December 8, 2025
by Kamaljeet Kalsi / December 8, 2025
AI search isn’t just an evolution of Google — it’s a revolution in buyer behavior.
For years, the B2B go-to-market (GTM) playbook was a predictable game of casting a wide net, capturing marketing-qualified leads (MQLs), and hoping enough of them converted to justify the spend. The MQL was the north star for marketing success.
But today’s buyer has already made up their mind before they ever talk to a salesperson, and AI is the primary enabler of this seismic shift.
According to Semrush, over half of all searches now result in zero clicks, and AI is set to overtake traditional search traffic by 2028. We’ve moved from an era of passive discovery to one of active curation, where buyers use chatbots and generative search to self-diagnose, vet vendors, and even draft request for proposals (RFPs). The old funnel, powered by generic content and form fills, has expired.
So how are savvy sales and marketing leaders adapting?
We teamed up with experts from Apollo.io, 6sense, Seamless.AI, HubSpot, Lusha, Customer.io, Qualified, Goldcast, Twilio, Zappi, and more to dissect this transformation. Their insights reveal a new revenue playbook built on precision, partnership, and fierce focus on signals that matter.
AI search doesn’t just drive traffic — it drives higher-converting traffic.
Adam Kaiser of 6sense noted that LLM-driven search activity already outperforms legacy organic search when it comes to downstream conversion. Buyers aren’t browsing casually; they’re arriving with context, curated shortlists, and pre-formed preferences.
“Good marketing, good PR, getting the word out, building your brand so you’re showing up in other places is also a big part of it.”
Adam Kaiser
Vice President, Brand and Growth Marketing, 6sense
This shift has elevated the importance of brand visibility beyond owned channels. Kelly Cheng, CMO at Goldcast, calls it “mindshare marketing” — showing up consistently in the buyer’s world before intent spikes appear.
“Our approach centers on 'mindshare marketing', the idea that you have to show up before the signals do.”
Kelly Cheng
Chief Marketing Officer, Goldcast
John Schoenstien, Chief Revenue Officer at Customer.io, noted that today’s buyer is far more self-directed and expects a personalized experience long before talking to sales. In response, Customer.io has completely rebuilt its pipeline engine around AI — shifting from volume tactics to intelligent, signal-driven engagement across the entire funnel.
His team now uses AI to identify high-fit accounts, anticipate buying signals, enrich inbound leads in real time, and automate manual sales tasks so reps can focus on higher-value conversations that actually move deals forward.
“Today’s buyer is more self-directed and better informed, so we’ve shifted from brute-force tactics to an AI-powered pipeline that is faster, smarter, and more scalable. Our pipeline generation is now powered by real-time intelligence rather than legacy MQL-driven processes.”
John Schoenstien
Chief Revenue Officer, Customer.io
The takeaway: pipeline generation is no longer about spraying content. It’s about becoming a brand that buyers already trust when they start their journey with AI search.
The MQL, once the lifeblood of B2B marketing, is now a lagging indicator at best. So what signals should revenue leaders be looking at now?
While buying has always been a group sport, AI has amplified the need to think in terms of accounts, not individuals.
“In the old world of MQLs, just because you have one contact who submits a lead doesn’t mean the actual account is ‘sales ready’.”
Michael Pannone
Head of Global Demand Generation, G2
Today, teams prioritize motion over form fills — intent spikes, job changes, funding announcements, and tech shifts.
“The strongest signals now live outside our owned channels. Gated content is irrelevant when buyers are already deep in decision mode.”
Yoni Tserruya
Chief Executive Officer and Co-founder, Lusha
Tserruya reinforced this by stressing that static lists are obsolete. Yoni emphasized that static lists die, and that sales streaming keeps the pipeline alive by curating new signals and context every day.
Bruno Basic of DualEntry highlighted that hardship signals are often the most reliable: layoffs, abrupt stack changes, or job posts suggesting operational struggles.
“We’re no longer chasing traffic volume — we’re focused on being the best answer to the right question, for the right buyer.”
