The 5 gaps AI exposes in commercial teams (and how to spot yours)
The short answer
AI exposes five gaps in commercial teams: the Skills Gap (incomplete briefs and missing human judgement), the Oversight Gap (nobody holding a complete view across teams), the Scaling Trap (more activity widening the holes between functions), Thin Thinking (polished but generic work) and the Metrics Loop (KPIs misaligned to real value). Most businesses have two or three active at once.
Key takeaways
- 60% of companies report minimal revenue and cost gains from AI, and only 5% are generating substantial value at scale (BCG, 2025). This is sometimes referred to as the productivity J-curve (Brynjolfsson, Rock and Syverson, 2021).
- The five gaps are structural and emerge from everything that sits around the technology. They often feel like people problems at first glance, which is why they're easy to misdiagnose.
- Each gap has a practical first step, and you don't need a new tool for any of them.
When a commercial team isn't performing the way you're expecting, it usually gets treated as a people problem. In most growing businesses I work with, it usually turns out to be a systems problem, and it shows up in five common ways.
It often starts with a sense of something not working. The founder or commercial director knows the effort going in isn't matching what's coming back. The pipeline is inconsistent, marketing and sales aren't quite aligned, and when a quarter dips, the debrief produces reasons rather than solutions. AI accelerates this, because it works at scale, and that includes the parts of the process that weren't working before.
These are the five challenges I see most often, how to spot each one, and where to start. For three of them I've included a free toolkit you can use as it is or customise for your team.
The Skills Gap
The capability of the users when it comes to real-life application, and the tool gets the blame.
The Oversight Gap
No one connects the work or the system across the functions, so insight or data falls in the gaps between the sales, marketing and BD teams.
The Scaling Trap
When the net grows, the holes get larger. Scale results in more, not necessarily better.
Thin Thinking
Output looks polished but starts to sound like it could have been produced by any of your competitors, with little real insight that differentiates and adds value for your specific customer.
The Metrics Loop
The measures and KPIs don't line up to the work that makes the difference and creates the value. Insights don't flow across the system, whether that's from marketing to BD or from sales to delivery teams.
The five gaps AI exposes in commercial teams.
The Skills Gap
The thinking that inputs into the brief is missing, or the human judgement layer gets lost.
AI has made knowledge accessible to everyone, and anyone can now produce something that looks pretty polished in less time than it takes to make a coffee. The gap was probably always there, in how sharply someone can brief a problem and judge the answer that comes back. It compounds where there are different sales approaches, transactional versus consultative, where deeper knowledge creates better partnerships with customers. AI exposes this, because a generic brief now produces generic-looking output, and it turns customers off, with messages getting lost in the noise of more outreach.
It shows up differently depending on where you sit in the pipeline. A rep gives the AI a job title and company name instead of the customer's real, live situation and uses whatever is generated verbatim. A manager reviews what lands in their inbox but can't always tell polished from good, or doesn't value the time it might take to coach on what would be better and how to get there. An owner who has hired someone senior to run commercial will focus on the pipeline and the targets, and doesn't adjust the questions they ask to help the team learn how to use AI well. I explore the demands on managers in more detail in how to lead a team that works with AI agents.
How to spot it:
- Proposals and outreach across different accounts start to sound the same.
- People can't explain why the AI suggested what it did, or what's missing.
- The best work is produced by the same two or three people.
Where to start: Ask people to write down what they know specifically about the customer and their problems before they write the prompt, and to read every output twice: once for accuracy and once for whether there is real value in what's been generated. I've worked with a team that built their own solutions to help bridge these gaps with strategic sales reports, and I'd encourage using these in coaching situations to help develop the human judgement capability in teams.
Skills Gap toolkit: three self-serve tools
One tool each for your individual contributors, your managers and the owner or commercial leader, with the checks, challenge prompts and coaching questions you can start using. Adapt them to your team. 3 pages.
Get the PDF, free
The Oversight Gap
No one holds the overall view across functions, so the gaps between sales, marketing and BD get replicated by the technology.
Each team can usually describe its own part of the process well. What's missing is someone who can see across all of it and who owns the points where work passes from one team to the next. A lead gets dropped when marketing hands it over to sales, or a promise made during the sale never reaches the delivery team.
There's a quality challenge to this too. Most managers learned to lead by doing the job, so they know what good looks like in their own work. Not only do they have to develop people management skills, there's now the additional need to manage and support teams using AI.
How to spot it:
- Nobody can say who is responsible for the handover between two teams.
- Each team has its own measures, which can be misaligned. This carries through to the goals that direct agentic work.
- Work gets approved because it looks good, but it's missing the skill and input of seasoned experts. I see this often with marketing and BD messaging, for example, that looks great on the surface but focuses on product features rather than customer problems.
Where to start: Map one workflow across your teams, identifying every customer touchpoint, every input and output relating to that touchpoint, and who is involved, both internally and within your customer (use RACI), and see what's missing. This is some of the most illuminating work I do with teams, and I share three free tools to help you get started in how to map your sales, marketing and BD workflow.
The Scaling Trap
When the net grows, the holes get larger.
At the point where a business shifts from fast and flat to structured and standardised, the instinct is usually to do more: more outreach, more leads, more campaigns, more activity. Then, because you need more capacity to do all that, you recruit more people. It feels like progress because everyone is busier, until you look at what's actually landing.
