ve been wrestling with this for a while now, and I think we’re at an inflection point with how AI is reshaping influencer discovery and vetting. For years, I was doing a lot of manual research—checking engagement rates, scrolling through follower lists, trying to spot fake accounts. It was exhausting and honestly, pretty unreliable.
Recently, I started experimenting with AI-powered vetting tools, and it’s genuinely different. Not in a “set and forget” way, but in how it’s changing the quality of decisions I’m making. These tools use predictive analytics to look beyond surface metrics—they’re analyzing audience authenticity in real time, flagging suspicious engagement patterns, and even predicting campaign performance before I sign a contract.
What fascinates me most is the fraud detection side. We’ve all been burned by influencers with inflated numbers or bot-heavy audiences. AI is getting scary good at catching this. I’ve seen tools use machine learning to profile legitimate engagement versus artificial amplification. It’s reducing our wasted spend significantly.
But here’s what I’m grappling with: AI is amazing at surfacing data-backed influencers, but it can’t catch cultural fit or authenticity with brand values the way a human conversation can. The best approach I’ve found is using AI to shortlist and vet, then having my team spend quality time with the influencers who pass the first cut.
I’m also curious about how predictive analytics are helping you forecast ROI before a campaign launches. Are you seeing AI tools actually predict performance accurately, or is it still too early to rely on those projections?