Figuring out the most efficient way to grow revenue has always been a cornerstone of B2B startups. But today, compressed product cycles, shifting buyer expectations and the rise of AI is forcing CROs to adapt the rulebook in real time.

At the 2025 Battery Kick-Off (BKO) in San Francisco, more than a hundred CROs and revenue leaders came together to tackle the most pressing questions facing go-to-market organizations today.

As Battery Operating Partner (and former two-time CRO) Bill Binch reminded the room: “You were hired for the playbook that worked last time, but if you don’t adjust it, you’ll lose credibility fast.”

Here are six takeaways shaping the new, AI-powered CRO playbook, as shared by revenue leaders who’ve built and scaled iconic, industry-leading teams.

1.  AI moves from product feature to sales force multiplier

AI isn’t just transforming what companies sell, it’s reshaping how revenue teams operate.

Leaders are embedding AI into daily workflows to free up time and amplify selling capacity.

At OpenAI, Head of Revenue Ashley Kramer’s team has no sales development reps at all. Instead, an internal workflow agent – nicknamed Taylor – qualifies inbound leads, parses intent and even closes deals. Sellers prepare for high-stakes conversations by role-playing with a simulation agent, while Kramer herself relies on ChatGPT as a “chief of staff” surfacing account history, sentiment and competitive intel before meetings.

Gong* CRO Shane Evans shared that conversational intelligence tools now give each rep back nearly a full workday per week. Instead of losing hours to CRM updates, call notes and forecasts, reps are redirecting that time to higher-impact selling.

Across the board, AI isn’t an experiment or add-on. It’s becoming the backbone of revenue operations.

2.  The “quota question” in the AI era

Quotas have always been the north star of sales teams. But AI is reshaping what they mean, how they’re set and how they’re achieved.

At OpenAI, traditional quota-setting has been scrapped entirely. Targets can expand by billions from one quarter to the next with no corresponding jump in headcount. There’s no variable compensation plan because adoption is too volatile to anchor incentives. As Kramer put it: “I probably have 5x the target with one-fifth the team.”

CRO’s are looking to bend the traditional $1M quota per sales rep into more using AI. Boards are responding by pushing for AI-first strategies anchored to measurable conversion outcomes, not just tool adoption.

3.  Why AI can automate selling, but not trust

For all its sophistication, AI isn’t replacing the human factor in enterprise selling.

Kramer noted that Taylor can close smaller contracts, but multimillion-dollar deals still demand her personal involvement. For those, Ashley personally gets involved and shares her direct cell number. “That kind of trust is not going away,” she says.

It’s a pattern across companies. At Vercel, AI bots qualify inbound leads, but a human still oversees edge cases. At Gong, forecasting tools flag risks, but Evans steps in to coach strategy directly.

Just as system administrators thrived when they embraced the cloud, sellers who embrace AI will thrive, too. But in complex deals, trust, negotiation and empathy remain distinctly human.

4.  Hire for technical curiosity

The sales org chart is being rewritten. SDR-heavy models are fading, while new roles like GTM engineers, RevOps specialists and forward-deployed engineers are on the rise.

At Vercel, sales engineers were redeployed into a dedicated GTM engineering team. Unlike traditional SEs, these hires were former developers who could both sell and code — building internal tools that rewire the sales motion itself. One of their first projects was an inbound qualification bot, built in just six weeks and costing under $1,000 a month to run. The bot improved lead-to-opportunity conversion while freeing SDRs to focus on higher-value outbound work.

Forward-deployed engineers, meanwhile, are being embedded directly with customers in highly regulated industries, where deep domain knowledge is required to fine-tune AI models before scaling.

Michelle Benfer, former CRO at BILL and HubSpot, stressed that intellectual curiosity and coachability now outweigh tenure as predictors of sales success. Dennis Lyandres, former CRO at Procore, added that in leaner, AI-powered orgs, high performers shine while average performers are quickly exposed.

The new hiring bar? Technical curiosity and adaptability over resume pedigree.

5.  Design for change, not static playbooks

Traditional selling frameworks like MEDDICC — which asks reps to qualify deals based on metrics, economic buyer, decision criteria & decision process, ID pain, champion, and competition — or stage-based forecasting, are losing relevance in AI-powered GTM, where sales motions are dynamic, data-driven, and continuously adapted in real time.

At New Relic, usage data is combined with CRM records to highlight patterns invisible to traditional forecasts. These signals shape how reps prioritize accounts, how managers coach and how leadership directs strategy.

Gong is taking a similar approach to forecasting. Instead of relying on rep-entered deal stages, systems now assign stages automatically and prescribe next steps. The question shifts from “What stage is this deal in?” to “What is the system predicting what this customer will do next?”

6.  The evolving role of the CRO

Perhaps the most profound shift is in the role of the CRO itself. Today’s revenue leaders are part sales chief, part product thinker and part analyst.

Vercel COO Jeanne DeWitt Grosser observed that the best GTM orgs are equal parts revenue generating and R&D. Rather than receiving fully packaged motions, CROs are handed raw product capabilities and must quickly test where they resonate with customers, identify what’s missing, and adapt accordingly. In her words, that means spending “half my job being a product manager”.

Lyandres emphasized that learning velocity is the CRO’s most critical skill. With customer behaviors and AI capabilities evolving rapidly, leaders must set the tone by experimenting, adapting and discarding what doesn’t work.

Where GTM goes from here

The new CRO playbook isn’t humans versus AI, but humans amplified by AI. The leaders who embrace this balance will not only future-proof their own roles; they’ll build revenue teams capable of thriving in the most transformative GTM era yet.