At ELEVATE 2025 in New York City, more than 80 GTM executives gathered for a full day dedicated to one pressing challenge facing every modern B2B organization: What does it truly mean to be AI-native, and how do we build a GTM playbook ready for 2026 and beyond?
Set against the backdrop of ServiceNow’s stunning Hudson Yards office, the event brought together leaders from across industries, business models, and stages of maturity. But they all arrived with a shared reality: the pace of change has never been faster, customer expectations have never been higher, and the gap between “what we promise” and “what customers expect us to prove” has never been smaller.
Throughout the morning, executives surfaced common themes that define the moment we’re in:
- Pipeline velocity is shifting rapidly
- Champions are under more internal scrutiny
- Proof of value is now expected from the very first conversation
- GTM teams are being asked to do more, with less, and faster
And as AI continues to transform how value is discovered, quantified, and validated, the group leaned into a deeper belief: being AI-native isn’t just about technology. It’s about reimagining how we partner with customers, orchestrate teams, and align around outcomes.
This mindset came to life most vividly during our afternoon workshops, where participants rolled up their sleeves, challenged assumptions, and co-created the foundations of the AI-native GTM playbook. Below are the insights from Group 2: Co-Create & Commit.
Inside the Workshops: Co-Creating the AI-Native GTM Playbook
Participants broke into five scenario groups, each tasked with solving a core challenge GTM leaders face today. The focus of Group 2: Co-Create & Commit was on accelerating value alignment and business case creation without adding more headcount.
Their scenario began with a familiar pressure:
“Demand is up 20%, but you can’t hire anyone new.”
Customer expectations continue to rise. Champions want proof of value faster than ever. Deals require alignment across more stakeholders, but today, sellers are often asked to co-create business cases before they’ve even spoken with procurement or finance.
Meanwhile, AI can model return on investment (ROI) in seconds. Yet customers still struggle to trust the numbers. Internal alignment is hard. Confidence wavers. Deals stall.
The question Group 2 tackled head-on:
How do you reimagine Co-Create & Commit balancing scale, trust, and human judgment in an AI-native world?
Below is their creative vision.
The Big Idea: The AI Value Mad Lib Experience
Group 2 envisioned a GTM motion powered by a hyper-personalized, AI-assisted co-creation engine that transforms how buyers and sellers build value cases together.
Their concept, nicknamed the AI Value Mad Lib Experience, centers around three core capabilities:
1. A Dynamic Value “Mad Lib” Simulator
A digital workspace where customers and sellers fill in assumptions, goals, challenges, and priorities together. Rather than a static template, this is a flexible, exploratory tool that lets non-technical users create, test, and adjust scenarios instantly.
2. An AI Seller (Or Digital Teammate)
For buyers who are not ready to speak with sales yet, an AI agent captures inputs, personalizes insights, and sets the stage for a warmer handoff to a human seller.
This agent also:
- Preps the human rep with context, sentiment, and objections
- Engages with existing customers using real-time signals
- Supports early co-creation without adding headcount
3. A Digital Twin for Value Storytelling
The AI engine models how changes in product usage, processes, or decisions ripple through the customer’s business. Sellers and champions can jointly explore:
- What-if scenarios
- Risk zones
- Value acceleration paths
- Peer benchmarks and anonymized outcomes
Together, these elements shift the early sales conversation from “generic discovery” to collaborative design, long before the first procurement meeting.
Practical Plays: What Teams Can Do Now
To move toward this vision, Group 2 identified three near-term steps:
1. Launch a Coaching Agent for Sellers Today
Utilize AI agents to help support the seller, including:
- Drafting narratives grounded in customer context and industry benchmarks
- Summarizing call transcripts and extracting themes, risks, and stakeholder priorities
- Recommending next steps aligned to proven value-selling motions
- Preparing reps for customer meetings with real-time insights, predicted objections, and tailored talking points
This is a safe, scalable entry point, and one that Ecosystems customers are already experiencing through ViViEN™, Ecosystems' Virtual Value Engineer.
ViViEN™ acts as a behind-the-scenes strategist, pulling from discovery data, value assessments, external signals, and outcome benchmarks to help sellers show up smarter and more prepared.
2. Pilot Manual “Mad Lib” Workshops
Before building technology, teams can simulate the process:
- Early discovery calls
- Value statements
- Scenario testing with customers
- Pulling in win/loss and usage insights
These sessions help validate what resonates before automation.
3. Assess Customer AI Readiness
Not every buyer will trust AI on day one. Group 2 recommended scoring customers on their:
- Appetite for automation
- Trust in AI-generated insights
- Preferred interaction style (human-first vs. digital-first)
This informs where to pilot AI-led co-creation.
The Change Levers: What Must Shift to Make This Work
Group 2 also surfaced two foundational organizational shifts:
1. Experiential Playgrounds
A sandbox for both sellers and customers to:
- Interact with early AI prototypes
- Practice new workflows
- Learn how to collaborate with digital teammates
- Develop confidence before full-scale rollout
This is exactly why the ViViEN™ Innovation Labs were created. Through the Innovation Labs, executives and practitioners from top SaaS companies are given the opportunity to test-drive ViViEN™ and model prompts and value hypotheses. Sign up for the chance to participate here.
2. Clear Guardrails and Value Realization Data
AI should never promise outcomes humans can’t deliver. Organizations need governance around:
- What AI can say
- What data it can reference
- How value realization is captured and fed back into the engine
This ensures credibility is never sacrificed for speed.
How Ecosystems Helps Bring This Vision to Life
What Group 2 imagined aligns directly with the future Ecosystems is building.
ViViEN™ AI 2.0: Your Virtual Value Engineer
ViViEN™ helps teams:
- Model ROI instantly
- Create tailored value narratives
- Prepare for customer meetings
- Identify missing proof points
- Strengthen alignment across champions, finance, and procurement
The future Group 2 envisioned is not hypothetical. It’s emerging inside the Ecosystems platform today.
If you are interested in learning more, please contact our team today.
