By Lee Allen Miller, Executive Director
Your station’s website, social media feeds, and email communications are the digital front door of your broadcast operation. For many viewers, particularly younger ones, the digital presence is the primary way they interact with your brand, even if the broadcast signal is still where most of your revenue comes from. For most LPTV stations, the digital side is under-resourced, often handled by someone whose main job is something else entirely.
This is a natural place for AI tools to help. The work is high-volume, relatively lower-stakes than on-air editorial, and full of tasks that benefit from first-draft assistance. Let me walk through how stations are using AI tools effectively in their digital operations and what the sensible guardrails look like.
Social media post drafting and scheduling
The most common and most practical AI application for social media is first-draft post creation. Given a story, an event, or a piece of programming, AI can produce a reasonable draft post for various platforms, adjusted for each platform’s style and character limits. A post for Facebook will read differently from one for X or Instagram, and AI tools handle those differences reasonably well.
The person running your social media still needs to review the drafts, adjust tone, add station voice, and make sure the content reflects actual judgment about what should be posted. But starting from a first draft rather than blank space makes the difference between posting twice a day and posting six times a day. For a station trying to maintain an active presence on limited staff, that is a meaningful capacity difference.
AI tools are also useful for producing variations of the same core message for different platforms and different audience segments. One news story might warrant different framing for your main station Facebook page, your news-specific Twitter account, and your community-focused Instagram feed. Producing those variations manually is tedious. Producing them with AI assistance takes a fraction of the time.
Website content support
Most station websites suffer from outdated content, inconsistent quality, and a lack of regular updates. Not because stations don’t want to do better, but because the work of maintaining a content-rich website competes with everything else a small station is trying to do.
AI tools can help here in several ways. Drafting station pages. Updating program descriptions. Producing longer-form content based on reporting or station information. Generating alt text for images. Producing metadata for SEO. Writing email newsletter content that integrates website content.
The quality consideration is the same as for social. The AI produces a first draft. A human reviews and finalizes it. Generic AI-written web content is easy to recognize and reflects poorly on the station. Human-edited AI-assisted content can be indistinguishable from content written from scratch, at a fraction of the time.
Community engagement and response
Social media is not a one-way broadcast. It involves responding to comments, questions, and mentions. Handling this at volume is time-consuming, and small stations often simply let comments go unanswered.
AI tools can help here in a limited way. Drafting responses to common questions. Suggesting engagement language for different situations. Flagging comments that need human attention because they involve complaints, misinformation, or sensitive topics. What AI should not do is respond autonomously to viewers as if the station were responding. That kind of automated response breaks the implicit promise of social engagement and usually produces bad outcomes when it goes wrong.
The model I would recommend is AI-suggested responses with human review before posting. Faster than writing every response from scratch, more authentic than fully automated responses, and less likely to create embarrassing incidents.
Visual content and graphics
AI image generation has improved dramatically, and it is increasingly used for social media graphics, web illustrations, and other visual content. This is an area where stations need to be careful about several specific issues.
First, disclosure. If you are using AI-generated imagery in contexts where viewers might assume it is a photograph or actual representation of a real event, you need to disclose that the image is AI-generated. This matters for credibility and increasingly matters for legal reasons as regulations around AI content disclosure develop.
Second, accuracy. AI image tools can produce images that look real but contain inaccuracies or inappropriate content. They can generate misleading representations of real events, places, or people. Using them in news or informational contexts requires particular care.
Third, rights and licensing. AI-generated content exists in a developing legal landscape around copyright and usage rights. What you can safely use depends on the specific tool, its terms of service, and how the content was generated. Getting legal clarity before using AI-generated imagery in commercial contexts, particularly for advertising, is worth the effort.
Used carefully, AI-generated visuals can enrich your digital presence. Used carelessly, they can create legal exposure and credibility problems. Station policy should cover this specifically.
Email newsletters
Stations that maintain email lists for their audience have an underutilized channel that AI tools make more practical to use well. Writing a weekly or biweekly newsletter is time-consuming. AI-assisted newsletter drafting can reduce that time significantly while allowing for personalization and segmentation that would be impractical otherwise.
The content still needs to come from somewhere. AI does not know what is happening at your station or in your community unless you tell it. Given that input, it can produce drafts that your communications person edits into final form. The output is better than what many stations currently produce, at a fraction of the time.
Analytics and optimization
AI tools can also help with the analytics side of digital presence. Analyzing which posts perform well and why. Identifying patterns in audience engagement. Suggesting content types and posting times that might work better. Summarizing performance across platforms for management reporting.
This is routine analytical work that is well suited to AI assistance. It does not replace having a person who understands your station’s goals and audience, but it can make that person’s analysis faster and more systematic.
Policy considerations
A few specific policy points worth addressing at any station using AI for digital communications.
Disclosure standards. When, if ever, do you tell your audience that content was AI-assisted? This is a developing area, and different stations are making different choices. Having a clear policy, whatever it is, is better than making ad hoc decisions that may be inconsistent.
Content approval. Who reviews AI-assisted content before it posts? What are the standards? How are errors caught and corrected? Digital content moves fast, and mistakes can be embarrassing or worse. Clear approval processes protect the station.
Voice and identity. Every station has a voice. AI tools will produce content in a default voice that may not match yours. Training your team to edit AI output toward your station’s voice is part of using these tools well. Content that reads as generic AI output undermines your brand, even when it is factually accurate.
Brand safety. AI tools can occasionally produce content that is inappropriate, offensive, or inconsistent with your station’s values. The risk is low with reputable tools used reasonably, but not zero. Review processes need to account for this possibility.
A realistic view of the opportunity
For most LPTV stations, the digital operation is a high-leverage place to apply AI tools. The work is high volume, the stakes per item are lower than on-air editorial, and the productivity gains are immediate and measurable. A station that thoughtfully applies AI to social media, website content, and email communications can often double or triple the volume of its digital output while maintaining or improving quality, at modest additional cost.
That productivity gain, if well used, supports better audience relationships, stronger sales conversations, and more effective community engagement. That is worth investing in, and it is well within reach of LPTV stations today.
