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Is Your Sales Org Exploring AI
or Excelling With It?

Discover what leaders in AI-enabled sales are doing differently. Then take our 2-minute assessment to plot your own route to success.
ILLUSTRATIONS BY IBRAHIM RAYINTAKATH
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Introduction

How can our company successfully
adopt AI?

This question is at the forefront of every boardroom discussion today. Forward-thinking sales leaders clearly see AI’s potential — automating busywork to free sellers to focus on what AI can’t replace: relationship-driven, consultative selling.

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Based on a new study from the global research firm Dynata, 71% of sellers and 87% of sales leaders are already on board or preparing to start using AI, both encouraging stats. But in the field there’s a delta between the early experimentation and long-term potential of deeply AI-enabled sales motions.
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David's travel-weary notebook is still his primary source of customer conversation insight. Elena still dedicates an “admin day” to a mountain of meeting follow-ups. And then there’s Marcus, patiently awaiting pitch feedback for weeks while his manager is buried in deal forecasting.


Too often, the sales frontline feels less like an AI Renaissance and more like a throwback to the floppy disk era.

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Because when generic AI tools are simply overlaid onto deeply ingrained selling practices, old habits, predictably, tend to prevail. Inconsistent seller adoption makes it hard for revenue leaders to prove ROI, and momentum is quickly lost. No wonder only 16% of recent AI initiatives have scaled enterprise-wide.
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And yet, there are outliers — high-performing sales orgs who are making AI work where others have failed. Global companies like GF, Bruker and Barco, are investing in intelligent systems, purpose-built to solve the problems that slow sellers down. They’re focussed on reducing friction, not adding to it.


That's why we engineered the AI-Enabled Sales Org Assessment — to help you understand where your sales org is on the journey to successful AI implementation and how to move forward.

But first
SECTION 1
What is successful AI-enabled sales?
The sales orgs turning seller potential into predictable performance with AI aren't just equipping sellers with general productivity tools like ChatGPT, Google Gemini, or Microsoft Copilot.

While the large language models behind these AI chat experiences are incredibly powerful, sellers in the field need more tailored, workflow-specific assistance. To transform productivity, sellers need an AI that understands the products they sell, the content that engages buyers, the milestones that close deals, and can grow smarter from every customer interaction.


To build such an intelligent system and leverage it to maximize revenue, you need the right technology and strong seller buy-in. Here are the four essential principles to make sure your approach to AI-enabled sales accomplishes both to make a measurable impact:
SECTION 1
What is successful AI-enabled sales?
The revenue orgs turning seller potential into predictable performance with AI aren't just equipping sellers with general productivity tools like ChatGPT, Google Gemini, or Microsoft Copilot.
#1 Prioritize value over volume

Sales is a numbers game, so the temptation for sellers using AI is to focus on increasing quantity — more communication, with more customers, more often.

For example, David assumes he’s increasing his chances of closing by taking spray-and-pray tactics to a whole new level with AI. But when David and all his competitors take the same approach, inundated buyers switch off completely.

Instead, deals in the AI era will continue to hinge on a seller’s ability to demonstrate value and broker belief. The sellers that win will use AI to go deeper, not wider: strengthening bonds with the right buyers, not just more of them. With personalized content that builds trust. Just-in-time communication that drives urgency. Smarter meetings that turn momentum into revenue.

#2 Fuel AI with your unique business context
3.2 MONTHS
Average amount of time it takes to get a seller up to speed on your products, sales methodology, and messaging

In order for AI to help your sellers show differentiated value, it has to understand what makes your business distinct. On average it takes 3.2 months to get a seller up to speed on your products, sales methodology, and messaging. This can lengthen in companies with large, complex, or highly regulated product and service portfolios.

To optimize the performance of every seller in your ranks, all that knowledge it takes a human months to learn is the minimum context AI needs to add meaningful value. Intelligent systems must be able to draw on brand-approved content plus seller behaviors, buyer engagement data, and deal insights across your entire sales team to effectively guide them to take the next deal-winning action.

To put a fine point on this, Elena is no more efficient if she has to manually prompt this context every time she requests AI’s assistance.

#3 Augment, don’t replace, human skills

Your best sellers possess intuition, empathy, and ability to build trust — qualities AI can’t replicate. Many will embrace AI to eliminate busywork to develop and use these valuable skills more often. 


