The news: AI is revolutionizing the way social media managers (SMMs) work, but spending on the tools is surprisingly low.

• 73% of SMMs, content creators, entrepreneurs, and marketers use AI daily, per Metricool’s 2025 State of AI in Social Media report. Two-thirds create at least half their content with it.
• Over half (52%) spend nothing on AI tools each month, and only 8% spend over $50 per month.

Where it’s going: AI is mostly used in broad, upper-level tasks like content ideation, adaptation, and creation rather than mundane activities and direct engagement with consumers.

• 78% rely on it for generating content ideas, 72% for writing copy, and 68% for tailoring tone and platform fit.
• Only 20% use AI to automate repetitive tasks, and just 18% apply it to respond to social media comments.

High use but low investment: While AI is transforming social media management, it’s doing so on a budget. Sixty-two percent of SMMs have no plans to increase AI spending this year.

• This means that, while much of marketers’ work depends on AI, few are willing to invest in the tools.
• The minimal spending suggests AI is being treated as a free productivity hack rather than a tool worth investing in.

While powerful AI tools including ChatGPT, Perplexity, and Gemini offer free versions, these no-cost accounts may expose companies to security risks should proprietary company information be pulled into model training.

Lack of oversight: Although adoption is high, strategic use may also be lagging. More than one-third (36%) of SMMs don’t know or track that performance.

This indicates a gap between usage and oversight.

• Many teams are relying on AI without clear KPIs or evaluation metrics.
• The lack of performance tracking suggests AI is viewed more as a tool of convenience rather than a data-supported asset.

Our take: Failing to monitor AI’s benefits and limitations could hinder teams’ ability to optimize content or justify investment to higher-ups. CMOs should recognize that adoption alone is not a strategy: Tie outputs to performance data, invest in secure tools, and incentivize teams to move beyond surface-level use to capitalize on AI’s potential.