Bruno Basic
Go-to-market Leader, DualEntry
Liz Yoselowitz of Brainlabs explained that MQLs were built for a world where companies could bid on high-intent keywords and drive people straight to conversion pages.
Today, discovery happens in AI chat threads, LinkedIn conversations, and Reddit discussions. The old funnel assumed buyers came to you first; now they research you everywhere else before deciding whether you’re worth visiting.
“If people can't find you on their preferred platforms, they can't purchase from you. The truth is, attribution is getting more difficult. Any marketer's guiding light should be revenue, but you need to track leading indicators like visibility across all platforms - not just form fills.”
Liz Yoselowitz
Chief Marketing Officer, Brainlabs
As these signals evolve, CFOs and CIOs are emerging as power players in software purchases. Their fingerprints now show up in the signals that matter — procurement scrutiny, integration risk flags, security reviews, and budget tightening.
Even when an account shows strong intent, deals stall if these roles aren’t aligned. Revenue teams need to read and prioritize these operational signals early, not treat them as late-stage surprises.
And as these operational signals grow more complex, the question becomes: What’s the best strategy to capture and convert leads? Should we let AI take the reins or let our human reps lead the fore?
AI SDRs have carved out a clear role: scale. They excel at high-volume, low annual contract value (ACV) transactions, broad outbound, and re-engaging dormant accounts.
“AI SDRs are good for broad outreach, broad inbound, mid-market, and SMB with speed and coverage. But for higher ACV enterprises, it’s going to be very difficult to replace the human in the loop.”
Jonathan Pogact
Vice President of Marketing, Seamless.AI
Human reps remain non-negotiable for high-value enterprise deals.
“AI excels at qualifying, nurturing, and converting to a meeting, but human sales reps take it from there.”
Kieran Snaith
Senior Vice President of Revenue Operations, Qualified
Snaith emphasized that enterprise buyers want nuanced conversations, particularly around pricing and multi-stakeholder decisions.
The implication: AI can warm the pipeline, but people still close it.
Samuel Thomas Elliot of Apollo.io calls experimentation the differentiator.
“Teams that invest now in testing, building, and learning from their own 'AI SDR’-like workflows, using their own data and context, will be the ones who win when the tech matures.”
Samuel Thomas Elliott
Prompt Writer & Engineer - AI Platform, Apollo.io
If AI and human reps now play distinct roles, the intelligence guiding those handoffs has to evolve too.
Even with sophisticated tools and AI SDRs, sales is still human at its core. Signals don’t replace relationships. Buyers still want to feel seen and understood.
Nataly Kelly, Chief Marketing Officer at Zappi, cautioned against losing touch with the basics:
“Teams have gotten so used to hiding behind a monitor or looking at signals that they forget what matters most: building relationships and caring about prospects as human beings.”
Nataly Kelly
Chief Marketing Officer at Zappi
The message is clear: AI may open the door, but only a genuine human connection closes the deal.
Sales intelligence has shifted from dashboards to execution engines. Instead of passively collecting signals, teams are operationalizing them by feeding insights directly into workflows that trigger outreach, campaign adjustments, and sales plays.
This is less about watching the market and more about acting at the exact moment motion signals show readiness. Tools that push signals into sequences, enrich contacts, and trigger plays are winning more praise than those that simply add another dashboard to stare at.
As sales intelligence becomes more actionable, revenue teams need a unified system to execute on those signals.
Despite progress, many teams still treat account-based marketing (ABM) as a tactic instead of a holistic revenue system.
“The real power of ABM is a full-funnel conversation. You can’t have sales and marketing working in black boxes; the buyer can feel that disconnect.”
Shaun Hinklein
Head of SEO, Apollo.io
Angela DeFranco of HubSpot doesn’t mince words:
“The old playbook isn’t just broken, it’s expired.”
Angela DeFranco
VP & GM of Product - Marketing Hub, HubSpot
What Angela’s pointing to is the collapse of the traditional, linear funnel. AI search is now capturing intent upstream, reshaping how buyers gather information, and diminishing the old reliance on gated content and manual qualification.
