How have you incorporated AI-powered voice search optimization into your digital marketing strategy? What's one tip you'd share?

Most companies are approaching voice search as a formatting problem — optimizing for conversational queries, FAQs, and long-tail keywords. That's already outdated. Voice is just the interface. The real shift is that AI systems are now making the decision about which businesses to recommend. Whether someone types, speaks, or taps, they're increasingly getting a single synthesized answer. That means the goal is no longer to "rank" for voice queries — it's to be included in the answer itself. This is where our strategy has shifted. We use what I call an agentic content system, anchored by an AI-powered podcast. Instead of creating isolated content pieces, we capture real expertise through structured interviews, then use AI agents to expand that into a distributed network of assets — articles, FAQs, comparisons, and authority signals across multiple platforms that LLMs pull information from. This matters because AI systems don't just crawl your website. They evaluate your presence across the web. So rather than optimizing for voice search directly, we're building a footprint that AI systems can consistently recognize, trust, and recommend. One tip: stop optimizing for how people ask questions, and start optimizing for how AI systems choose answers. If your expertise only lives on your website, you're invisible. AI visibility comes from being distributed, validated, and cited across the broader web.