Part 3: Are You Giving AI More Context Than You Give Your Customers?
AI is teaching businesses to communicate more clearly. B2B customers have needed that clarity all along.
Most of us have had some version of this experience.
We ask an AI tool to create something using a short, general prompt. The response is technically correct, but generic, incomplete or simply not what we intended.
So we try again.
This time, we explain the audience. We provide background. We describe the objective, identify the most important points and specify the desired outcome.
Suddenly, the output improves.
We may think we are learning how to use AI. But we are also learning something much more fundamental: how to communicate clearly.
A recent Nimbl Digital article examines this idea through the lens of neurodivergence. Its premise is that AI’s need for explicit context and direct instruction mirrors communication practices neurodivergent people have advocated for years.
Clear expectations. Written instructions. Defined priorities. Fewer assumptions. Less reliance on people to interpret what was left unsaid.
These practices reduce ambiguity and unnecessary cognitive effort. They can make workplaces more inclusive, but they also make communication more effective for everyone.
That same principle should extend beyond our internal teams.
It should change how B2B companies communicate with customers.
The customer should not have to fill in the blanks
Companies naturally develop a shared internal language.
Employees know the products, acronyms, competitors and history. They understand what the company means when it uses certain phrases. They can often fill in missing information because they already possess the context.
Customers do not.
Yet much of B2B communication is created as though they do.
A website describes a company as delivering “transformative solutions” without explaining what is being transformed. A sales presentation lists capabilities without connecting them to the customer’s priorities. A follow-up email says the team is “circling back” without clarifying what decision is needed. A proposal explains what will be delivered without defining what success should look like.
The customer is left to interpret the message, identify its relevance and determine the next step.
When that does not happen, we may conclude that the customer was not interested, did not pay attention or was not ready to buy.
Sometimes the real problem is simpler: we made the customer work too hard to understand us.
AI is making the cost of ambiguity visible
AI provides an immediate demonstration of what happens when communication lacks context.
A vague request produces a vague response. An ambiguous instruction can be interpreted in several different ways. An unstated expectation remains unstated.
We have learned to correct this by giving AI more complete inputs:
Who is the audience?
What does it already know?
What problem are we trying to solve?
What information is most relevant?
What outcome do we want?
What constraints should be considered?
What should happen next?
Customers need many of the same things.
They need to know whether a message is meant for them, what problem the company understands, why the information matters and what makes the proposed solution relevant. They need enough context to evaluate the message without decoding internal language or making assumptions about what the company intended to say.
This does not mean every customer communication should be lengthy. Clarity and volume are not the same thing.
In fact, the clearest communication is often shorter because it removes the words that are not doing useful work.
Clarity is part of the customer experience
B2B companies frequently treat messaging as a marketing deliverable. But communication quality affects the entire customer relationship.
Clear website messaging helps buyers determine whether a company is relevant before investing more time.
Clear sales communication helps multiple stakeholders understand the problem, solution and business case.
Clear proposals reduce questions about scope, responsibilities and expected outcomes.
Clear onboarding materials prevent early frustration and establish confidence.
Clear customer communications help people understand what is changing, why it matters and whether they need to take action.
In each case, clarity reduces friction.
It also builds trust. Customers are more likely to feel confident in a company when they do not have to search for the point, interpret vague promises or repeatedly request information that should have been provided in the first place.
This becomes particularly important in complex B2B purchases. The person reading your content may need to explain the solution to a manager, procurement team, financial decision-maker or executive sponsor.
If that person cannot easily repeat your message, your communication has not finished its job.
Clearer communication also helps AI understand your company
There is another reason this matters now.
Customers are increasingly using AI platforms to research companies, compare options and develop shortlists. Those systems rely on the information companies make available publicly, including website copy, articles, press releases, case studies, executive commentary and third-party coverage.
When that information is vague, inconsistent or outdated, AI has to reconcile the gaps.
A company may understand its own differentiators perfectly. But if those differentiators are never stated clearly and consistently in public, neither customers nor AI systems can be expected to infer them accurately.
Clear communication now serves two audiences at once:
The people evaluating the company.
The AI systems helping those people conduct their evaluation.
That does not mean companies should write for algorithms at the expense of humans. It means the qualities that help people understand a business also help AI represent it more accurately: specificity, consistency, context and credible evidence.
A simple clarity audit
Before publishing a customer-facing communication, consider asking:
Would someone outside our company understand the main point?
Have we explained why this matters to the customer?
Are we using terminology the customer knows, or terminology we know?
Have we provided enough context without overwhelming the reader?
Is the desired next step explicit?
Could a customer easily share or summarize this information for another decision-maker?
Are we expecting the audience to make a connection we should make for them?
These questions apply to everything from a homepage and sales email to a proposal, case study or customer announcement.
They also reveal an important distinction.
Clear communication is not about assuming less intelligence on the part of the audience. It is about demanding less unnecessary interpretation from them.
The lesson is bigger than prompting
AI may be forcing businesses to become more disciplined about context, instructions and desired outcomes.
The opportunity is to carry that discipline into our human relationships.
Customers should not need to learn how to prompt a company to receive a clear explanation. Employees should not have to interpret unstated priorities. Buyers should not have to translate marketing language into business relevance.
The best B2B communication provides the audience with what a good AI prompt provides the tool: context, purpose, relevance and a clear definition of what should happen next.
If we are willing to provide that clarity to a machine, we should certainly be willing to provide it to the people whose trust and business we hope to earn.