The sales and marketing go-to-market frameworks we’ve relied on for decades — staples like the funnel, the flywheel, and the buyer’s journey — are fast becoming obsolete … or are out the door already.
We all know that buyers use traditional online resources like vendor websites, trade publications, social media, and forums to conduct research and minimize their engagement with sales teams. But generative AI tools have empowered them in ways GTM teams can scarcely imagine.
- GenAI tools like ChatGPT are among buyers’ top sources of self-guided information
- 90% of buyers presently use GenAI for business purchasing
- Using GenAI, they’re less inclined to directly access vendor websites
- And they’re considering more vendors than they would have otherwise
Current GTM frameworks can’t detect or reflect the real-time behaviors and intentions of AI-empowered buyers. To succeed, B2B leaders must flip the power dynamic back, reclaiming control through smarter strategies driven by data, signals, and their own use of AI.
Here’s how.
GTM AI Makes the Traditional Go-to-Market Funnel Obsolete
The funnel, which we’ve depended so heavily on to track the buying journey, hasn’t failed because it was poorly executed — it’s failed because it was never designed to handle the complexities of today’s AI-driven, buyer-first world.
Armed with tools like GenAI, buyers zigzag through buying stages now, reacting immediately to real-time insights and shifting priorities. Conventional GTM tools can’t keep up, providing information that is outdated, static, and frustratingly out of sync with reality.
Here are other reasons why the funnel no longer works:
Sellers Miss Early Opportunities
The funnel’s rigidity often blinds sellers to opportunities for early influence. Static funnels fail to provide these early insights, leaving sellers struggling to meet buyers where they are.
Buyers Demand Relevance and Timing
Prospecting that’s irrelevant or poorly timed can harm deals more than help them. Without a dynamic framework to adapt to real-time signals, sellers risk alienating people instead of converting them.
Flywheel Marketing Spins Out of Control
The flywheel promised a perpetual motion of growth, where delighted customers would fuel future demand through word-of-mouth and advocacy. But in today’s buyer-first, AI-driven world, the flywheel has lost its momentum. Here’s why:
Buyers Move Faster Than the Flywheel Spins
The flywheel assumes a cyclical, predictable relationship between marketing, sales, and customer success. But modern buyers don’t wait for the flywheel to catch up. With real-time data and AI-driven insights at their fingertips, they expect immediate relevance and action — not a slow spin through interconnected phases.
Flywheel Marketing Ignores Buyer Complexity
While the flywheel centers on customer advocacy, it fails to address how fragmented buying teams and independent decision-makers actually operate. With multiple stakeholders influencing decisions, there’s no single “moment of delight” that triggers the next rotation of the wheel. Instead, GTM strategies must adapt to unique, nonlinear buyer journeys for each stakeholder.
Customer Advocacy Alone Isn’t Enough
In an AI-first world, buyers rely on independent research and algorithmic recommendations far more than personal advocacy. A glowing referral means little if a competitor’s content, pricing, or product appears higher on a search engine or recommendation platform. Without leveraging data and intent signals, the flywheel stalls in its ability to generate sustainable growth.
Why the B2B Buyer’s Journey No Longer Maps the Path
We’ve already seen how AI-empowered buyers no longer follow a clean, sequential progression in the buying journey. But there are other ways the journey as we’ve relied upon it is now obsolete:
B2B Buyers Don’t Follow the Rules
The journey assumes buyers engage on your terms: consuming your content, entering your funnel, and converting through your prescribed steps. In reality, buyers are guided by their own priorities, often bypassing your touchpoints entirely. AI-driven platforms and third-party research shape their decisions before you even know they’re in the market.
The Buyer’s Journey is Built for Sellers, Not Buyers
The buyer’s journey was designed to help sellers guide prospects through a sales process, but it doesn’t reflect how empowered buyers operate today. They make decisions faster than sellers can react.
