Your GTM spend isn’t just an expense — it’s an asset

For as long as most of us can remember, go-to-market (GTM) operations — especially marketing and sales — have been treated almost entirely as operating expenses. The logic was simple: GTM costs are short-term, their benefits too uncertain and their ties to financial outcomes too tenuous to justify anything but immediate expensing. But that logic is falling apart.

As causal AI enables us to quantify the time-lagged, material impact of GTM investments on future business outcomes, we are standing at the threshold of a radical shift in how we account for, govern and invest in GTM. A brand investment that moves pricing power for four years isn’t an expense — it’s an asset.

The hidden accounting insight

Let’s start with one overlooked but transformative insight: Time lag is the accounting backbone of capitalization and amortization.

If an investment’s benefit unfolds over time and can be reliably measured, then by GAAP standards, it qualifies for capital treatment. For decades, marketing and sales have failed this test. Not because they didn’t generate long-term value, but because we couldn’t prove it. Now we can.

Causality changes the game

Causal AI — especially when paired with time-series modeling and directed acyclic graphs (DAGs) — lets us isolate which GTM actions drive which financial outcomes, with what delay and how material that influence is over time.

This creates a traceable, audit-grade basis for treating certain GTM activities not as throwaway spend, but as durable, depreciable assets. This is not theoretical. It’s operational and already influences how CFOs, boards and auditors interpret GTM line items.

Dig deeper: Why causal AI works when other forecasting models fail

Reclassifying GTM spend: What might shift from OpEx to CapEx

Here’s how this model plays out across GTM subfunctions in both B2C and B2B contexts:

✅ = Strong case for causal-driven capitalization.
⚪ = Case depends on evidence quality and time horizon.

Time lag in action: B2B vs. B2C

B2B: LinkedIn’s ABM strategy

In 2019, LinkedIn launched a multi-year account-based marketing (ABM) program targeting senior HR, sales and marketing decision-makers. Key GTM assets included:

• CMO-level thought leadership content.
• Industry whitepapers and webinars.
• Targeted sales tools.
• Long-cycle lead nurturing via ABM tech stack.

Causal chain: Minimal impact in Year 1, but by Year 3, the initiative delivered:

• 42% increase in enterprise LTV.
• 26% lift in upsell velocity.

Time lag: 12–18 months to influence buying center behavior; total impact over 3–4 years.

Capitalization rationale: Reusable content, sales assets and playbooks justify partial CapEx treatment, similar to internal-use software.

B2C: Nike’s ‘You Can’t Stop Us’ campaign

In 2020, Nike launched an emotion-driven, global campaign highlighting resilience and unity.

• A 90-second montage with no product pitch.
• Cross-platform digital and TV distribution.

Causal chain:

• 50M+ views in the first week.
• 25% spike in engagement.
• 11% digital sales growth.
• Favorability lift in key markets.

Time lag: Effects peaked within 1–2 months; minimal carryover after 6 months.

Capitalization rationale: Despite high ROI, the steep decay curve means this remains a short-lived operating expense.

Comparison snapshot

What GTM leaders are not asking (but must)

To shift from spend to stewardship, GTM leaders need to start asking:

• What qualifies as a “reliable and objective” causal model under GAAP? It must be auditable, traceable to systems of record and statistically valid.
• Where do we draw the line between asset and performance spend? Not every campaign qualifies. Segment short-term tests from long-horizon infrastructure.
• How do we define useful life for GTM assets? Build decay curves. A 3-month campaign and a 3-year enablement program are not the same.
• Can this matter before GAAP changes? Yes. Use internal dashboards, board reports and capital allocation committees. Influence precedes codification.

Why finance will push back — and how to win the argument

It’s natural for finance to question any shift in accounting treatment. The key is to speak their language — aligning GTM strategy with financial rigor and auditability.

Fiduciary duty and GTM’s hidden value

The 2023 Delaware fiduciary ruling redefined oversight: Boards and executives must now govern how value is created — not just whether a cost was approved.

Meanwhile, intangibles account for over 90% of enterprise value, yet are barely visible on most balance sheets. Causal AI offers a bridge:

• Provides audit-grade visibility into GTM’s role in value creation.
• Supports selective reclassification of spend.
• Enables fair-value disclosures in M&A, impairment and investor reporting.

Dig deeper: AI is transforming GTM teams into fiduciary powerhouses

Toward monetization and internal hedging: The next evolution

Causal modeling doesn’t just tell us what worked — it quantifies how much it worked, when and under what conditions. That opens two transformational frontiers:

1. Financial monetization of GTM assets

Just as companies monetize IP portfolios, GTM investments validated by causal models may soon qualify for:

• Securitization: Bundling high-confidence GTM programs into revenue-linked assets.
• Insurability: Where causal fidelity is high, parts of GTM spend may be underwritten for performance risk.
• Loan facilities: Borrowing against the calculated NPV or forecasted LTV of long-cycle GTM initiatives.  This is what CAC/LTV pretends to be, but it’s not generally understood that CAC is a debt incurred against future revenue and most LTV is pure guesstimate.
• Tax treatments: Drawing parallels to R&D credits, government bodies may one day recognize validated GTM investments as capital expenditures with depreciation or credit value.

2. Internal hedging against GTM failure

CFOs can now convert causal outputs into actuarial-grade logic, enabling internal hedging strategies that would have been impossible under correlation-based models. Causality turns GTM planning from blind faith into hedgeable foresight.

For example, a SaaS company launches a 3-year ABM program projected to generate $36 million in revenue, but causal models reveal a 25% downside risk. The CFO allocates a $3 million internal reserve — not in cash, but as a contingency buffer within GTM planning. Triggered by causal variance (e.g., declining content engagement, macro headwinds or sales misalignment), this reserve can be:

• Redirected to higher-performing cohorts.
• Reallocated to short-cycle demand programs.
• Or used to buffer timing volatility without alarming the board.

This is not financial engineering. It’s strategic foresight rooted in causal clarity, giving Finance the tools to mitigate GTM risk with the same precision applied to credit, supply chain or operations.

Causal modeling makes it possible to build GTM reserves, trigger capital reallocation early and defend investment quality at the board level — before failure becomes visible in revenue.

Dig deeper: A 3-step guide to unlocking marketing ROI with causal AI

Rethinking the GTM ledger

We’re not claiming that all GTM spend becomes CapEx. Campaigns, tests and one-off activations remain OpEx. But the default assumption that GTM = pure expense is no longer tenable.

CFOs must now ask:

• What portion of our spend is building multi-year value?
• What are we underreporting on the balance sheet?

And GTM leaders must be fluent in:

• Amortization curves.
• Net present value (NPV).
• Decay-adjusted contribution.

Because in a world where trust, loyalty and strategic influence drive growth — your GTM engine may be the company’s most valuable asset.

Causal AI gives us clarity we’ve never had before. The only question is whether GTM, Finance and the Board are ready to act on it.

It’s time to move from spend to stewardship — and to account for GTM not just as an expense, but as the strategic capital asset it truly is.