Naturally, some sellers may feel uncomfortable with this change. Take Marcus, who still struggles with the CRM introduced to him 20 years ago. Even though 70% of his week is lost to mundane administrative work, for him, automating tasks and guiding decisions with AI is an advanced skillset. But by implementing the right intelligent system, sellers don’t have to become expert prompt engineers to make AI work for them. 


When AI is seamlessly woven into existing workflows, involves human input at the right moment, and clearly explains its logic and sources, sellers like Marcus can quickly realize how it helps them close more and ultimately earn more.

#4 Align your revenue team for collective success

While sellers in the field might be the face and voice of your business, it takes collaboration across sales, marketing and enablement to make sure they show up in the right place, with the right message, at the right time.


By helping David, Elena, and Marcus capture and structure insights from customer conversations when they’re on the move — on factory floors, in hospital corridors, on construction sites — AI gives sales, marketing, and enablement leaders back at headquarters new visibility into the field.

Knowing how content is used, where coaching can move the needle, and how training is adopted makes it possible to scale what works. With intel at the individual and team level, teams can confidently roll out winning behaviors across the entire sales org.

CONCLUSION
When the pressure to gain a competitive edge is high, it’s tempting for revenue leaders to sacrifice long-term success for short-term speed, investing in AI-based point solutions or retrofitting legacy tools with bolt-on AI features. But these quick fixes create surface-level gains, not system-level transformation. Making the wrong technology investments can be costly, but doing nothing is the biggest competitive liability of all.
SECTION 2
Introducing the 
AI-Enabled Sales Org Assessment
Building an effective AI-enabled sales program can be a daunting task. To help, our AI-Enabled Sales Org Assessment considers the state of two key dimensions and evaluates your sales org's AI maturity against four states of progress.

X axis
Technology sophistication
Transforming seller productivity with AI demands scalable, secure technology that can be trusted to automate tasks based on a deep understanding of your business.
Y axis
Human adoption
From senior leadership to field sellers, it takes human effort and enthusiasm to realize the full potential of AI.
To understand how to advance to the next level of your revenue team’s AI integration and impact, take our AI-Enabled Sales Org Assessment now.
Your results
THE SPECTATOR
THE BELIEVER
The OPERATOR
THE OPTIMIZER
Low Human Adoption + Low Technology Sophistication
Your organization has largely stayed on the sidelines of AI. Change feels risky, legacy systems seem too complex to modernize, and leadership may not see a clear path to value. Meanwhile, sellers spend most of their week on manual admin, with less and less time for customer conversations. Burnout rises, expertise walks out the door, and outdated processes become the norm.
What a “business as usual” future looks like
The urgency here is paramount. Competitors already leveraging AI will keep pulling ahead — faster workflows, more personalized outreach, sharper buyer insights. Inaction isn’t neutral; it’s an accelerating disadvantage that erodes market share, raises costs, and makes it harder to meet rising customer expectations.
Five recommendations build your strategic and technology foundations
Map current usage and workflow gaps
Identify clear use cases where AI can reduce friction and free up seller time. It's critical to begin with these real scenarios to secure the necessary organizational buy-in for a meaningful AI investment.

Speak directly with sellers, asking them where they experience friction in their daily workflows. Building trust with sellers and giving them a voice in how and why they use AI is far more likely to drive lasting adoption.
Prioritize integrated, scalable solutions
Evaluate comprehensive AI solutions that seamlessly integrate with your existing tech stack and sales data sources, particularly your CRM. 94% of sales leaders recognize the value of using data to prioritize seller activity, but without the right connectivity, leveraging it effectively remains a huge challenge. Focusing on evaluating technology that can elevate your existing tech stack rather than adding more complexity is a critical consideration.

This approach allows you to avoid falling into the trap of implementing isolated point solutions that operate only on context provided through manual prompting.
Pilot for proven ROI on core workflows
Before fully implementing a comprehensive AI-enabled sales platform, launching a targeted pilot program can provide clear evidence of potential to persuade more reluctant stakeholders. Pilots focused on improving essential sales workflows, such as access to sales content and seller training can be tied to core business metrics like win rates, sales cycle velocity, or time saved on administrative tasks.

The concrete proof of value generated from these pilots will be crucial for justifying broader investment and proving the potential of AI embedded across seller workflows.
Address data and governance concerns proactively
A key blocker to broader investment in AI solutions beyond generic tools like ChatGPT, Google Gemini, or Microsoft Copilot is security concerns. Many leaders are worried about cybersecurity (55%), regulatory compliance (36%), and personal privacy (28%) when it comes to AI.