How GTM AI Maps A Better Way Forward
The answer isn’t to abandon traditional go-to-market activities entirely — it’s to evolve them for today’s unpredictable, buyer-first landscape. Modern frameworks can adapt in real-time to dynamic behaviors and preferences.
This transformation hinges on the power trio of data, signals, and AI, enabling sellers to:
- Harness data for precision: Pinpoint high-intent opportunities by analyzing real-time signals, such as website visits, content downloads, and email engagement.
- Leverage AI for personalization: Tailor messaging to individual buyer needs, fostering trust, boosting engagement, and speeding up decision-making.
- Act on signals to stay relevant: Adapt instantly to shifting buyer priorities, ensuring every interaction is timely and meaningful.
By combining data, signals, and AI, GTM leaders can leave behind outdated linear strategies and embrace a smarter, more agile approach to buyer engagement.
Examples of GTM AI in Action
| AI Capability | Explanation | Example |
| Identify Real-Time Intent | AI analyzes vast datasets, pinpointing buyers ready to purchase based on intent signals like visits to pricing pages or engagement with competitive content. Linear models can’t keep up, but AI seamlessly updates targeting strategies in real time. | A prospect downloads a competitor comparison chart and begins engaging with high-value case studies. AI flags this activity, prompting sales to prioritize personalized outreach immediately. |
| Anticipate Next Moves | Predictive analytics suggest next-best actions, ensuring sales and marketing align with the buyer’s stage — even when it changes unexpectedly. | A prospect viewing technical content receives an offer to connect with a subject matter expert, accelerating their decision-making process. |
| Enable Tailored Engagement | AI synthesizes buyer behavior across thousands of touchpoints, enabling GTM teams to deliver precise, personalized messaging in real time. | AI recommends industry-specific case studies to buyers based on their role and past engagement, improving relevance and increasing conversion rates. |
Empowering Sellers in a Buyer-First World
Selling at the speed of B2B requires more than just a modernized GTM strategy. It takes vision, discipline, and a willingness to challenge old paradigms. Here’s a helpful framework to get you started.
Step 1: Audit GTM Processes for Linear Dependencies
Start by identifying dependencies on linear, stage-based workflows and the risks they pose to buyer engagement and revenue outcomes. For instance:
Evaluate Legacy Processes
Conduct an in-depth review of your GTM strategies. Look for signs of inefficiency, such as rigid lead qualification criteria or declining conversion rates despite high pipeline volume. Some key questions to ask include:
- Are high-intent prospects failing to progress due to outdated MQL/SQL thresholds?
- Does your system lack the ability to share real-time data across marketing, sales, and operations?
- Are you integrating third-party intent signals from tools like ZoomInfo?
Use a flowchart tool to map a typical buyer journey through your system. Highlight points where rigid dependencies — such as requiring form fills for progression — create friction in the sales cycle.
Commit to Experimentation and Iteration
Transitioning to a dynamic framework requires a test-and-learn mindset. Pilot-test AI models within specific segments or verticals. Focus entirely on buyer intent signals and eliminate reliance on pre-defined stages.
For instance, use intent data from a GTM Intelligence platform like ZoomInfo to prioritize engagement with accounts that are demonstrating purchase readiness. For instance, accounts visiting pricing pages or competitor comparisons could trigger immediate outreach, bypassing traditional qualification steps.
Step 2: Implement GTM AI Tools to Monitor What Matters
AI is the foundation of a dynamic go-to-market framework, enabling real-time insights and adaptive engagement strategies. Here’s how to start:
Select the Right Tools
Prioritize AI-powered platforms that integrate seamlessly with your CRM and marketing systems. Look for capabilities such as:
- Predictive analytics to forecast buyer behavior and recommend next-best actions.
- Behavior-based segmentation to adapt outreach based on real-time signals.
- Lead prioritization to focus resources on the most promising opportunities.
Tools like ZoomInfo integrate with platforms like Salesforce, enriching pipelines with intent signals such as competitor activity, content engagement, or website visits.
