MAROKO133 Update ai: Gong study: Sales teams using AI generate 77% more revenue per rep Ed

📌 MAROKO133 Eksklusif ai: Gong study: Sales teams using AI generate 77% more reven

The debate over whether AI belongs in the corporate boardroom appears to be over — at least for those responsible for generating revenue.

Seven in 10 enterprise revenue leaders now trust AI to regularly inform their business decisions, according to a sweeping new study released by revenue intelligence company Gong. The finding marks a dramatic shift from just two years ago, when most organizations treated AI as an experimental technology relegated to pilot programs and individual productivity hacks.

The research, based on an analysis of 7.1 million sales opportunities across more than 3,600 companies and a survey of over 3,000 global revenue leaders spanning the U.S., UK, Australia and Germany, paints a picture of an industry in rapid transformation. Organizations that have embedded AI into their core go-to-market strategies are 65% more likely to increase their win rates than competitors still treating the technology as optional.

"I don't think people delegate decisions to AI, but they do rely on AI in the process of making decisions," Amit Bendov, Gong's co-founder and chief executive, said in an exclusive interview with VentureBeat. "Humans are making the decision, but they're largely assisted."

The distinction matters. Rather than replacing human judgment, AI has become what Bendov describes as a "second opinion" — a data-driven check on the intuition and guesswork that has traditionally governed sales forecasting and strategy.

Slowing growth is forcing sales teams to squeeze more from every rep

The timing of AI's ascendance in revenue organizations is no coincidence. The study reveals a sobering reality: After rebounding in 2024, average annual revenue growth among surveyed companies decelerated to 16% in 2025, marking a three-percentage-point decline year over year. Sales rep quota attainment fell from 52% to 46% over the same period.

The culprit, according to Gong's analysis, isn't that salespeople are performing worse on individual deals. Win rates and deal duration remained consistent. The problem is that representatives are working fewer opportunities — a finding that suggests operational inefficiencies are eating into selling time.

This helps explain why productivity has rocketed to the top of executive priorities. For the first time in the study's history, increasing the productivity of existing teams ranked as the number-one growth strategy for 2026, jumping from fourth place the previous year.

"The focus is on increasing sales productivity," Bendov said. "How much dollar-output per dollar-input?"

The numbers back up the urgency. Teams that regularly use AI tools generate 77% more revenue per representative than those that don't — a gap Gong characterizes as a six-figure difference per salesperson annually.

Companies are moving beyond basic AI automation toward strategic decision-making

The nature of AI adoption in sales has evolved considerably over the past year. In 2024, most revenue teams used AI for basic automation: Transcribing calls, drafting emails, updating CRM records. Those use cases continue to grow, but 2025 marked what the report calls a shift "from automation to intelligence."

The number of U.S. companies using AI for forecasting and measuring strategic initiatives jumped 50% year over year. These more sophisticated applications — predicting deal outcomes, identifying at-risk accounts, measuring which value propositions resonate with different buyer personas — correlate with dramatically better results.

Organizations in the 95th percentile of commercial impact from AI were 2 to 4X more likely to have deployed these strategic use cases, according to the study.

Bendov offered a concrete example of how this plays out in practice. "Companies have thousands of deals that they roll up into their forecast," he said. "It used to be based solely on human sentiment, believe it or not. That's why a lot of companies miss their numbers: Because people say, 'Oh, he told me he'll buy,' or 'I think I can probably get this one.'"

AI changes that calculus by examining evidence rather than optimism. "Companies now get a second opinion from AI on their forecasting, and that improves forecasting accuracy dramatically — 10 [or] 15% better accuracy just because it's evidence-based, not just based on human sentiment," Bendov said.

Revenue-specific AI tools are dramatically outperforming general-purpose alternatives

One of the study's more provocative findings concerns the type of AI that delivers results. Teams using revenue-specific AI solutions — tools built explicitly for sales workflows rather than general-purpose platforms like ChatGPT — reported 13% higher revenue growth and 85% greater commercial impact than those relying on generic tools.

These specialized systems were also twice as likely to be deployed for forecasting and predictive modeling, the report found.

The finding carries obvious implications for Gong, which sells precisely this type of domain-specific platform. But the data suggests a real distinction in outcomes. General-purpose AI, while more prevalent, often creates what the report describes as a "blind spot" for organizations — particularly when employees adopt consumer AI tools without company oversight.

Research from MIT suggests that while only 59% of enterprise teams use personal AI tools like ChatGPT at work, the actual figure is likely closer to 90%. This shadow AI usage poses security risks and creates fragmented technology stacks that undermine the potential for organization-wide intelligence.