Marketers no longer “generate” pipeline in isolation since AI is doing the sorting, ranking, and routing long before a form fill ever appears. That shift demands a new operating model where ABM isn’t a campaign layer but the connective tissue that aligns ICP definition, signal interpretation, personalized plays, and revenue execution across teams.
The lines are blurring as marketers move beyond lead gen to own SQLs, revenue, and even SDR responsibilities.
True ABM integrates ideal customer profile (ICP) definition, signals, plays, handoffs, and measurement into one continuous loop. Campaigns end; operating systems scale.
G2 review data for the Sales Intelligence category reveals that buyers crave execution over dashboards, trust over noise, and motion over MQLs.
AI is scaling the simple stuff, humans are winning the complex plays, and brand credibility is quietly becoming the new pipeline currency.
Across 500 reviews (August 19–September 24, 2025), the average star rating is 4.57/5, and “likely to recommend” averages 9.13/10 (NPS ≈ +73). Buyers mention execution terms (workflow, sequence, enrich, trigger, automation) in 126 reviews, compared with just 18 mentions of dashboards. The message: execution > reporting.
Teams prize automation and velocity, but get stuck on data quality and metering.
Users’ likes: AI (680 mentions), UI (299), email (256), lead lists (200), search (157), integrations (HubSpot 28, Salesforce 18).
Users’ dislikes: credits/limits (37), pricing (24), phone data (25), accuracy (17), bounces (22), export friction (18).
Signals like funding, job changes, and stack shifts appear in ~10% of reviews. These reviews average slightly lower ratings (4.39/5, LTR 8.78) than the dataset overall, suggesting that buyers want greater precision and reliability when using motion to prioritize accounts.
196 reviews mention trust, reliability, accuracy, or verification, with slightly higher averages (4.59/5, LTR 9.17). Translation: Credibility makes signals usable, and trusted brands turn signals into pipeline.
Execution keywords dominate review data (126 mentions) compared with “dashboard” (18). Buyers reward tools that operationalize signals into outreach, sequences, and cadences, not just visualize them.
AI scales SMB, while humans handle enterprise.
Reviews tying AI/automation to verbs like qualify, nurture, or reactivate (17 reviews) are highly positive (4.62/5, LTR 9.24). Reviews that reference enterprise, pricing, or human reps are more common (82 reviews) but lower rated (4.22/5, LTR 8.44).
While ABM mentions are sparse in G2 reviews for sales intelligence software, HubSpot appears frequently with strong sentiment (4.61/5, LTR 9.22). This suggests CRM-anchored workflows underpin ABM success, while “ABM as campaign” has little resonance. Notably, 6sense is not mentioned in this dataset.
Tip: Leaders must also balance speed with responsibility. Signal-led outreach pushes into sensitive data and compliance territory, making legal guardrails a non-negotiable part of the playbook.
In an AI-first world where MQLs no longer reflect real buying intent, this stability is its own signal. Consistently high satisfaction at scale shows which sales tech platforms are actually powering the new, signal-led pipeline.
Category leaders like Apollo.io, Wiza, and Cognism show consistently strong satisfaction, while smaller players post perfect scores that lack the volume to be definitive.
These are the ones helping revenue teams move beyond form fills and toward real buyer motion.
Here’s a leaderboard by review count:
Honorable mentions of leading smaller players:
The old model of handoffs between sales and marketing is crumbling. Today, campaigns are built as joint ventures where brand, demand gen, and sales align around one narrative.
“There's no organization where marketing can win if sales isn't winning.”
Jonathan Pogact
Vice President of Marketing, Seamless.AI
Adam Kaiser reinforced that brand credibility has become indispensable in an AI-first world. If your brand isn’t trusted, AI search won’t surface you. That makes PR, customer advocacy, and third-party validation central to revenue strategy, not just marketing vanity projects.
The AI-augmented buyer requires an AI-augmented revenue team. The winners won’t be those who chase leads; they’ll be the ones who attract buyers already in motion, build credibility in AI search, and align brand, marketing, and sales into one revenue engine.
“The biggest mistake is assuming personalization means customization at the individual level, when buyers actually want control over their experience.”
