Over the past decade, B2B go-to-market (GTM) organizations have grown increasingly complex and fragmented. Revenue operations functions emerged to drive consistency, efficiency, and alignment across the GTM processes and systems that connect sales, marketing, and product functions. 

While never seamless, RevOps managed the mission. It standardized processes, improved data quality, drove common metrics, and brought much-needed discipline to commercial operations. 

But now, the environment RevOps was designed to support has been upended. It’s barely recognizable. AI has altered both the way buyers buy and how organizations operate. Buyers increasingly use AI to research solutions, compare vendors, and answer questions that were once directed toward websites and sales reps. At the same time, executive teams are aggressively pursuing AI investments to avoid falling behind competitors and drive organizational productivity. And the change is nowhere near through. 

AI creates opportunities to fundamentally rethink how GTM work gets done. Activities that once required significant human effort can increasingly be automated, augmented, or redesigned altogether. As AI changes the work humans perform directly, this transformation won’t go well without operations leaders defining sharp objectives, establishing guardrails and governance, driving better decisions, and ensuring that technology delivers meaningful outcomes. 

AI Has Altered The Conditions Under Which RevOps Operates  

For RevOps leaders, AI has changed the game in three ground-shifting ways: 

  • Changing buyer behavior has reduced visibility into the customer journey. As buyers increasingly rely on AI-mediated research and decision-making, many of the engagement signals organizations historically relied upon become harder to observe and interpret. 
  • Mounting pressure to adopt AI risks prioritizing deployment over outcomes. Organizations face increasing pressure to demonstrate progress with AI, creating a risk that technology adoption becomes a goal in itself rather than a means of improving customer experiences, decision quality, and business performance. 
  • AI will redefine operational work rather than simply automating it. The most significant opportunities will come from redesigning processes, not merely accelerating existing workflows. This requires organizations to rethink how work is managed, measured, and governed. 

RevOps Must Redefine Where It Creates Value 

The path forward requires RevOps leaders to: 

  • Apply AI to maximize customer, then company value. Organizations that optimize exclusively for internal benefits risk unintentionally creating friction for buyers and customers. RevOps leaders need to prioritize AI investments that improve customer outcomes and experiences over internally focused efficiency, productivity, or cost reduction outcomes. 
  • Establish a data foundation for AI excellence. AI systems depend on trusted business context. Revenue operations leaders should prioritize data quality, common business definitions, semantic consistency, and governance practices that allow copilots, agents, and AI-enabled workflows to operate from a reliable foundation. 
  • Ruthlessly focus resources on transformative operations.  AI’s greatest impact comes through reimagining how work is performed, how decisions are made, and how functions coordinate efforts across the revenue engine.  RevOps teams should prioritize transformative AI use cases ahead of efforts geared toward making legacy processes incrementally faster. 

Revenue operations emerged to help organizations navigate complexity. That challenge has not disappeared. What has changed is the nature of the complexity itself. The organizations that benefit most from AI will not necessarily be those that deploy the most technology. They will be those that successfully apply AI to create customer value, establish trusted operational foundations, and transform how go-to-market teams work together. 

Join me and my colleagues Vicki Brown, Laura Cross, Brett Kahnke, Katie Linford, and Anthony McPartlin for a webinar on September 22 as we exchange 2027 budget planning recommendations for Revenue Operations leaders. We’ll each offer specific recommendations on where revenue operations leaders should invest, divest, avoid, and experiment as they prepare for the next phase of AI-enabled growth. 

Read the full report: Budget Planning Guide 2027: Revenue Operations Leaders Must Steer Go-To-Market AI

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