2026 代理生产力影响报告

Powered byOutreach InsightsGroup findings from Outreach's proprietary research of Salesand Revenue organizations. By analyzing millions ofbuyer-seller interactions, deals, revenue workflows, andmarket trends, the OIG reports insights and best from the Outreach platform, focusing on qualified cohortsof active AI users. operational analysis from Outreach Account Executivesand Sales Development Representatives, conductedbetween January and February 2026 analysis designed to isolate the impact of AI onenterprise workflows: based on specific usage patterns within the Outreachecosystem. It does not serve as a cross-industry or globalbenchmark index. Our methodology prioritizes controlleduser groups to ensure data credibility without implying broad AI Agents AreReshapingEnterprise RevenueExecution Engagement Lift Drives Conversion Momentum AI Improves Message Effectiveness 3xReps saw an averageof 3x improvementin reply rates whencompared to non-AImessaging. Higher engagement with AIoutreach led to an increase inreplies and meetings booked,creating a stronger top of thefunnel pipeline. Reply to meeting ratedoubled for both inbound and outbound cases. for sellers? In this report, we dive into real data that showshow AI agents are creating measurable impact acrossenterprise revenue organizations. 5xmeasurable lift in inboundfollow-up, resulting in 5xmore meetings booked. 10 execution by increasing buyer engagement, acceleratingconversions, reducing manual friction, and ultimatelyexpanding revenue capacity.Here are our core findings: across personalization, research,and administrative tasks. When reinvested into revenue-creating Enterprise RevenueGrowth NowDepends onWorkflow Efficiency Buying Committee Expansion: Deals now involve more stakeholders than ever before, requiring buy-inacross finance, security, legal, and technical teams. Multi-Threaded Complexity: Single-contact deals are disappearing. Your teams must now navigatecomplex internal structures and maintain relevance with multiple decision-makers simultaneously. engagement over longer periods. are still tasked with hitting aggressive targets. efficient, consistent execution. Revenue leaders facepressures that make traditional GTM motions harder tosustain without significant workflow evolution. Here are afew challenges in today's landscape: operational efficiency. The ask is no longer just to adopt technology, but to demonstrate how it manage these larger, longer, and complex deals exceeds the available capacity of the sales teamWithout a shift in workflow efficiency, revenue predictability is bound to suffer. with the most AI experiments.They'll be the ones that operationalize AIresponsibly, securely, and with clear intent.Abhijit Mitra, CEO, Outreach AI AdoptionFrequencyCorrelates withWorkflow Impact > Daily Users (Power Users): Account Executives (AEs) and Sales DevelopmentRepresentatives (SDRs) take the lead in daily usage, leveraging AI for high-volume tasks likeprospecting, follow-ups, and meeting preparation. These users report the highest confidence in AIoutputs, with 85% trusting AI to handle complex workflows. > Weekly Users (Task-Specific): Customer Success Managers (CsMs) primarily fall into this category,using AI for account research, renewal planning, and QBR preparation. Confidence levels are on themoderate side, with 60% trusting AI for specific tasks but relying on manual workflows for others. sporadically, often for ad-hoc tasks or exploratory purposes. Confidence is lower, with 40%expressing trust in AI outputs. Our analysis of enterprise users shows different levels of AI adoption, depending on how deeply it's integrated intotheir workflows. The more you use something, the betteryour results will be. while many have access to AI tools,the extent to which they rely on them in daily operationsvaries a lot based on how often they use them. High-frequency usage often correlates with a shift in user behavior. Daily users tend to move beyond simple "drafting" assistance and start to leverage AI for strategic research and decision support.As reps and managers become more familiar with the tools, their trust in the system output seems to A Lift in Reply-to-Open Rates MeansStronger Messagesand PipelinePotential Engagement Signal Why did we measure reply-to-open rates? That's because reply-to-open rates isolate why theAI-generated message worked. while subject lines drive the first open, the body content determineswhether it sticks with buyers. Higher reply-to-open rates reflect stronger alignment with buyer needs,making them a critical early signal. We found that with AI Email Personalization: > One of our customers saw a 7 percentage point lift when using AI for personalized outreach. Higher reply-to-open rates are associated with increased meeting booking rates and a greater likelihood of the opportunity going through. Engagement is the earliest measurable lever in pipelinecreation, bridging the gap between