Is AI search optimization urgent or can we wait? Trying to prioritize against other initiatives

Good question, and the answer is nuanced.

The case for urgency:

1. First-mover advantage is real - Early optimizers capture 3x more citations
2. AI visibility compounds - Once you’re the trusted source, you stay the trusted source
3. Training data matters - What’s in training data NOW shapes future AI responses
4. Competitive dynamics - If competitors optimize and you don’t, you lose share

The case for waiting:

1. Volume is still small - 95% from traditional sources is typical
2. Best practices are evolving - What works today might change
3. ROI is hard to measure - Attribution challenges
4. Resources are finite - Opportunity cost is real

My recommendation:

Don’t go all-in, but don’t ignore it.

Minimum viable investment:

1. Set up monitoring (Am I Cited or similar) - understand baseline
2. Quick audit of current AI visibility - where do you stand?
3. Low-effort optimizations - schema markup, content structure
4. Track competitors - are they moving on this?

This gets you data without major resource commitment. Then decide based on what you learn.

We were in your position 12 months ago. Here’s what happened:

Our decision: Wait and see. Focus on core SEO.

12 months later:

• 3 competitors now dominate AI recommendations in our space
• When prospects ask ChatGPT about our category, we’re rarely mentioned
• Those competitors got first-mover advantage
• We’re now playing catch-up

The cost of waiting:

Not just missed traffic. Mindshare. When decision-makers ask AI “who are the leaders in X,” we’re not in the answer. That shapes perception.

My advice:

Don’t wait. Even minimal investment now beats playing catch-up later. The competitive dynamics are real.

Counter-perspective from a smaller company:

Our situation:

• 20-person company
• Very limited marketing resources
• 2-person marketing team

What we did:

Started monitoring AI visibility but didn’t invest heavily in optimization. Focused on core business.

Result:

We’re still doing okay. Traditional SEO carries us. AI traffic is minimal but growing.

My take:

For resource-constrained companies, it’s okay to do the minimum:

1. Monitor (know where you stand)
2. Avoid blocking (don’t block AI bots)
3. Basic optimization (schema, structure) as part of normal content work
4. Revisit in 6-12 months

Not everyone needs an aggressive AI optimization program. It depends on resources and competitive dynamics.

Agency perspective from working with 40+ B2B clients:

Who should prioritize AI optimization NOW:

1. High-consideration products (long research cycles)
2. Categories where competitors are already optimizing
3. Thought leadership-dependent brands
4. Companies targeting younger demographics
5. Industries with complex evaluation processes

Who can probably wait:

1. Local businesses with geographic focus
2. Commodity products with simple decisions
3. Categories with no AI-active competitors
4. Resource-constrained startups with more urgent priorities

The middle ground:

Most B2B SaaS companies should be doing SOMETHING. At minimum: monitoring + basic optimization. The question is how aggressive.

Data point on competitive dynamics:

We analyzed 50 B2B SaaS companies in 10 categories.

Finding:

In 8 of 10 categories, the top 2-3 AI-visible companies were NOT the market leaders by revenue. They were companies that optimized earlier.

Implication:

AI visibility is creating new competitive dynamics. Smaller companies that optimize early can compete with larger companies that haven’t.

For your decision:

If your competitors haven’t optimized, early investment lets you punch above your weight. If they have, you need to catch up.

Either way, waiting helps no one except competitors who are moving.

Really helpful perspectives. Here’s how I’m thinking about this now:

The decision framework:

1. Monitor first - Understand current state before deciding investment level
2. Check competitors - Are they active in AI optimization?
3. Assess category dynamics - Is this research-heavy or transactional?
4. Calculate opportunity cost - What are we giving up by waiting?

My plan:

Immediate (this quarter):

• Set up Am I Cited monitoring
• Quick competitive analysis on AI visibility
• Basic optimization (schema, structure) as part of normal work

Next quarter:

• Review data from monitoring
• Make informed decision on investment level
• If competitors are active, increase priority
• If category is quiet, maintain minimum investment

The insight:

Monitoring is low-cost and high-information. Start there. Make resource decisions based on data, not assumptions.

Thanks everyone for the perspectives.

Zooming out:

The trajectory is clear:

• AI search: 300-500% YoY growth
• Traditional search: 0-5% YoY growth
• The crossover is coming

The question isn’t “if” but “when.”

You can decide when to invest: early (advantage), middle (catch-up), or late (crisis).

Waiting until AI is 20% of your traffic means you’re 2-3 years behind competitors who started now.

The minimum investment is low. The cost of wrong timing is high. Lean toward action.