AI Saves Sellers 5 Hours Per Week

Artificial intelligence is delivering measurable efficiency gains for sales organizations, saving sellers an average of 4.8 hours per week, according to Gartner.

However, 72 percent of sales organizations reported low reinvestment of those time savings back into high-value sales activities, creating what Gartner calls a “reinvestment gap” that limits AI’s impact on commercial performance.

This comes despite findings from Gartner that sales organizations that achieve moderate to large AI time savings and then reinvest that time into high-impact sales activities are 2.2 times more likely to exceed customer growth goals and 3.1 times more likely to exceed lead-to-opportunity conversion goals, compared with organizations that reinvest less.

More than 1 in 10 (11.5 percent) of sales organizations said they have allocated AI investments to improving productivity, while 46 percent said their AI investments are centered on increasing revenue and reducing costs.

“AI is not the hero of this story; AI is the accelerant,” says Dan Gottlieb, vice president analyst in the Gartner Sales Practice. “The opportunity is not simply using AI to improve sales productivity. It is using AI to break through the constraints that limit sales output.”

Gartner further notes that there is a significant difference between sales organizations getting returns from their AI investments and those that don’t; one-quarter reported a 50 percent or higher positive return, while just one-fifth had a 50 percent or higher negative return, according to the firm’s research.

Gartner also found that the need to rethink productivity is urgent. Sales organizations continue to invest in CRM platforms, technology stacks, process redesign, automation, AI, and headcount, yet productivity gains remain constrained by operating models designed to scale primarily by adding more people.

Productivity innovators are pulling ahead by moving beyond headcount-based productivity models. These organizations build strong data infrastructure, reinvest AI time savings into high-value sales activities, and establish operating rhythms that improve seller performance and commercial outcomes.

To overcome the productivity paradox, CSOs should focus on three actions: owning AI-forward sales infrastructure, orchestrating winning seller behaviors, and capturing AI’s impact on sales capacity, the firm says.

“Sales productivity does not stall because reps forget how to sell; it stalls because the system quietly caps them,” says Gottlieb. “By redesigning the system around sellers, sales leaders can turn AI-enabled capacity into sustained productivity gains.”

According to the research firm, the discrepancy shows that AI value depends less on access to technology and more on how sales organizations redesign the systems around it.

Gottlieb adds that a better measurement would be what Gartner calls digital capacity units, or AI improvements in human equivalents. Such a measurement treats AI as a workforce resource, he explains. Examples include gains in productivity, closed deals, and win rates.

“Organizations that measure sales productivity at the customer segment or market level are 2.5 times more likely to exceed revenue growth goals,” Gottlieb says. 

Consumers Want AI Shopping Help, Not Purchase Decisions

Marketers should prioritize AI tools that support research and comparisons, Gartner urges.

As companies race to invest in agentic commerce, consumer willingness to let artificial intelligence make purchase decisions for them topped out at just 11 percent across lower-stakes categories, such as personal care and household supplies, according to Gartner.

The survey found greater openness to AI tools that help narrow product choices, as 31 percent of consumers said they would be willing to allow AI to narrow choices for household supplies purchases, and 28 percent were willing to do so for personal electronics purchases.

“Consumers are not looking to outsource shopping decisions to AI,” says Kate Muhl, a vice president analyst in the Gartner Marketing Practice. “They want AI to help them find better information, compare prices, identify deals, and narrow choices, while keeping final decision-making control for themselves.”

Marketers would do well, then, not to focus investments on fully autonomous shopping agents, the firm says.

Gartner cites trust and accuracy as the biggest barriers to broader adoption, noting that early adopters still encountered friction when using AI for shopping. Among consumers who used AI while shopping for recent purchases, 54 percent said they had to double-check the accuracy of all information generative AI tools provided, and 62 percent said information from genAI tools ended up being a waste of their time.

“Accuracy is now a brand issue,” Muhl says. “If consumers believe AI shopping tools create more work by requiring them to verify every recommendation, they will not see those tools as convenient or valuable. Marketers must prioritize transparent, reliable information, especially around price, product fit, and recommendations.

“The brands that earn consumer trust will be those that use AI to enhance consumer control, not replace it,” she adds.

Companies would also do well not to eliminate salespeople from the equation, despite consumers wanting to do more self-service in the buying journey.

A separate Gartner study found that 69 percent of B2B buyers said they prefer to validate AI-generated insights with human sales reps, even as 45 percent said they used genAI during recent purchases. Buyers also reported using an average of seven information sources as they evaluated vendors and products.

“B2B buyers are more comfortable using digital channels and genAI to navigate the purchase process on their own, but that does not eliminate the role of the seller,” says Robert Blaisdell, a vice president analyst and chief of research in the Gartner Sales Practice. “Buyers still turn to sales reps to validate AI-generated insights and support decision making at critical moments in the journey.”

As AI becomes a more common part of the B2B purchase journey, buyers are also weighing the reliability of the information they receive. Fifty-one percent said they are more likely to encounter misleading information from genAI, while 49 percent said they are more likely to encounter misleading information from sales reps.

These findings point to a more nuanced buying environment: Buyers want the speed and convenience of digital and AI-assisted research, but they still rely on sales reps when they need reassurance, context, and decision support. Reps remain the most important information source when buyers are researching a business problem or need, identifying a preferred supplier and securing internal support, and finalizing the purchase.

“Sales leaders should not interpret buyer preference for digital self-service as a signal that sellers matter less,” Blaisdell states. “It is a signal that sellers need to show up differently, engaging where they can help buyers validate information, reduce risk, and move forward with greater confidence.”