AI in Marketing

The Situation: The traditional "Marketing Qualified Lead" (MQL) model is failing because B2B buying behavior has fundamentally changed. Modern purchase decisions are made by committees of 6–10 people, not single individuals, and 80% of their research happens in the "Dark Funnel" (podcasts, communities, peer reviews) where traditional tracking cannot see them. Continuing to measure marketing success by individual form-fills creates a misalignment where marketing celebrates "lead volume" while sales struggles with low-quality, unresponsive contacts, ultimately wasting budget and headcount.

The Solution: Forward-thinking organizations are shifting to a Marketing Qualified Account (MQA) model supported by Demand Generation. Instead of gating content to capture emails, they ungate information to educate the entire buying committee, using AI and identity-resolution tools (like 6sense or Koala) to track account-level intent. This approach aligns marketing and sales around a single scoreboard—revenue and pipeline velocity—ensuring that resources are focused on accounts that are actually ready to buy, rather than individuals who simply downloaded a PDF.

Why So Many B2B Teams Are Moving From MQLs To MQAs And Demand Gen
Marketing qualified leads did not suddenly stop working. What changed is the buying behavior around them, and the pressure on marketing to prove revenue, not downloads.

The loud “MQL is dead” line on LinkedIn is mostly theater. Underneath it, something real is happening: companies are quietly rebuilding their funnel around accounts (MQA) and demand creation instead of raw lead volume.

This is what that shift actually looks like, and why it is happening.

What broke with the classic MQL
MQLs were built for a world where you could treat a single contact as “the buyer.” That world has shrunk.

Three things pushed teams away from a pure MQL scoreboard:

Buying committees: Most mid-market and enterprise deals involve a team, not a single person. The intern who downloaded your ebook, the manager who joined a webinar, the VP who skimmed the pricing page. Classic MQL logic elevates one person and ignores the rest of the room.

False positives and junk volume: “Leads” climbed, opportunity quality dropped. SDRs spent their week chasing students, agencies, and partners, because the rule said “downloaded asset + job title = MQL.” Sales blamed marketing. Marketing pointed at the dashboard.

Operational friction with sales: Sales teams sell to accounts. Territories are accounts. Forecasts are built on accounts. A metric that lives at the contact level never quite fits the way sales works in real life.

MQLs did not vanish. They just got demoted from “primary success metric” to “one signal among many.”

What an MQA actually is (and is not)
An MQA (Marketing Qualified Account) is simple in theory: an account that matches your ICP and is behaving like it might buy soon.

Under the hood, that means you stop obsessing over a single contact score and start aggregating signals across a company:

Firmographic fit (industry, size, tech stack)

Buying behavior (intent tools, search patterns, review sites)

Direct engagement (site visits, content, events, product usage)

You still need people inside that account.

You cannot email a logo. Contacts are how you reach the buying group. MQAs just treat those contacts as parts of a shared pattern rather than winners of a scoring contest.

The practical structure many teams settle on is a double funnel:
A volume funnel that still tracks individuals: MQLs, PQLs, free-trial users, webinar attendees.

An account funnel that tracks target accounts: aware, engaged, MQA, opportunity, customer.

The key rule: an account earns MQA status only when enough of those individual signals stack up. For example, several unique visitors from the same company hit product and pricing pages in a short window, while intent data spikes on buying keywords.

Why MQA forces you toward Demand Gen
Once you move your scoreboard to accounts, you run into a data problem. You cannot score an account if the only people you see are the handful who filled out your forms.

That is where demand generation comes in.

Traditional lead gen tries to trap contact data: gated PDFs, forced registrations, “get the slides” forms. You see the one person willing to trade their email, and you miss the rest of the buying group.

Modern demand gen flips the posture:

You remove most gates so more people actually consume your content.

You rely on identity resolution tools to match anonymous traffic to accounts.

You treat social, podcasts, communities, and partner content as part of the funnel, even when tracking is messy.

In that setup, MQA is the scoreboard. Demand gen is the playbook that creates enough broad, low-friction engagement for account-wide patterns to appear.

The Tech Stack: Identity and Deanonymization
If you stop gating content, you need a new way to see who is reading it. The market for "identity resolution" has shifted rapidly in the last 18 months.

The Enterprise Standards: Platforms like 6sense and Demandbase remain the heavyweights. They don't just identify traffic; they offer full-suite advertising and orchestration to target the accounts you discover.

