In the “olden days,” we walked into an account knowing more than the prospect. We knew the speeds and feeds, the lease ex-dates, the service costs, and the components of the monthly payment.
All the buyer knew was that the old device jammed Friday afternoon, the invoice “never matched” the quote, and the office manager had stopped believing the service promise sometime around the third callback.
That conversation has evolved, especially in this new AI/LLM world.
I wonder how many prospects are using AI now, and how much that changes the sale.
A quick look at the research reveals a few interesting points. Our prospects, especially the SMBs, may not have a corporate AI policy, but the data says employees are already adopting and using LLMs.
The Census Bureau’s Business Trends and Outlook Survey showed U.S. business use of AI was modest in early 2024, rising from 3.7% in fall 2023 to 5.4% in February 2024. By spring 2025, The Washington Post reported that 8.7% of U.S. companies used AI to produce products and services between April 21 and May 4, 2025, up from 4.8% a year earlier. That is formal business use, like AI-driven CRMs or line-of-business applications. That is not the “I asked ChatGPT before the meeting” usage.
Individual usage is more interesting. Gallup found that by early 2026, 50% of U.S. employees used AI at work in some capacity, 13% used it daily, and 28% used it daily or a few times weekly. This is nothing new; company adoption of anything new is slow. The people inside the company have always moved faster.
There’s more. The U.S. Chamber ofCommerce 2025 Empowering SmallBusiness Report found that 58% of smallbusinesses were using generative AI,up from 40% in 2024. Verizon’s 2025 small-business survey put SMB AI use
at 38%, especially for marketing, recruiting,and customer service. Surveys define “use” differently, but the direction is consistent. Most companies do not have an AI program. But their employees already have an AI habit.
Which means your prospect, especially the SMB buyer, probably uses AI inside Microsoft 365, Google Workspace, QuickBooks, Shopify, Airtable, ChatGPT, Copilot, Gemini, or another AI tool to help make purchasing decisions.
Not instead of the sales rep.
Before the sales rep.
It’s not hard to imagine a business owner asking an LLM whether leasing or buying makes sense. Or a controller and CFO pasting a contract into an LLM and asking for an explanation and red flags. The
office manager may have asked for questions to ask you, the copier vendor, before signing a five-year agreement.
The really savvy decision maker might upload a year’s worth of invoices, including meter reads, and tell the LLM to make a recommendation. Not just on one device, but across the entire fleet.
A clinic looking at a copier lease may feed AI page counts, monthly costs, service terms, toner assumptions, and the incumbent’s quote. A school business manager may ask AI to compare five-year costs across bids. A law firm controller may ask it to explain lease escalators and end-of-term obligations. A light manufacturer may ask whether in-house color
print makes financial sense compared with outsourcing.
Put that in your CRM.
Reps who pretend this is not happening will lose deals and blame price.
The sharper rep will ask a better question. “Before we look at my proposal, did you use ChatGPT, Copilot, Gemini, or another tool to compare options or frame the decision?”
Pause and let the buyer answer.
The next question is even better.
“What assumptions did it use?”
That one question opens the deal. Page volume. Color percentage. Number of users. Current lease end date. Service response expectations. Outsourced print spend. Paper path. Security needs. Growth plans. Monthly budget pressure.
The buyer’s AI answer is only as good as the inputs. Bad assumptions create polished nonsense. Good assumptions create a better buying conversation.
This is where you still have the advantage when you are willing to use it.
Sure, AI summarizes a lease and compares monthly payments. That part is easy. But AI does not walk the building and notice that shipping prints labels on one side while accounting waits at a device on the other. It does not hear the strain in an office manager’s voice when billing has been wrong for six months. It does not know that the receptionist has become the unofficial help desk because the “main” device sits in the wrong hallway.
The LLM helps the buyer prepare.
You help the buyer see.
AI on paper: more clarity, less noise
Think about your proposals.
Sales managers have spent years coaching reps on objection handling. Now they need to coach assumption handling.
Every proposal needs to make the assumptions visible. Show the page volume used. Show the service exposure. Show what happens if volume changes. Show the cost of downtime in a busy office.Show the difference between a cheaper payment and a cleaner operating decision. Buyers using AI will punish vague proposals. They will paste them into an AI tool and ask, “What is missing?”
When your proposal is chock-full of marketing, company history, soft promises, and eight pages of “we care about our customers,” the answer may be ugly.
You should be fine with that.
A vague proposal gets picked apart faster now. A strong proposal travels better inside the account. When the office manager forwards it to the owner, clean assumptions help. When the controller
looks at the lease terms, clean language helps. When the buyer uses AI to review the offer, real numbers help.
The buyer may use AI after the meeting.
That means your proposal has to hold up when you are not standing there to explain it.
The rep still writes for the human who has a machine nearby.
Clear scope. Clean terms. Real numbers.
Stated assumptions. No fog machine. No brochure perfume. No eight-slide company history from 1983 with a picture of the founder and a delivery van.
Nobody cares about the van.
There is risk, too. AI makes mistakes. It may compare outdated models, misunderstand service coverage, miss lease language, or trust bad online information. Some buyers will arrive with confident but wrong conclusions.
Arguing with the tool makes the rep sound defensive.
Auditing the assumptions makes the rep useful.
Remain calm and deliver:
“Let’s walk through what it compared.”
That sentence gets you more trust than a 10-minute speech about why your dealership is different.
We have seen this movie before. Buyers researched specs online, forwarded quotes to competitors, learned to question cost-per-page math, and got skeptical about five-year terms. Buyers stopped making the copier the center of the office.
AI is another turn of the wheel, with one new wrinkle. This time, the buyer has access to expert help before the rep arrives. That changes the day in small, annoying, useful ways.
Discovery needs to remain specific. Proposals need to get cleaner. Follow-up emails will be read against the meeting notes. Lease language gets questioned earlier, if not first. The office manager may arrive with better questions. The controller has less patience for mystery math, like they ever did, and the owner wants the operational case, not the brochure version.
For dealer principals and sales managers, this is a training issue hiding inside a technology issue.
The sales team needs to know how to ask about AI without sounding cute or threatened. The proposal template needs fewer company-history pages and more account-specific numbers. The manager reviewing a quote needs to ask the rep, “What assumptions are we showing the buyer?”
That is the work now.
Over the next few years, reps are going to need to know more about everything, especially from the prospect’s perspective. That is a bigger job than memorizing speeds and feeds.
It is also a better job.
The buyer has a machine now, too.
Good.
A prepared buyer is still a buyer. A confused buyer with AI is still confused, only faster.
The deal is closer when you cut the noise, clean up the facts, and leave the prospect with a decision they still understand after you drive out of the parking lot.
AI Columnist Greg Walters
About the columnist: Greg Walters is a writer, analyst, speaker, and longtime technology operator who has led managed print and IT initiatives for several organizations. He is a founding member (and past president) of the Managed Print Services Association (MPSA) and creator of The Death of the Copier blog. Walters also co-founded the Cricket Continuum, which works to convert office technology dealers into robotics resellers and service partners. Future columns will continue to focus on artificial intelligence in the copier dealer community. If you have curiosity about the subject, drop us a line, and we’ll see if we can come up with something.