When building a single intelligent system, it's vital to choose secure, reputable vendors with a proven enterprise security track record. Solutions purpose-built for AI-enabled sales, particularly for enterprise businesses, should have robust protections to mitigate any critical procurement criteria.
Cultivate internal champions
Identify a few open-minded sellers or managers willing to participate in your pilot and become internal AI advocates. Create incentives and an internal comms channel for them to share their AI discoveries and illustrate how AI makes their jobs easier. This builds grassroots momentum, addresses any fear of change by showing peer success. Additionally, educate these champions and other sellers on the limitations of general AI tools compared to more comprehensive solutions purpose-built for your company’s specific needs.

Emphasize how these integrated tools unlock greater efficiencies, provide company-specific context, and minimize manual prompting. While you gather quantitative data from pilot programs to prove potential impact, a small amount of internal advocacy can be a key catalyst for border change.
High Human Adoption + Low Technology Sophistication
Your sellers are excited about AI and already using it to speed up repetitive tasks. That enthusiasm is a real competitive advantage. But without a centralized strategy, it’s fragile. Generic tools create small, localized wins, but unmanaged data, security risks, and lack of scale make it hard to prove impact.
What a “business as usual” future looks like
Without more strategic investment, your AI-enabled sales efforts will remain a collection of isolated experiments, failing to scale impact. Seller enthusiasm turns into frustration, momentum stalls, and competitors with smarter systems pull ahead.
Five recommendations to move from enthusiasm to scaled impact
Map current usage and workflow gaps
Channel your team's enthusiasm into a unified strategy. Speak directly with sellers, asking them where they currently use AI and where they continue to experience friction in their daily workflows. Translate use case insights into an executive-level business case to guide technology investment.
Prioritize integrated, scalable solutions
Evaluate AI solutions that seamlessly integrate with your existing tech stack and sales data sources, particularly your CRM. An impressive 94% of sales leaders recognize the value of using data to prioritize seller activity, but without the right connectivity, leveraging data remains a huge challenge.

With the right integrations, AI has a deeper understanding of your business and deal context, allowing it to guide sellers with smart recommendations and save them time by automating multi-step tasks.
Pilot for proven ROI on core workflows
Run a targeted pilot focused on improving essential sales workflows, such as immediate access to sales content or AI-feedback on pitch practice, using a single platform. Anchor pilots to core business KPIs like win rates, sales velocity, or time saved on repetitive tasks. Use proof points to justify broader investment and rollout.
Address data and governance concerns proactively
Despite enthusiasm, a key blocker to broader investment in AI solutions is security concerns. Many leaders are worried about cybersecurity (55%), regulatory compliance (36%), and personal privacy (28%) risks. Choose a secure, reputable vendor with a proven enterprise security track record and robust protections to mitigate risk.
Cultivate internal champions
Identify a few open-minded sellers or managers willing to become advocates for a more meaningful technology investment. Ask them to share ideas about the measurable efficiency gains they could achieve with specific capabilities. This builds grassroots momentum and proves seller adoption commitment to senior leadership.

Additionally, educate these champions and other sellers on the limitations and risks of generic AI tools compared to solutions purpose-built for your company’s specific needs. Emphasize how a single intelligent system will unlock greater efficiencies, draw on company-specific context, and minimize manual prompting.
JUMP BACK TO RESULTS
Low Human Adoption + High Technology Sophistication
You’ve made major investments in advanced AI tools, but sellers aren’t using them. Instead, they stick to manual processes because existing solutions feel too complex, too generic, or too disconnected from their workflows. The result: low adoption, mistrust of outputs, and wasted potential.
What a “business as usual” future looks like
Stalled momentum can be particularly painful, representing significant wasted investment. The technology you’ve invested in might be capable, but it's not usable or trusted in the context of your sellers' daily lives in the field.

The urgency here is paramount: your AI investment is currently a sunk cost, not a competitive advantage. Sellers will remain inefficient, burdened by administrative tasks that AI should be handling. This situation breeds frustration and erodes trust in future tech initiatives. Without a strategic shift, you'll continue to lose ground to competitors who effectively leverage their AI investments, impacting your market share and overall revenue.
Five recommendations to rebuild trust and drive adoption
Map current usage and workflow gaps
Pinpoint the reasons for low adoption by speaking directly with sellers. Ask them where they currently use AI and where they continue to experience friction in their daily workflows. Feedback will provide crucial insights into use-case specificity that will identify the issues blocking adoption.
Prioritize integrated, scalable solutions
Although many AI solutions are intended to free sellers from busywork, point solution sprawl can create new friction, particularly for sellers on the move in the field. A single purpose-built platform is not only easier for sellers to navigate and use, it can also grow smarter with every customer interaction.