The Modern "Pure-Play" Identifiers: For teams that just want to know "who is on my site" without buying a massive platform, tools like Koala and Snitcher have emerged. They focus on clean UI and product-led growth (PLG) signals.

The "Person-Level" Shift: New tools like RB2B and Warmly are pushing the boundary by attempting to de-anonymize specific people (via LinkedIn profiles) rather than just companies, specifically for US-based traffic.

A Note on Clearbit: A longtime staple of this stack, Clearbit was acquired by HubSpot and is being integrated into HubSpot Breeze Intelligence. For HubSpot users, this means enrichment is becoming a native feature rather than a third-party plugin.

The AI Accelerant: Why this is happening now
For years, MQA was a luxury for enterprises because it required an army of analysts to connect the dots. Artificial Intelligence has democratized this capability.

AI is accelerating the death of the "Contact Request" form in three ways:

Signal Processing: An AI model can ingest thousands of unstructured signals—a G2 review, a pricing page visit, a LinkedIn comment, and a job posting for a new VP—and score the account accuracy far better than a human-built "Lead Score" rule ever could.

The Rise of the "AI SDR": We are seeing the emergence of AI agents (like 11x.ai or Piper) that act as the first line of defense. These agents can engage and nurture the lower-intent volume leads instantly. This removes the fear that "sales will be overwhelmed with junk," allowing human teams to focus exclusively on the high-value MQAs.

Hyper-Personalization: MQA requires outbound. You have to reach out to the buying committee. AI tools can now scrape a prospect's recent podcast appearances and quarterly reports to generate a hyper-personalized outbound sequence for each member of the buying group, making account-based marketing scalable for small teams.

The new scoreboard: from lead counts to revenue signals
Killing the MQL without replacing the scoreboard is how you lose your budget. The teams that made this shift work did not stop measuring. They changed what they celebrated.

Common moves:

Promote “high-intent opportunities” as the hero metric: Instead of “500 MQLs,” the focus becomes “10 demo-quality opportunities from ICP accounts.” The marketing win is not the form fill. It is the meeting that sales accepts and works.

Track pipeline speed, not just pipeline size: When people binge your content, listen to the podcast, and show up already educated, sales cycles usually compress. Measuring “days from first high-intent action to opportunity” tells that story in numbers.

Blend software attribution with self-reported attribution: The form field “How did you hear about us?” looks quaint until you compare it with what analytics says. Software: “Direct.” Prospect: “Your VP on a podcast and three LinkedIn posts.” That gap is the dark funnel in one line.

Shift from CPL to CAC payback: Cheap leads rarely become good customers. Finance cares about CAC and payback period. When marketing reports in those terms, MQA and demand gen stop feeling like a branding hobby and start reading like an investment case.

Who can “kill the MQL” and who should not
There is a hard truth under the romantic “no forms” story: only certain brands can afford to go that far.

Well-known, well-funded companies: Drift, HubSpot, Cognism, and similar firms had strong brand awareness. When they ungated content, people came back on their own. They had direct traffic, communities, and sales coverage to catch that demand.

Most early-stage teams: If your logo is unfamiliar and you ungate everything, people consume, then vanish. You have no permission to remind them you exist. For companies under roughly eight to ten million in revenue, the email list is often the only reliable way to build an audience fast enough.

This is why the real pattern in the market is hybrid, not purity.

A common split:

Ungate “why” content: opinions, narratives, benchmarks, problem framing. The goal is reach and trust.

Keep some “how” content gated: templates, calculators, deep technical material. The goal is to identify people actively working on the problem.

How to make the shift without burning the funnel
If you run marketing and want to move toward MQA and demand gen, the safe path is gradual.

Here is a workable sequence:

Audit your current funnel: Look at a quarter of data. How many MQLs became opportunities? How many were rejected by sales, and why?

Define account qualification rules: Document your ICP. Agree on the signals that matter at account level: firmographic fit, intent patterns, engagement that shows buying work inside the company.

Set a clear MQA threshold: Decide what tips an account into MQA territory (e.g., multiple contacts + intent spike).

Rebuild the dashboard: Keep MQLs for a while, but subordinate them. Put MQAs, accepted opportunities, and pipeline amount on the first screen.

Change the content program slowly: Start by ungating a few pieces that currently produce vanity leads. Watch what happens to high-intent actions from the same audience.

This is less about ideology and more about plumbing. Titles and taglines can wait. The real work is making sure your systems and teams can see accounts, agree on what “good” looks like, and react fast when one starts circling your product.