Insights that drive growth.

If you already have an SEO agency, choosing an AI SEO agency comes down to whether your incumbent's process has actually changed for AI search. This guide covers when to extend your current agency versus adding a specialist, a vendor checklist, eight questions to ask, red flags, and 2026 pricing by delivery model.

To choose an AI search optimization agency, use a checklist that verifies real AI citation tracking, off-site authority building, and pipeline measurement. Ask eight specific questions on every sales call, treat guaranteed placements and anonymous case studies as dealbreakers, and consider a strategy-only partner if your team already has execution capacity or your buyers aren't using AI search yet.

Hire a GEO agency when AI answers already shape which vendors your buyers consider, competitors appear in those answers more often than you, and your team cannot close the gap in the next quarter or two. This guide covers the signs to check in your own data, when waiting is smarter, and what the first 90 days with an agency look like.

Hire an AEO agency if AI search already shapes how your buyers research and your team lacks the time or skills to act on it. Build in-house if you have strong SEO, content, and analytics skills plus budget to experiment, use a tool if you mainly need visibility data, and hold off if the basics are not in place yet.

AI search optimization for B2B companies typically runs $3,000 to $5,000 per month for an entry retainer, $5,000 to $12,000 per month for mid-market programs, and $12,000+ per month for enterprise scope, with one-time launch projects from $5,000 to $20,000. Product lines, content maturity, and technical work decide where you land.

In 2026, generative engine optimization typically costs roughly $10 to $1,000 per month for DIY tools and software, and roughly $1,500 to $50,000+ per month for agency and managed services. Your category, your content maturity, and how you measure results decide where you sit.

Prioritize an integrated visibility system that aligns technical SEO, answer-focused content, and entity building to influence buyers across search and AI-driven discovery. You’ll learn clear distinctions between SEO, AEO, and GEO, practical first steps for audits and content structure, and measurement tactics that combine independent signals to prove influence when clicks no longer tell the whole story.

Optimizing content for AI Overviews requires reshaping pages so they answer fan-out sub-questions directly, are crawlable, and include verifiable first-party evidence that earns citations. Follow a repeatable sequence: research tied to ICP, reverse-engineer the live Overview, structure self-contained sections, add data and visuals, then measure impressions, citation share, and assisted conversions to track progress.

Treat LinkedIn thought leadership as a repeatable system rather than a collection of tactics: optimize your profile as the landing page, anchor two to three content pillars in buyer pain, and sustain a cadence you can hold on your worst week. Amplify posts that earned real engagement with thought-leader ads and measure qualified profile visits, DMs, and inquiries as leading signals of pipeline.