Choose a partner who specializes in working with similar-sized businesses to benefit from innovation that matters most to your sellers and company goals.
Build for real sales scenarios
The majority of AI sales tools are built for inside selling. If you rely on hybrid or field sellers, prioritize solutions that work on the move and offline — adoption depends on fit with real-world workflows.
Anchor AI to core business metrics
Another common blocker to AI tool adoption is a lack of advocacy from senior leadership, often due to skepticism or a lack of awareness of how they can play a role in promoting its potential. To make advocacy easier for senior leaders, anchor your AI strategy to measurable business metrics like win rates, sales cycle velocity, or quota attainment.

Ensure the solutions you're working with also leverage AI to surface deep, actionable insights into what content, seller training, and workflows are most impactful so your entire sales org can confidently focus on scaling what works. Evaluate vendors who build solutions specifically for your sellers’ use cases and can offer their expertise to map performance metrics rather than providing the technology alone.
Cultivate internal champions and showcase wins
Identify a few open-minded individual sellers, sales managers, or leaders from marketing and enablement teams willing to become advocates. Create incentives and an internal comms channel for them to share their AI discoveries and efficiency gains. For example, illustrate how insights from how sellers engage buyers can inform marketing campaigns, product development, or customer success initiatives.

This approach builds grassroots momentum, addresses fear of change by showing peer success, and provides relatable examples for wider adoption, illustrating how AI makes their jobs easier, not harder.
JUMP BACK TO RESULTS
High Human Adoption + High Technology Sophistication
Congratulations! You are well ahead of the curve when it comes to AI-enabled sales. For your business, AI is not just a set of fragmented tools; it's seamlessly integrated into your end-to-end sales process. Sellers are proficient in its use, efficiency is up, collaboration is stronger, and the results are translating directly into predictable revenue.
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Your organization benefits from a comprehensive AI foundation that connects data sources and automates complex workflows. You’ve cleared the typical hurdles — leadership buy-in, governance, and adoption — and built a culture that embraces innovation.
What a “business as usual” future looks like
Even leaders risk losing ground. The AI market is evolving fast, and fragmented point solutions can create long-term instability. As vendors crowd the space with narrow use cases, you could overwhelm sellers with tools that don’t align with your goals, eroding trust and adoption. Staying ahead means continuously future-proofing your advantage.
Five recommendations sustaining excellence and drive further innovation
Future-proof impact
Relying on a patchwork of AI point solutions introduces significant risk. Choose a single, enterprise-grade system that grows smarter with every seller interaction and delivers stability over quick fixes.

This approach isn't just easier for sellers to use day-to-day; it also gives AI the comprehensive exposure to your seller workflows it needs to grow smarter with every customer interaction.
Build for real sales scenarios
The majority of AI sales tools are built for inside selling. If you rely on hybrid or field sellers, prioritize solutions that work on the move and offline — adoption depends on fit with real-world workflows.
Anchor AI to core business metrics
Focus your AI strategy on impacting measurable business metrics like win rates, sales cycle velocity, or quota attainment. Ensure the solutions you invest in also leverage AI to proactively surface deep, actionable insights into what content, seller training, and workflows are most impactful. This helps your revenue team focus on scaling what works. Select vendors who can offer their expertise in tracking performance outcomes.
Incentivize sharing wins
Build incentives and internal comms channels for recognition so sellers feel comfortable sharing their AI discoveries and efficiency gains. This helps maintain a healthy, pro-innovation culture, reinforcing how AI can make sellers jobs easier. Encourage sales, marketing and enablement leaders to gather feedback and crowdsource ideas for improvement directly from their teams to unlock new opportunities to do more with less.
Expanding to continuous learning
Many believe that AI-enabled sales is just about personalizing and automating customer communications. But AI can also be used to help sellers continually learn and gain new skills beyond onboarding. With the right intelligent system, it should also be possible to identify skill gaps across the team based on aggregated performance data and assign learning paths to drive continuous improvement.

From instant feedback on pitches to interactive courses based on brand-approved content, AI can help scale the level of different continuous learning experiences available to sellers. This embodies the principle of augmentation, not replacement, empowering sellers to become expert consultants.
JUMP BACK TO RESULTS
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