Every sales and marketing leader is talking about AI. But what's actually happening on the ground?

To find out, we joined forces with UserGems. We didn't want another "AI is amazing" report. We wanted the truth. So, using Wynter, we surveyed 100 B2B SaaS leaders at companies with $50M+ in revenue.

What we found: 93% of teams are still struggling to see real value from their AI investments.

The 7% who are seeing results are thinking about AI differently than everyone else.

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What percentage of B2B teams see ROI from AI? Only 7% report clear returns

When we asked leaders to describe their team's current success level with AI adoption, the results painted a sobering picture:

• 7% report measurable ROI and clear value
• 28% see moderate success with growing returns
• 20% achieve limited success in specific use cases
• 45% experience limited success with uncertain value

Nearly half of teams are stuck investing time and resources without clear returns. They're running pilots, testing tools, and waiting for the breakthrough that hasn't come.

But dig deeper into what the successful 7% are doing, and clear patterns emerge.

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How to start small with AI: Why specific use cases drive 7% higher ROI

The teams seeing real ROI didn't try to "AI everything." They picked narrow, well-defined use cases where the path to value was clear.

"Teams need to make a point to use it. It's very helpful to create a learning journey to help people not only learn what and why, but also how to implement best practices and give people the opportunity, time and space to practice."

The successful teams typically start with:

• Tasks where errors are low-risk
• Processes with measurable outcomes
• Workflows that are already well-documented
• Areas where 80% accuracy is good enough

"If your team is hesitant to adopt and implement AI, start small with redundant, manual tasks. Not everything needs to be big and splashy right away."

This constraint-based approach does two things: it makes success measurable and it builds team confidence.

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Why does AI implementation fail? 25% blame bad data and poor prompts

A quarter of AI implementation failures trace back to two fundamental issues: messy data and poor prompts. The 7% understand that AI is only as good as its inputs.

"Data quality is important for AI to work properly."

"CRM data, including validations and flows, needs to be structured in order for AI to deliver productivity improvements."

Teams getting ROI share these practices:

• Regular CRM hygiene sprints before AI implementation
• Standardized data entry protocols
• Clear naming conventions and tagging systems
• Documented prompts that consistently deliver results

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One Senior Email Marketing Manager summed it up perfectly:

"How good your outputs are is 100% dependent on how good your inputs are."

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Don't rush training

Perhaps the biggest differentiator between the 7% and everyone else is mindset. Successful teams don't treat AI as plug-and-play automation. They see it as a team member that needs onboarding, training, and ongoing coaching.

"The set-up and training of an AI tool is key."

"It takes time to train a system to your company's needs and goals. You have to be invested for the long term and not expect results overnight."

This means:

• Dedicated time for learning and experimentation
• Regular optimization of prompts and workflows
• Human review built into every process
• Patience through the "training period"

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Teams that rushed implementation consistently reported frustration. Those that invested in proper setup saw compound returns.

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88% of B2B teams require human oversight

When we asked teams how they envision AI fitting into their workflows, the responses were remarkably consistent. Even for the most AI-suitable tasks, the majority want human oversight:

• AI search and optimization: 59% want human oversight
• Outbound personalization: 84% require human touches
• Lead scoring: 55% insist on human validation
• Content creation: 88% see it as human-AI collaboration
• Forecasting: 72% want AI to assist, not decide

The pattern is clear: the 7% use AI as a co-pilot, not an autopilot. They've learned that AI excels at handling repetitive tasks and surfacing insights, but human judgment remains critical for context, creativity, and relationship building.

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What should never be automated in B2B sales?  

When we asked what should never be fully automated, successful teams were protective of four key areas:

1. Creative work and brand voice (29%): "AI content all sounds the same" noted a Senior Marketing Manager. "Our differentiation comes from human creativity."
2. Customer communication (21%): Teams recognize that one tone-deaf AI response can undo months of relationship building.
3. Relationship building (13%): "AI can't read a room" as one VP of Field Marketing put it. Real connections happen human-to-human.
4. Strategic thinking (12%): While AI can spot patterns in data, it can't understand organizational context, market dynamics, or the subtle factors that drive real decisions.

The 7% understand that competitive advantage comes from using AI to handle the predictable so humans can focus on what matters: building relationships, creating differentiated content, and making strategic decisions.

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How to get ROI from AI in B2B: A step-by-step playbook

Based on our research, here's how to join the 7% seeing real ROI:

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Start with the grunt work

Identify one specific, repetitive task that drains your team's time. Common winners include:

• Meeting note transcription
• Initial prospect research
• Email subject line variations
• Data entry and enrichment
• First draft creation

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Set realistic expectations

Remember, success takes time and it doesn't always go well on the first attempt.

"Trust the process and realize that you likely will not see results right away. There's trial and error with AI but if you put the time and effort, most companies will reap the benefits."

Build trust through transparency

Address team concerns head-on. Position AI as enhancing their work, not replacing their value. Give them time to learn, space to experiment, and celebrate early wins.

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Measure what matters

Track specific metrics from day one:

• Time saved on routine tasks
• Accuracy rates for AI outputs
• Team adoption and usage rates
• Quality of human work post-AI implementation

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Stay human-first

The most successful teams never forget that B2B sales is fundamentally about relationships. Use AI to eliminate friction and create space for relationship building and human-to-human interactions.

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The bottom line

The 7% getting real ROI from AI aren't necessarily smarter or better resourced than everyone else. They've simply figured out that AI works best when it makes humans more effective, not when it tries to replace them.

As one Global Director of Sales Enablement told us:

"It's very early days. The trust we will have in AI to be more autonomous is coming but it's not fully here yet."

Until that day comes, the winning formula remains clear: AI for efficiency, humans for differentiation. Start small, fix your data, keep humans in control, and protect what makes you unique.

The future of B2B isn't about choosing between human or machine. It's about combining both in ways that amplify what each does best.