The State of AI Marketing in 2025 - What's Helpful (& What's Hype)

By Dan Sanchez · Episode published

Use AI marketing with practical discipline: learn one workflow at a time, apply an ethical standard to generated media, and verify capability claims before relying on them.

Get the next practical AI marketing episode wherever you listen.

Apple PodcastsSpotifyYouTube

Learn AI by Testing What Helps

AI marketing is moving from experimentation to ordinary daily work. That changes the question from whether marketers should try AI to where it creates real value, where it needs human review, and where the surrounding hype outruns the evidence.

The useful path is practical. Learn one workflow, test it on real work, measure the result, and keep the human judgment that decides whether the output is accurate, ethical, and worth using.

Make Time for the Work That Saves Time

The source highlights a familiar contradiction: marketers often say they do not have time to learn AI even as they value its ability to reduce repetitive work. Learning a new tool does require an initial investment. The return comes when that learning removes a recurring task or makes a process easier to repeat.

Start with a small, frequent task. Summarize a research document, organize notes, draft a first pass from approved source material, or build a simple checklist. Set aside time to learn and test it rather than waiting for a less busy season. The aim is not to collect tools. It is to develop reliable workflows that compound.

Use AI Video With a Clear Ethical Standard

AI video can help create visual assets that were previously expensive or difficult to produce. The source describes uses such as filling a missing B-roll shot or testing dramatic creative concepts. These possibilities expand what a small team can attempt.

They also require judgment. The source proposes a useful ethical question: if a viewer did not know the asset was generated, would they feel misled? That matters especially when an image could exaggerate what a product does, depict a false endorsement, or create a fake influencer. Use AI to support a message you can stand behind, not to manufacture an impression that falls apart under scrutiny.

Separate Product Announcements From Useful Capability

New agent builders, connected apps, video tools, and AI-enabled software appear constantly. A launch is not proof that a feature belongs in your workflow. The source recommends holding off on a new agent builder because other automation tools were more capable and better integrated at the time of the recording. That is a good evaluation habit: compare the feature against the job you need done today.

For e-commerce and other customer-facing work, connected AI apps may change discovery and shopping behavior. Treat that as a signal to study how customers search and make decisions, while avoiding assumptions that one announcement has already transformed your market.

Ask for Capabilities the Right Way

One of the source’s most practical cautions is that an AI tool may hallucinate about its own features. A system can understand a request such as “write this step by step” without having a real slash-command feature. It may also claim it can perform an action that it cannot actually complete.

Use natural language to describe what you want rather than memorizing invented commands. When you need to know whether a product supports a feature, use its official documentation or ask a search-enabled tool to find current sources. Test the feature with a low-risk example before building a process around it.

AI marketing will reward people who learn quickly, but it will reward discernment more. Stay curious, test real work, verify new capabilities, and let useful results decide which tools earn a place in your workflow.