Home » Lusha CEO Declares Manual Sales Prospecting ‘a Tax,’ Touts AI-Powered Sales Streaming

Lusha CEO Declares Manual Sales Prospecting ‘a Tax,’ Touts AI-Powered Sales Streaming

In a bold declaration aimed at sales organizations worldwide, Yoni Tserruya, co-founder and CEO of the go-to-market (GTM) intelligence platform Lusha, asserts that the age of manual sales prospecting is over. He labels the long-held practice an inefficient “tax” on sales teams.

Tserruya argues for a fundamental shift toward an AI-powered “sales streaming” model designed to automate lead generation and free sales professionals to focus on high-impact, human-centric work.

The Crippling Cost of Manual Prospecting

For decades, the ability to manually hunt for, qualify, and route leads has been a core competency for sales development representatives (SDRs). Tserruya, however, argues this is a profound misuse of human capital.

“Manual prospecting is not a skill; it is a tax,” Tserruya said. “Every sales leader knows it is painful, admin-heavy work that wastes 70% of a rep’s time, yet many still treat it as necessary. I do not buy that.”

Industry data strongly support this sentiment. A recent State of Sales report from Salesforce found that sales reps spend only about 28% of their week selling. Most of their time is consumed by administrative tasks, data entry, and manual lead prospecting—precisely the work Tserruya believes is ripe for AI disruption. This inefficiency wastes time, lowers morale, and leads to higher burnout rates among sales teams.

‘Sales Streaming’: A Paradigm Shift Inspired by Consumer Tech

Tserruya’s proposed solution, “sales streaming,” moves away from the traditional model of an SDR starting their day with an empty CRM and a daunting list of accounts to research. Instead, he likens the experience to a consumer streaming service like Spotify.

“Spotify changed the way we consume music. You do not wake up and build a playlist from scratch, song by song, every morning. It already knows what you want to hear,” Tserruya said. “Sales Streaming works the same way.”

In practice, the AI platform analyzes a company’s most successful closed-won deals, historical CRM data, past user searches, and real-time intent signals from across the web. It learns the characteristics of an ideal customer profile (ICP) and then automatically curates and delivers a “playlist” of high-intent, qualified leads directly to the sales rep.

“Yesterday’s SDR opened a CRM and stared at a blank list. Today’s SDR opens a Lusha Playlist already filled with live, AI-curated opportunities,” Tserruya said. “One starts with guesswork, the other starts with action.”

Redefining Success: From Volume to Velocity

This new workflow necessitates a new set of key performance indicators (KPIs). According to Tserruya, managers should avoid tracking vanity metrics like the number of dials made or emails opened, which incentivize volume over quality. In a sales streaming model, the focus shifts to speed and effectiveness.

“Success is not dials or opens. It is time-to-engagement,” Tserruya said. “It is how responsive the team is to live signals. That is the new GTM muscle.”

This measures the team’s ability to act decisively when the AI surfaces a high-value, time-sensitive opportunity, which is a far more accurate indicator of a high-performing sales motion.

The Dawn of the Proactive and Autonomous Tech Stack

Tserruya sees this as part of a larger evolution in business technology. The future go-to-market tech stack, he predicts, will be proactive, not reactive. The global market for AI in sales is booming, with projections from Grand View Research suggesting a compound annual growth rate (CAGR) of over 12% from 2024 to 2030, as more companies seek to embed intelligence into their revenue operations.

“The GTM tech of tomorrow will not wait for humans to query it,” Tserruya said. “It will surface what matters most, when it matters.”

He pointed to two major shifts on the horizon: autonomous lead generation, where the system finds and qualifies leads without human intervention, and intent-driven engagement, where AI not only identifies a potential customer but also provides the context for why now is the right time to reach out.

Trust as the Engine: Data Quality in the Age of AI

The entire sales streaming model hinges on a foundation of trust in the AI’s recommendations. With AI hallucinations being a persistent concern, the quality and accuracy of the underlying data are paramount. The cost of insufficient data is significant, with Gartner research suggesting it can cost organizations an average of $12.9 million annually.

“The success of Sales Streaming depends on trust. That is why at Lusha, we only use verifiable, compliant data,” Tserruya said. “Our enrichment engine constantly updates from live signals and scores every lead for ICP fit, recency, and patterns. Compliance-powered prospecting has become the new standard.”

The Evolved SDR: Fewer Roles, Greater Impact

The automation of top-of-funnel activities inevitably raises questions about the future of the SDR role. Tserruya acknowledged that the landscape is changing, leading to more strategic, albeit fewer, human roles.

“The SDR role is not disappearing; it is evolving. I’m afraid there will be fewer SDRs, but each will have more impact,” Tserruya said. “The best will let the system handle prospecting, routing, and enrichment so that they can focus on the human part: trust, connection, and judgment.”

In this new world, the most valuable skills for a sales professional will include the ability to work symbiotically with AI, interpret complex intent signals, and act with speed and precision.

“Relevance is the new personalization,” Tserruya said. “Great reps will know how to interpret intent, move quickly when opportunity appears, and build automations that give them an advantage.”

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