Apply AI Across the Buyer Lifecycle
AI can dynamically adjust engagement strategies throughout the buyer journey:
- Early-stage: Monitor intent signals to identify accounts signaling purchase readiness.
- Mid-stage: Use predictive analytics to recommend high-value actions, such as sharing tailored content.
- Late-stage: Deliver hyper-personalized messaging to accelerate deal closure.
For instance, savvy use of Gen AI can identify a prospect engaging with technical documentation and recommends immediate outreach by a subject matter expert, accelerating decision-making.
Step 3: Redefine Success Metrics for a Non-Linear World
Traditional KPIs, like MQL-to-SQL conversion rates, don’t capture the complexity of today’s buyer journeys. Shift your focus to metrics that reflect the reality of dynamic engagement:
Engagement Velocity
Measure how quickly high-intent buyers progress through the pipeline. Use AI tools to track and optimize time spent at each stage.
Intent Alignment
Track how closely buyer actions (e.g., visiting pricing pages, downloading case studies) match purchase readiness.
Ecosystem Value Creation
Measure how effectively your solution solves buyer-specific challenges. This shifts focus from just closing deals to building lasting relationships.
Step 4: Re-Train Your Team
To succeed in a buyer-first, AI-driven world, teams must move away from static playbooks and embrace dynamic, real-time decision-making. This transformation starts with a mindset shift and continues with hands-on, practical training.
Foster a Mindset of Agility
Agility is the foundation of a dynamic GTM strategy. Your team needs to be empowered to interpret evolving buyer signals and adjust their strategies accordingly. This requires fostering a culture where adaptability is valued over rigid adherence to predefined stages or scripts.
Steps to foster agility:
- Scenario-based training: Conduct role-playing exercises simulating real-world buyer behaviors. Use intent data from platforms like ZoomInfo to create scenarios where teams must react to shifts in buyer activity.
- AI simulation tools: Train teams to use AI platforms that provide intent signals and predictive analytics. Ensure they understand how to act on these insights effectively.
- Feedback loops: Establish weekly debriefs where teams analyze what worked, identify missed opportunities, and refine their approach based on real-time data.
Practical Training Areas
Targeted training equips your team to harness AI insights effectively and transition to dynamic, behavior-driven engagement. Focus on these key areas:
Reading intent data: Help teams differentiate between levels of buyer interest and readiness:
- High interest: Multiple visits to thought leadership blogs or webinars.
- Ready-to-buy: Pricing page visits, product comparisons, or interactions with ROI calculators.
For instance, a prospect visiting a competitor’s pricing page may indicate high purchase intent. AI tools flag such signals, prompting sales outreach.
Agility in outreach: Train teams to pivot mid-cycle based on updated insights. For example:
- If AI detects a new stakeholder engaging with your website, prompt a tailored outreach strategy addressing their role.
For instance, ZoomInfo’s Workflows can automate alerts when a key decision-maker at a high-intent account engages with your content.
Measure adoption: Track how effectively your team acts on real-time insights with metrics like:
- Response time: Time between intent signal detection and outreach.
- Conversion rates: Success rates of AI-driven dynamic outreach compared to traditional methods.
For instance, companies that reduce response times to under 30 minutes improve lead conversion rates by 21%, according to InsideSales.
Conclusion
The collapse of the traditional sales funnel is more than a shift — it’s a wake-up call. We’re entering an era where data, signals, and AI aren’t just tools; they’re the foundation of a buyer-first paradigm. This isn’t about predicting buyer intent — it’s about building dynamic, self-sustaining ecosystems that evolve in real time to meet buyers where they are.
For GTM leaders, the challenge is clear: adapt or be left behind. By prioritizing data-driven precision, AI-powered personalization, and real-time adaptability, you can flip the script and reclaim control in an AI-dominated world. This isn’t just about keeping up; it’s about defining what’s next.
The leaders who embrace this evolution won’t just survive — they’ll set the standard for what buyer engagement looks like in the future. The question isn’t whether the funnel is dead — it’s who will lead the way in building the smarter, faster, AI-first models that come next.