The Promise vs. The Practice
AI has officially arrived in sales. It’s writing emails, summarizing calls, generating battlecards, and building business cases – all in seconds. It promises efficiency, consistency, and scale.
But here’s the catch: AI still doesn’t know how to sell.
At our NYC breakfast event, we sat down with over 30 sales and value leaders to unpack how AI is really being used in the field. And while everyone agreed it’s saving time, most admitted it’s not helping reps do the one thing that actually wins deals – deliver a tailored, credible, and evolving “Why Buy” story.
That’s the missing piece in today’s AI tooling. Just like traditional frameworks: MEDDIC, Challenger, Force Management, these tools are only as good as the seller’s ability to contextualise. To take raw inputs and translate them into insight. To craft a message that resonates not in theory, but in the moment.
This blog unpacks where AI is genuinely helping sales teams today and why that’s not enough to solve what’s really broken in B2B selling.
Where AI Is Adding Value
Speeding Up Discovery Prep
AI is helping sales reps gather surface-level insight faster than ever.
Tools like Gong and ChatGPT are being used to:
- Pull company background and funding history
- Generate discovery question templates
- Flag common pain points based on persona or industry
This is a win for efficiency. But the question isn’t how quickly a rep can prepare – it’s how deeply they can connect.
‘68% of sales reps say they struggle to balance productivity with delivering meaningful customer interactions.’ – Gartner Future of Sales 2025 Report
And that’s where the current AI stack falls short. While it equips sellers with inputs, it doesn’t help them translate that input into a credible, prospect-specific “Why Buy” story. Instead of guiding reps toward relevance, most AI tools leave them with generic prep packs and templated talk tracks – expecting them to do the synthesis themselves.
So yes, sellers are walking into meetings faster. But they’re still walking in with the same challenge: how do I make this valuable to this person, right now?
Automating Admin Workflows
“I’m not stuck formatting MEDDPICC notes or writing up summaries anymore.”
AI has become a reliable assistant when it comes to sales admin. Reps are using it to:
- Auto-generate post-call summaries
- Fill out CRM fields with qualification data
- Structure MEDDPICC notes based on conversation transcripts
This is creating welcome efficiencies, reducing time spent on documentation and increasing consistency in data capture across teams.
But let’s be clear: automation is solving the formatting problem, not the thinking problem.
Sellers still need to decide what matters, connect it back to the value proposition, and evolve the story as the deal progresses. And that’s the part that’s still manual, still inconsistent, and still heavily dependent on rep experience.
Without context, this automation creates a clean system – but a shallow one. Data gets captured, but insight doesn’t get translated. Momentum stalls.
So while AI is cleaning up the process, it’s not yet empowering reps to become better storytellers. And in B2B selling, that’s what actually moves the deal forward.
Generating Content at Scale
“We’re using GPTs to draft first-pass emails and recap notes. It’s helpful… to a point.”
There’s no question: AI has made it easier to generate content. Reps are using it to:
- Write outbound prospecting emails
- Summarize calls into follow-ups
- Create first-draft slides and proposal content
This has unlocked volume. Messages go out faster. Templates are standardized. Follow-ups don’t fall through the cracks. But scale without context is just noise at speed.
When AI-generated content isn’t grounded in your value proposition, aligned to persona-specific pain, or tailored to the buyer’s stage, it becomes a liability. What looks polished can feel hollow. What sounds “on-brand” can still be off-message.
47% of go-to-market leaders cite “accuracy of output” as their top concern with AI tools. – Databox x Jasper.ai Report
The deeper problem? Reps start trusting the content too much. They send without editing. Default to generic outputs. And slowly disengage from the value story altogether.
So yes, content is being created at scale. But the real question is: is it content that actually converts?
What's Getting in the Way
Disconnected Insights
“AI gives me the what. But I still have to figure out the why and the how.”
AI is great at summarising what happened. It can pull call transcripts, extract MEDDPICC criteria, flag keywords. But not turn them into a narrative.
