Should I hire a dedicated GEO specialist or can my SEO team handle this?

We went through this exact decision 6 months ago. Here’s what I learned:

The skills overlap is ~80%:

What’s actually NEW in GEO:

• Understanding how LLMs process content
• Tracking citations instead of just rankings
• Multi-platform visibility strategy
• AI-specific content structuring

Our decision: We upskilled existing team + added tools (Am I Cited for tracking) + gave them 25% dedicated time for GEO.

6-month results:

• AI visibility up 180%
• No additional headcount
• Team developed new skills
• Did need to deprioritize some traditional SEO work

When to hire instead:

• Enterprise scale with complex needs
• Team truly at maximum capacity
• Aggressive timeline with board pressure
• Budget isn’t the constraint

Speaking as the SEO person who got “upskilled” for GEO:

What I needed to learn (took ~2 months):

1. How AI systems retrieve and cite content
2. How to use citation tracking tools (Am I Cited)
3. Content structuring for AI extraction
4. Multi-platform visibility analysis

What I DIDN’T need to learn:

1. Basic content optimization (already knew)
2. Technical SEO (already knew)
3. Competitive analysis (already knew)
4. Keyword/topic research (already knew)

What actually helped me learn:

• Tool access (Am I Cited was eye-opening)
• Permission to experiment (20% time allocation)
• Documentation and resources (shared learning)
• Clear success metrics

What would have KILLED the initiative:

• Adding GEO to my plate with no capacity
• No tools for tracking
• Unclear ownership
• No executive support

My advice to CMOs: Your SEO team CAN do this. But they need:

1. Time allocation (real, protected time)
2. Tool investment
3. Clear ownership
4. Permission to deprioritize something else

If you can’t give those things, hire instead.

Before you decide hire vs. upskill, audit what’s ACTUALLY missing:

The common misconception: “We don’t have GEO capability.”

The reality: “We don’t have GEO INFRASTRUCTURE.”

What infrastructure means:

My assessment of most teams:

• Skills: 7/10 (they have enough)
• Infrastructure: 2/10 (this is what’s missing)

What happens when you hire without infrastructure: New person is equally lost. No visibility data. No clear process. No way to show impact. They leave in 6-12 months.

My recommendation:

1. Build infrastructure first (tools, processes, ownership)
2. Give existing team 60 days to show progress
3. Then decide if you need specialist hire

Infrastructure first, people second.

Let me do the actual budget math:

Option A: Hire GEO Specialist

• Salary: $120-150K
• Benefits: ~30% = $36-45K
• Recruiting: ~20% = $24-30K
• Onboarding: 3 months to productivity
• Total Year 1 cost: $180-225K
• Ongoing: $156-195K/year

Option B: Upskill + Tools

• Tools (Am I Cited, etc.): $12-24K/year
• Training/resources: $5-10K
• Reallocation of 25% of existing time: $30-40K (opportunity cost)
• Total Year 1 cost: $47-74K
• Ongoing: $42-64K/year

Option C: Hybrid - Part-time consultant + tools

• Consultant (10 hrs/month): $24-36K/year
• Tools: $12-24K/year
• Team time allocation: $30-40K
• Total: $66-100K/year

ROI consideration: At $50M revenue, even a 2% improvement in qualified pipeline = $1M. All three options can achieve that if executed well.

My take: Option B (upskill) or C (hybrid) for most mid-market companies. Option A (hire) only for enterprise or when team is genuinely at capacity.

Don’t hire for prestige. Hire for capacity.

As someone who consults on this, here’s when clients should/shouldn’t hire:

Hire a GEO specialist when:

• Multiple product lines with different AI visibility needs
• Complex technical environment requiring dedicated attention
• Team is at 100%+ capacity on existing work
• Budget is available and speed matters
• You need someone who can own this end-to-end

DON’T hire when:

• You’re not clear on what GEO success looks like
• You don’t have visibility tracking in place
• Your team has capacity but lacks direction
• Budget is tight and you need results fast
• You’re hoping the hire will “figure it out”

The failed hire pattern I see:

1. Company hires “GEO specialist”
2. No clear metrics, no tools, no process
3. Specialist struggles to show impact
4. Leaves within a year
5. Company concludes “GEO doesn’t work for us”

The successful pattern:

1. Company sets up infrastructure (tools, process, metrics)
2. Existing team shows initial progress
3. Capacity becomes the constraint
4. Specialist hire adds capacity to working system
5. Compound improvement

Hire to scale what works, not to figure out what works.

Reality check for small teams like yours:

You have 2 SEO people. Here’s what I’d actually do:

Week 1-2:

• Sign up for Am I Cited (or similar)
• Baseline your current AI visibility
• Identify top 5 priority topics

Week 3-4:

• Allocate 4 hours/week per person for GEO
• Start with quick wins (restructure top pages)
• Track changes weekly

Month 2-3:

• Evaluate what’s working
• Document the process
• Calculate capacity reality

Then decide: If you’re seeing progress and capacity is fine → Continue If progress is good but capacity is strained → Consider hire If progress is poor → Diagnose why (probably infrastructure, not skill)

The 4 hours/week reality: 4 hours/week = 208 hours/year = ~5 weeks of full-time work

That’s enough to make meaningful progress on GEO without major disruption. If you can’t find 4 hours/week, you have a prioritization problem, not a headcount problem.

Here’s how to assess if your team can upskill:

Questions for your SEO team:

1. “Can you explain how ChatGPT decides what to cite?”

   • Good answer: Demonstrates LLM understanding
   • Learning opportunity if not

2. “How would you track our visibility in AI answers?”

   • Good answer: Mentions tools, methodologies
   • Critical gap if blank

3. “How would you optimize a page for AI citation vs. Google ranking?”

   • Good answer: Knows the differences
   • Trainable if they can articulate Google approach

4. “What would you deprioritize to focus on GEO?”

   • Good answer: Has realistic tradeoff thinking
   • Red flag if “nothing, I’ll just add it”

Assessment outcome:

• 4 good answers: Upskill with confidence
• 2-3 good answers: Upskill with support
• 0-1 good answers: Consider hire or heavy training

Most SEO professionals I meet can answer 2-3 well. That’s enough to start.

This thread was exactly what I needed. Here’s my board presentation outline:

Recommendation: Phased upskill approach

Why not immediate hire:

• Talent pool is limited (4-month search likely)
• Team has transferable skills (80% overlap)
• Infrastructure is the bigger gap
• Lower risk, faster start

Phase 1 (Weeks 1-4): Foundation

• Deploy Am I Cited for tracking
• Baseline current AI visibility
• Identify quick win opportunities
• Investment: $15K (tools + training)

Phase 2 (Months 2-3): Execution

• Allocate 8 hours/week team time
• Deprioritize: [specific lower-impact SEO tasks]
• Execute on top 10 priority pages
• Weekly visibility tracking

Phase 3 (Month 4): Decision Point

• Evaluate progress vs. targets
• Assess capacity constraints
• Make hire/no-hire decision with data
• Budget reserved for hire if needed: $150K

Success metrics:

• AI citation rate improvement
• Visibility score across platforms
• Competitive share of voice

What the board will like:

• Not ignoring AI (we have a plan)
• Responsible investment (phased approach)
• Clear decision points (data-driven)
• Flexibility (hire option preserved)

Thanks everyone. This is a much better plan than my original “should I hire?” framing.