The other instinct is to fix growing pains with more process, such as another approval, another template or another meeting. On a visit to Amazon's headquarters in Seattle, I heard how an organisation at that scale works against this: small teams working the same problem from different angles, instead of more documentation. The framework shared on that visit came from Mark Schwartz, who uses three cuts to reduce bureaucracy: the Monkey (provoke a process by skipping a step and seeing what breaks), the Razor (strip out anything that isn't needed) and the Sumo Wrestler (use an existing rule or template instead of building a new one) (Schwartz, The (Delicate) Art of Bureaucracy, 2020).
How to spot it:
- Headcount and activity have gone up, but sales are flat.
- Your team or the process is being slowed down by another meeting, template or sign-off.
- Decisions are made several layers away from the customer, creating disconnect and distance between leaders and customers.
Where to start: Pick one process, template or recurring meeting that feels more burdensome than it should, and pass it through the three cuts mentioned above before you add anything new into the mix.
Scaling Trap toolkit: two self-serve tools
The Wider Net Problem walks you through the three cuts on one process, and Thinning Connections helps you check where your handovers have already stretched to the point of breaking. A starting point that you can adapt to your own business. 2 pages.
Get the PDF, free
From experience
Building my own agentic teams, I've gone back to what I've done many times before: building teams from scratch, developing the sales and marketing engine that fuels growth, putting processes in place where none existed, and setting up the information to track performance and attribution. Doing all of that inside an AI build has helped me formalise what I've been applying for years, and the same patterns show up every time.
Thin Thinking
Output looks polished but misses what's really valuable for the buyer.
AI can draft a well-structured, professional proposal in twenty minutes that covers all the bases, and everyone feels good about it. So it's frustrating when it doesn't land.
Often nobody read it twice before it went out, or asked whether the thinking underneath was sharp or just looked it on the surface. Speed and volume create the illusion of depth, and no-one checks quality or content because the output gives the impression of quality. What's missing is the wisdom or insight behind it. Does this reflect what we actually know about this customer? Does it describe their problem (emotional and physical, professional and personal) in words that will resonate? What would they need to see or hear to say yes? AI can raise the floor on how the work looks, but it's the people who raise the floor on the thinking.
How to spot it:
- Proposals look great but they still don't convert.
- Outreach could be sent to any company in the sector, by any other competitor in the sector.
- Nobody can identify the one insight a piece of work is built on.
Where to start: Before anyone writes outreach or a proposal, ask them to find one specific, evidenced insight about that account, then build the message around it. A lot of the theory, whether that's sales, marketing or any other, still stands because it was solid in the first place. Don't assume AI research will surface the same theory or best practice that your subject matter experts know, from experience, to be true.
Thin Thinking toolkit: two self-serve tools
A prompt that turns what you know about an account into one genuine insight, and a simple structure (Problem, Agitate, Call to action) for building an email around it. Adapt the prompt and structure to your own sales process. 2 pages.
Get the PDF, free
The Metrics Loop
The value measures you've identified aren't aligned to the value of the work that makes the difference.
When AI makes it easy to do more, the easiest thing to report is how much more: emails sent, posts published, licences used. The dashboard looks healthy, spend on tools keeps rising, and nobody can connect it to improving conversion.
It's a wider pattern. BCG surveyed 1,250 senior executives and found that 60% of companies are reporting minimal revenue and cost gains from AI, while only 5% are generating substantial value at scale (BCG, 2025). I wrote about what happens when the system rewards volume in why teams stop using the AI tools you rolled out.
How to spot it:
- Reporting focuses on activity and tool usage.
- Nobody can state with confidence whether AI-assisted work converts better than before.
- Pipeline reports take days to rebuild and are out of date the moment they are completed.
Where to start: Pick one quality measure, such as reply rate, meetings booked or proposal win rate, and track it for AI-assisted work against how things were before.
How much value companies are getting from AI
Share of companies in each group, from a survey of 1,250 senior executives
A quick self-check
Score each statement for your team as it is today: not yet, sometimes, or yes, consistently.
Where to start
Most businesses have two or three of these gaps active at once. The most useful work is finding out which one is costing you the most, and starting there. If you'd like a fuller picture, the Commercial Engine Scorecard takes about three minutes and shows where your commercial system is leaking revenue and opportunity. And if you'd rather talk it through, book a call.
Sources
- BCG, AI Leaders Outpace Laggards with Double the Revenue Growth and 40% More Cost Savings (The Widening AI Value Gap) (September 2025)
- Brynjolfsson, Rock and Syverson, The Productivity J-Curve: How Intangibles Complement General Purpose Technologies (American Economic Journal: Macroeconomics, 2021)
- Mark Schwartz, The (Delicate) Art of Bureaucracy: Digital Transformation with the Monkey, the Razor, and the Sumo Wrestler (IT Revolution, 2020)
Where this fits in WISE: this is part of Workflow analysis. See how the full WISE system works.
Questions people also ask
What are the five gaps AI exposes in commercial teams?
The Skills Gap, the Oversight Gap, the Scaling Trap, Thin Thinking and the Metrics Loop. They cover how work is briefed and judged, who holds the view across teams, how growth adds complexity, the quality of thinking behind polished output, and whether investment can be tracked back to results.
Which gap should you fix first?
Start with the one that's costing you the most, which is often the one closest to conversion. If you're not sure, a short self-check or scorecard across all five usually highlights the priority.
Are these gaps a sign of weak people?
Rarely. They're structural, which is why they tend to feel like people problems initially. Fixing the brief, the handovers, the process or the measures usually unlocks the potential hiding in your system.
About the author
Sarah L Morgan has led sales, marketing and BD teams for more than 20 years, from FTSE 100 media to £4m professional services firms. She now helps £5m to £30m businesses fix the people and process gaps AI exposes.
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