“Right now, AI can summarize. What we need is something that helps us sell.”
Sales reps are still responsible for:
- Understanding the prospect’s real motivation
- Translating deal signals into outcomes
- Aligning insights to strategic priorities
AI gives us more data – but not more clarity. And that means reps are still stuck doing the cognitive heavy lifting: stitching together a narrative that resonates, moves the deal forward, and supports internal alignment.
Until AI learns how to sell – not just summarize – it will remain a support tool, not a strategic one
Lack of Internal Context
“The AI doesn’t know what we know.”
Most AI tools operate in a vacuum. They can pull public data, market signals, and news alerts, but they lack access to the knowledge that actually differentiates your company:
- Win stories from similar customers
- Internal benchmarks and outcomes
- Persona-specific pain points and messaging
- Discovery frameworks and value drivers
‘62% of sales reps say their AI tools lack access to internal enablement content.’
– Gartner Future of Sales 2025 Report
Without this embedded context, AI-generated content sounds polished but falls flat. It doesn’t speak in your voice. It doesn’t align to your sales methodology. And most importantly, it doesn’t build the value narrative that helps your buyer justify change.
The result? Reps receive content that’s technically correct, but strategically useless.
Until AI systems are deeply connected to the internal frameworks that define how you sell, they’ll keep producing content that’s generic, repetitive, and disconnected from what actually wins deals.
Prompting Skill Gaps
“Our team doesn’t know how to prompt well, so we get mixed results.”
AI tools are only as good as the inputs they’re given. And that’s the problem: most sellers aren’t prompt engineers. They don’t know the difference between a general input and a strategic one. As a result, reps often:
- Rely on basic or vague prompts
- Avoid using AI altogether for critical tasks
- Blindly trust outputs, even when they’re off-message
The result? A patchwork of messaging quality across the team. One rep sends a strong, contextual message. Another sends a generic, irrelevant one. Neither knows if they’re right.
Inconsistent input creates inconsistent output and that’s a risk when you’re trying to build a repeatable, scalable sales motion.
AI shouldn’t require reps to be master prompters. It should be embedded with your best practice messaging, your persona-based insights, and your value framework – so that every rep, regardless of experience, can show up like your best rep.
Until then, the burden remains on the seller to close the gap between the prompt… and the point.
Superficial Personalization
“It looked like it was for me, but it clearly wasn’t.”
AI tools have made it easier than ever to insert names, titles, company facts and call it personalization. But B2B buyers are smarter than that. They can spot the difference between a message that’s for them and one that’s about them.
This is where many AI-powered sales efforts fall short: They personalise the data, but not the message.
‘Only 15% of B2B buyers say vendor outreach feels genuinely personalized.’
– Gartner Future of Sales 2025 Report
When outreach looks personalized but lacks relevance, it doesn’t just underwhelm, it erodes trust. Buyers feel like they’re being processed, not understood. And here’s the deeper issue: without access to your internal frameworks, your persona-based value props, customer stories, and segment pain points – AI finds it hard to move beyond surface-level customisation.
So reps send messages that look polished, but feel off. The tone is right. The structure’s solid. But the message? Forgettable. Until AI is connected to the real insight behind what makes your product valuable, and to whom, personalization will remain just that: superficial.
Where Does That Leave Us?
The takeaway from our NYC event was clear: AI is accelerating execution – but it’s not enabling better selling.
It’s helping with surface-level tasks: note-taking, email writing, research, and CRM hygiene. It’s saving time. It’s driving consistency. But it’s not helping reps:
- Understand the prospect’s motivation
- Tailor messaging to the moment
- Build and evolve a credible “Why Buy” story over time
That’s still on the seller. And it’s still painfully manual. The problem isn’t the tools themselves, it’s the fact that they operate in isolation. They don’t have access to your internal knowledge. They don’t understand the personas you sell to. And they’re not embedded in the frameworks that drive your sales process.
So what you get is activity without alignment. Scale without story. Volume without value.
“We’re not anti-AI. We just want AI that understands how we sell.”
