Sales representatives are increasingly turning to generative AI tools to alleviate the burdens of paperwork and data entry, which have historically hampered productivity. With sales professionals spending only 25% of their time actively selling, a surge in AI adoption has emerged, as evidenced by a report from Cirrus Insight indicating that 56% of sales professionals now use the technology daily. This transition has the potential to double the time available for selling by automating tasks such as CRM updates and note-taking, in line with findings from Bain & Company.
Eilon Reshef, co-founder and chief product officer at Gong, succinctly captured the ongoing frustrations during AI Business’s Targeting AI podcast, stating, “No organization is happy about a quarter of your time actually doing your work. The revenue professionals are also not happy about it.” Gong’s revenue intelligence platform exemplifies this trend by automating routine tasks, allowing sales representatives to focus on closing deals. However, Reshef cautions that AI is not infallible: “AI is always going to miss something. We always recommend that someone review it before acting on it,” he noted.
Data shows that sales representatives waste approximately 33% of their time on administrative tasks, such as data entry and follow-ups, according to Agentive AIQ. Generative AI addresses this issue by generating first-draft proposals in seconds and significantly reducing the 52% of time spent on value messaging that Gartner reported. The automation landscape is transforming workflows, as Bain notes that AI can help increase selling time from 25% to a much higher percentage.
Quantifying the impact of this administrative overload reveals a stark reality: it represents a significant revenue drain. HubSpot reports that 64% of sales reps save between 1-5 hours weekly thanks to automation, while LinkedIn indicates that 38% save an average of 1.5 hours on research alone. Vena Solutions estimates that the average daily savings from AI utilization stands at about 2 hours and 15 minutes. These efficiencies are not merely anecdotal; over 80% of teams using AI report increased revenue, as confirmed by Sopro via Cirrus Insight.
Gartner’s analysis further highlights that sellers leveraging AI for buyer intelligence see account growth of 5% faster than their peers. By 2027, it is projected that 95% of research workflows will initiate with AI—a dramatic increase from under 20% in 2024—thereby simplifying the manual prospecting process. McKinsey’s findings bolster this narrative, demonstrating that AI can increase leads by 50%, reduce costs by 60%, and decrease call times by 70%.
However, field sales face distinct challenges, with representatives devoting 72% of their time to non-selling tasks. SPOTIO’s AI technology tackles this by optimizing routes and automating CRM updates, as outlined in their 2025 update. Beyond simple copilots, a new wave of agentic AI is emerging, capable of planning and executing autonomous tasks including prospecting and outreach, as reported by Gartner.
For instance, Gong’s Orchestrate connects valuable insights to actionable outcomes. Reshef noted in a 2025 press release, “AI has delivered incredible insights… but it has fallen short when it comes to linking these with automated actions across the revenue cycle.” Bain identifies 25 use cases for AI throughout the sales lifecycle, from lead generation to guided selling, underscoring the technology’s expansive potential.
ZoomInfo’s CEO, Henry Schuck, elaborated on their AI agent, which has replaced Deal Desk, processing around 100,000 deals yearly and reducing contract turnaround from 2-5 hours to just 7 minutes. This automation, which includes PDF validation and Salesforce updates, has yielded annual savings exceeding $1 million with an 85% automation rate, as shared on social media platform X.
Real-world applications further illustrate the transformative power of AI. Notion, for example, has integrated AI into its sales processes, using it for account prioritization and messaging. Composio’s AI SDR-Kit connects over 60 applications like Salesforce and Apollo for autonomous prospecting. Observations from Alex Lieberman indicate that sales is ripe for disruption through AI-driven web agents and LLM drafting, particularly in firms with revenues from $10 million to $100 million.
Despite the promise of efficiency gains, challenges remain. Bain emphasizes the need for process redesign rather than simple automation, warning that mediocre processes will yield mediocre results. To effectively harness AI, companies must prioritize human oversight and address risks like data security and anomalies, as highlighted by Gartner.
Looking ahead, 90% of commercial leaders expect to incorporate generative AI into their workflows, with 81% already experimenting with the technology, according to Salesforce/Sopro. Notably, small businesses are also joining the trend, with 75% planning to invest in AI. Gong’s 2026 State of Revenue AI report indicates that 70% of UK organizations are adopting AI, reflecting similar trends in the U.S. As agentic systems evolve towards multi-agent coordination by 2027, the sales landscape is set to shift from administrative tasks to strategic engagement, potentially increasing win rates by over 30% in effectively deployed scenarios.
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