Is Your Marketing Team's AI Work Hidden From the P&L?

AI adoption can turn marketers into unpaid (ineffective) software teams, while the real work absorbs the opportunity cost. HubSpot reports 91% of marketing leaders say their teams use AI, and 66% say their company builds its own internal AI tools for marketing. Many of those projects don't appear in your team's marketing plan or project management tool.

What Happened

Kevin Indig published a Search Engine Land analysis on September 9, 2026 arguing that marketing teams are absorbing an unaccounted category of work: building, prompting, checking, and maintaining internal AI tools. He cites a METR study of 16 experienced developers on 246 tasks where AI made them 19% slower even though they believed they were 20% faster. Indig calls this the AI productivity paradox and warns organic search work is paying the bill.

Why This Matters for B2B Marketing Leaders in HR Tech and FinTech

Your SEO and growth teams are the earliest AI adopters on your marketing org, and they are also the ones responsible for earning mentions inside the LLMs your buyers now consult. If 66% of companies are building homebrew AI tools and none of that maintenance shows up in your project tracker, you have a hidden line item competing with the exact answer engine optimization work that determines whether ChatGPT and Perplexity recommend your platform to a VP of HR or a fractional CFO. The category is crowded, differentiation is language-based, and the lead time on organic AI visibility is long. Every hour your team spends babysitting a custom GPT is an hour not spent producing the source material that trains the models.

The Starr Conspiracy's Take

Indig is naming something you already feel. The productivity gains from marketing AI are real in narrow tasks and illusory at the portfolio level, because the work moved rather than disappeared. For HR Tech and FinTech marketers, the strategic error is treating internal tool-building as free R&D when it is actually a tax on your answer engine optimization program. We tell clients to audit AI hours the same way you audit media spend: which prompts, workflows, and custom builds are producing citable output, and which are hobby projects your senior strategists can't stop tinkering with? Kill the hobbies. Redirect the hours to earning mentions.

What to Watch Next

Expect a wave of 2027 planning conversations where CMOs ask for the ROI on last year's AI tool sprawl and can't produce it. The likely response is consolidation onto fewer platforms and a renewed budget line for organic AI visibility work that only humans plus disciplined systems can produce.

Related Questions

How do you measure hidden AI work on a marketing team?

Track it like any other production line. Add AI tool-building, prompt engineering, and workflow maintenance as project categories in your PM system, then review weekly hours against output. If a custom workflow consumes more senior time than it saves junior time, retire it.

What is the opportunity cost of homebrew AI tools for organic visibility?

Organic AI visibility compounds slowly and requires consistent published expertise. Hours diverted to internal tooling delay the citations, mentions, and structured content that get you surfaced in LLM answers. Learn how AEO differs from traditional SEO and why the lead time is unforgiving.

Should HR Tech and FinTech marketers build or buy AI tools?

Buy when the workflow is common across your category and a partner already serves it. Build only when the workflow encodes proprietary judgment your competitors cannot replicate. Most marketing AI tools fall into the first bucket, which means buying preserves your team for the strategic work.