Most sales leaders believe AI will reshape their jobs rather than eliminate them

Perhaps the most closely-watched question in any AI study concerns employment. The Gong research offers a more nuanced picture than the apocalyptic predictions that often dominate headlines.

When asked about AI's three-year impact on revenue headcount, 43% of respondents said they expect it to transform jobs without reducing headcount — the most common response. Only 28% anticipate job eliminations, while 21% actually foresee AI creating new roles. Just 8% predict minimal impact.

Bendov frames the opportunity as reclaiming lost time. He cited Forrester research indicating that 77% of a sales representative's time is spent on activities that don't involve customers — administrative work, meeting preparation, researching accounts, updating forecasts and internal briefings.

"AI can eliminate, ideally, 77% of the drudgery work that they're doing," Bendov said. "I don't think it necessarily eliminates jobs. People are half productive right now. Let's make them fully productive, and whatever you're paying them will translate to much higher revenue."

The transformation is already visible in role consolidation. Over the past decade, sales organizations splintered into hyper-specialized functions: One person qualifies leads, another sets appointments, a third closes deals, a fourth handles onboarding. The result was customers interacting with five or six different people across their buying journey.

"Which is not a great buyer experience, because every time I meet a new person that might not have the full con…

Konten dipersingkat otomatis.

🔗 Sumber: venturebeat.com

📌 MAROKO133 Eksklusif ai: Watch: China introduces humanoid traffic robot to manage

A new AI-powered traffic robot has begun operating on the streets of Hangzhou, China’s tech hub, introducing a new chapter in urban automation.

Nicknamed Hangxing No. 1, the 1.8-metre humanoid now stands at the busy intersection of Binsheng Road and Changhe Road in the Binjiang district, where it directs traffic, detects violations, and issues polite voice warnings, according to Chinese media outlets.

In a city of nearly 12 million residents—many navigating at speed on motorcycles and in cars—traffic flow remains a long-standing challenge. The robot’s unusual appearance and role have quickly sparked curiosity and debate among locals.

In November, UBTech Robotics signed a deal with China to deploy Walker S2 humanoid robots along the Vietnam border, expanding the country’s public-facing robotics push.

AI intersection guardian

Hangzhou has begun testing a new AI-driven traffic robot, adding a futuristic presence to the busy streets of the Binjiang district. Hangxing No. 1, a humanoid-style machine developed by the Hangzhou Traffic Police Tactical Unit, began its pilot deployment on December 1 at the intersection of Binsheng Road, according to CCTV.

Standing at 1.8 metres tall and equipped with cameras, sensors, and gesture-based signalling, the robot is programmed to support human officers during peak movement of vehicles, scooters, and pedestrians. Its movements—including signals to stop, proceed straight, or wait—were modelled on real police officers, allowing it to mimic standardised command gestures. It can also sound a digital whistle and synchronise its instructions with the existing traffic-light network.

According to NotebookCheck, Hangxing No. 1 does more than signal drivers: it monitors compliance in real time. The system can detect common violations such as riders without helmets, motorists crossing stop lines, and jaywalkers. When it spots an infraction, the robot issues a calm, pre-recorded reminder designed to correct behaviour without confrontation.

Powering the machine is a swappable battery system that delivers roughly 6 to 8 hours of operation, allowing it to cover peak commuting windows before returning to a charging dock on its own.

Future traffic policing

Hangxing No. 1 operates under a tightly integrated software system that continuously monitors its surroundings. Cameras feed live images into an AI model that can spot issues such as vehicles edging past stop lines, pedestrians crossing red lights, or cyclists drifting into unsafe zones.

When a violation is detected, the incident is logged and forwarded to a police database. During the early stages of deployment, a human officer remains nearby, stepping in only when polite audio warnings fail to correct behaviour.

According to traffic brigade staff member Zhang Wanzhe, the robot’s decision-making improves over time. Engineers review rush-hour footage to refine its judgment and reduce false triggers—an issue noticed during initial October trials when shadows and wind occasionally confused the system, reports Techeblog.

Integration with Hangzhou’s City Brain platform gives the robot access to a wider urban network, enabling predictive responses—for example, sending alerts or adjusting behaviour if traffic signals fail nearby. Developers say nearly every component, from weatherproof casing to motion controls and the multilingual voice system, was built specifically for the robot’s role on the streets.

Officials say the robot will continue to refine its abilities through live data collected at the intersection. Future updates could integrate large language models, enabling them to answer questions, provide route guidance, or support public safety education.

🔗 Sumber: interestingengineering.com