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Sales leaders today face relentless pressure to deliver results amid shifting buyer behavior, evolving tech stacks, and mounting internal inefficiencies. AI is often positioned as the silver bullet—but without a cohesive strategy, most AI efforts fall flat. The real challenge isn’t acquiring AI tools; it’s building an AI-first sales organization.
According to the Gartner® report, 2025 Strategic Roadmap for an AI-First Sales Organization,
“AI technology — including generative AI (GenAI), machine learning (ML), AI assistants and agents — is changing the way sales organizations work, from top to bottom.”
Yet despite the influx of innovation, “new technology that is not integrated into seller workflows contributes to overwhelming sellers and reduced performance”.
How, then, can leaders achieve a genuinely AI-first sales organization?
Gartner® offers a concrete definition of what it means to be AI-first—and it’s far more than implementing a few new tools.
“Future-state sales technology is composable, adaptive and action-oriented, revenue-outcome-focused and AI-infused.”
We believe this reflects a structural shift in sales org design. AI-first isn’t a bolt-on—it’s a blueprint. It means building a stack and a strategy that are:
“An AI-led sales technology strategy helps sales operations leaders mold their technology architecture to fit sellers’ and buyers’ needs, and provides the best chance for increased revenue and business outcomes.”
An AI-first strategy must serve real workflows. If it doesn't fit naturally into how buyers and sellers work, it will be difficult to derive ROI. AI assistants and agents should meet users where they are, removing friction from selling motions—not adding another disparate place to log in.
Composable systems allow organizations to move fast, adapt to new buyer expectations, and plug in AI wherever it's most needed. They make it possible to orchestrate intelligence across platforms—CRM, revenue intelligence, enablement—without duplicating functionality or overwhelming sellers with redundant tools.
This reinforces the need for integrated AI. For AI sales assistants and agents to work, they must operate across the full revenue stack. Point solutions won’t cut it. AI has to be able to pull insights from disparate tools, synthesize them in context, and present them in ways that are immediately actionable—without requiring sellers to jump between platforms.
The future isn't just about insights—it's about execution. AI-first systems must not only predict what sellers should do next, but actually help them do it. This is where embedded AI becomes a force multiplier: driving consistency, minimizing guesswork, and turning strategy into seller behavior—automatically.
AI will no longer be a back-end feature or an add-on to analytics. It becomes the interface itself—the primary way sellers interact with data, systems, and strategy. This redefines the seller experience, moving from static dashboards to dynamic, conversational, intelligent guidance.
This is a warning against building anything in isolation. AI-first doesn’t just mean having AI. It means building with AI as a design constraint—ensuring new tech integrates natively into the broader ecosystem of assistants and agents. If it can’t be orchestrated, it doesn’t belong in the stack.
This is where AI becomes a teammate. Not just surfacing insights—but executing alongside the seller. When agents can qualify leads, recommend follow-ups, or even trigger actions autonomously, sellers are freed to focus on the human side of selling—building trust, navigating complexity, and closing deals.
The B2B buying landscape is shifting rapidly. According to Gartner®, “61% of overall buyers we surveyed said they prefer a rep-free experience.” As buyer autonomy increases, sellers must bring immediate value when they do engage.
Productivity gains remain elusive when AI is not fully integrated. The report explains, “For sellers, AI can free up time spent on non-client-facing value tasks, but only if it is integrated into existing systems and seller processes.” Additionally, “If a seller must suspend or abandon work in one platform to complete the workflow in another platform, the organization faces increased frustration, poor data hygiene, skipped steps or other undesirable sales outcomes such as inaccurate pipeline results and analysis.” [PC4]
Disconnected AI creates noise, not value.
[PC5] Gartner® advises: “Move forward with your AI-first evolution by piloting new technologies that align with your sales strategy, improve sellers’ workflows and result in increased revenue and improved sales outcomes”. The best AI-first orgs deploy intentionally and measure relentlessly to outperform competitors and future-proof the sales organization
Transforming into an AI-first sales organization doesn’t happen through isolated tech upgrades. It requires strategic investment across data architecture, interfaces, workflows, and measurement systems. The Gartner® report, 2025 Strategic Roadmap for an AI-First Sales Organization, provides specific, actionable recommendations for leaders driving this change.
“To support sales composability, the future-state sales organization will have a modern architecture that supports processes and results, including: unified and consolidated data environments that eliminate traditional silos among the sales, marketing, customer service and customer success functions.”
This isn’t just about improving access to data—it’s about dismantling the structural silos that keep AI from delivering value. AI can’t optimize customer engagement if it doesn’t have a full view of the customer journey. By consolidating data across revenue functions, leaders create the connective tissue required for predictive insights, personalization, and intelligent orchestration across the funnel.
“By 2028, 60% of B2B seller work will be executed through conversational UIs that use GenAI sales technologies, up from less than 5% in 2024.”
This is a fundamental shift in how work gets done. Rather than relying on menus or filters, sellers will increasingly speak or type commands—“Show me at-risk deals,” or “Draft an email to re-engage this prospect.” These interfaces reduce friction and cognitive load, making AI outputs faster to access and easier to act on. Leaders should prioritize tools that bring intelligence to the seller in the most intuitive, human-centric format possible.
“Before investing in any AI-first new application, sales operations leaders should consider the full extent of capabilities already available to them in the existing tech stack, such as AI agents or next best action ML. Doing so will enable them to leverage the value of their tech stack without increasing seller effort.”
This is a clear call to shift the focus from acquisition (of point solutions) to activation (of connected revenue architectures).
We feel this means sales leaders should prioritize embedding intelligence into systems their teams already use. The goal isn’t to expand the tech stack with endless point solutions—it’s to orchestrate actions and insights across multiple systems, with AI as a single UI. In this way, AI sales agents that integrate with existing platforms, orchestrate actions, and deliver guidance at the point of execution can drive real impact without adding complexity for sellers.
That last part is critical: “without increasing seller effort.” When AI is deployed thoughtfully, it doesn’t feel like another tool—it feels like a teammate. It works behind the scenes to surface insights, streamline decisions, and reduce context switching. Organizations that treat AI as an embedded layer across lead-to-revenue processes, rather than a standalone solution, will be the ones that actually see benefits.
The report encourages leaders to, “Hold the AI you put in place accountable for results, much like human sellers are responsible for their outcomes.”
Too often, sales organizations implement AI and hope for impact without tracking whether it’s actually delivering. This recommendation underscores the importance of operationalizing measurement: AI tools and agents should have clear KPIs tied to seller behavior and business outcomes. If your AI isn’t accelerating deal velocity or increasing forecast accuracy, something’s wrong. Treat AI agents like a revenue contributor—monitor its output, iterate on its inputs, and ensure it performs just like any other team member.
We feel the message from Gartner® is clear: “For AI to be effective, sales must adopt an AI-first strategy — designing the technology architecture to fit sellers’ needs and integrate into workflows, and intentionally applying AI to augment sellers’ capabilities and create actionability rather than simply collect data”.
Download the Gartner® report, 2025 Strategic Roadmap for an AI-First Sales Organization, for the full framework and strategic guidance.
At Vivun, we’re helping Sales teams operationalize this transformation. Let’s build the AI-first future—intentionally.
Source:
Gartner, 2025 Strategic Roadmap for an AI-First Sales Organization, Melissa Hilbert, Adnan Zijadic, 5 May 2025.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved
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