AI-Powered Sales Strategies in Practice
In the dynamic world of enterprise sales, deals are intricate, involving multiple decision-makers, and influenced by emerging technology strategies. To navigate this complex landscape, revenue leaders are turning to AI-driven revenue orchestration.
According to the 2025 State of Enterprise Revenue report, the key to success lies in repeatable, data-driven playbooks that ensure consistency and stronger alignment across revenue, finance, and go-to-market teams. These playbooks, powered by AI, can translate the winning habits of top performers into guided actions for every seller to follow.
Rohit Shrivastava, the EVP and Chief Product Officer at ServiceNow, emphasizes the importance of centralizing data for AI to effectively augment sales processes. A unified view of CRM, engagement, and forecasting data is crucial to provide sellers with the tools they need to engage more meaningfully with buyers, meeting the diverse needs of multiple stakeholders.
One aspect that sets expansion deals apart is their significant impact on revenue. Though they make up only 5% of total pipeline, they drive 13% of won revenue per quarter and close 20% faster than new logos. To treat expansion as a repeatable motion rather than an opportunistic approach may leave potential revenue on the table. AI can help scale top-performer behaviors, democratizing success beyond a small group of stars.
AI-powered revenue orchestration can also guide sellers through the complexities of sales, surfacing insights at crucial moments. For instance, AI can help identify early warning signs of stalled deals, enabling earlier executive engagement and potentially preserving the pipeline. Static CRMs may miss key signals that could indicate stalled deals.
Moreover, AI can operationalize repeatable plays for high-value motions like renewal, upsell, and executive engagement. By avoiding the need to reinvent the wheel deal by deal, sellers can spend more time selling, rather than updating systems and chasing down information. On average, sellers spend only 30% of their time actually selling.
The importance of efficient revenue processes across the entire revenue cycle cannot be overstated. According to the 2025 State of Enterprise Revenue report, sales teams are struggling with data overload and lack actionable insights. With 13 people, on average, involved in an organization's buying decision, the need for AI to surface relevant insights at the right time is paramount.
Gartner's findings support this, stating that sellers who effectively partner with AI tools are 3.7 times more likely to meet quota than those who do not. AI-powered revenue orchestration can help companies orchestrate forecasting, pipeline, and renewals as one motion, accelerating deal velocity.
In conclusion, the integration of AI into sales processes offers a promising solution to the challenges faced by revenue teams. By centralizing data, operationalizing repeatable plays, and surfacing actionable insights, AI can help sales teams engage more meaningfully with buyers, close deals faster, and unlock more revenue opportunities.
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