Sidharth Ramsinghaney
Director of Strategy and Operations, Twilio
The old funnel is dead. The future of pipeline belongs to those who embrace intelligence over inertia; less about volume, more about relevance.
If you want more precision behind every prospect in 2026, save your spot for the G2 quarterly innovation event on Dec. 16. Learn how leading teams turn G2 signals and AI-driven visibility into real pipeline.
MQLs are lagging indicators. By the time a buyer fills out a form, they’re often already deep into their decision journey. AI search and generative chatbots are enabling them to self-diagnose, shortlist vendors, and even draft RFPs without touching your owned channels.
G2 insight:
In G2 reviews, mentions of “MQL” or “leads” are rare compared to “intent,” “signals,” and “execution.” Buyers reward tools that operationalize motion signals (like funding rounds or job changes) into workflows rather than just capturing form fills.
Next step:
Revenue teams can shift from chasing MQLs to leveraging G2 Buyer Intent data to see when accounts are actively comparing vendors or researching categories. This allows you to prioritize in-motion accounts instead of waiting for a form fill.
AI search isn’t just driving traffic — it’s sending you better-prepared buyers. They show up with curated shortlists and pre-formed preferences, making trust and brand credibility more important than top-of-funnel volume.
G2 insight:
Across 500 recent reviews, buyers mention execution (126) far more often than dashboards (18). They value tools that help them act at the moment of readiness, not passive analytics.
Next step:
CMOs can optimize their G2 profile to ensure their brand shows up credibly in AI search. Verified reviews, strong category positioning, and visible integrations (e.g., Salesforce, HubSpot) increase trust with in-motion buyers.
A zero-click search happens when a user gets the answer they need directly on a search results page or inside an AI chatbot such as ChatGPT, Gemini, or Perplexity. The user does not click through to a website because the information is already presented to them.
High-value signals now include account-level intent: funding announcements, job changes, layoffs, tech stack shifts, and content consumption across third-party platforms. These signals reflect the real motion inside accounts.
G2 insight:
Mentions of motion signals in reviews (≈10%) were tied to slightly lower satisfaction scores (4.39/5 vs. 4.57/5 overall), which suggests buyers want greater reliability and precision in using these signals.
Next step:
Sales and demand gen teams can integrate G2 Buyer Intent alerts into their workflows to know exactly when target accounts are researching their category or competitors — making outreach both timely and relevant.
AI SDRs excel at high-volume, SMB, and mid-market outreach where scale matters. But enterprise deals still demand human nuance — navigating pricing, compliance, and multi-stakeholder buying committees.
G2 insight:
Reviews show that AI-driven workflows for qualifying/nurturing are highly rated (4.62/5), but enterprise-specific reviews trend lower (4.22/5). This confirms that AI warms the pipeline, but humans close it.
Next step:
Leaders can arm human reps with G2 Buyer Intent data to walk into conversations with context—knowing which competitors are being considered, which features matter most, and which signals triggered the buyer’s search.
ABM is no longer a campaign — it’s an operating system. Buyers don’t see silos between brand, demand gen, and sales. If your brand isn’t trusted, AI search won’t surface you, no matter how good your targeting is.
G2 insight:
Reviews mentioning “trust,” “reliability,” and “verification” were tied to higher satisfaction scores (4.59/5 vs. dataset average 4.57/5). Brand credibility is becoming a revenue primitive.
Next step:
CMOs can invest in G2 profile optimization (verified reviews, badges, analyst recognition) to build credibility. Combined with intent data feeding into ABM workflows, this creates a full-funnel operating system where brand, demand, and sales scale together.
Edited by Supanna Das
Kamaljeet Kalsi is Sr. Editorial Content Specialist at G2. She brings 9 years of content creation, publishing, and marketing expertise to G2’s TechSignals and Industry Insights columns. She loves a good conversation around digital marketing, leadership, strategy, analytics, humanity, and animals. As an avid tea drinker, she believes ‘Chai-tea-latte’ is not an actual beverage and advocates for the same. When she is not busy creating content, you will find her contemplating life and listening to John Mayer.
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