Gabriel Cohen: How Klipboard's VP of Go-To-Market Uses AI to Grow Field Service Firms

Gabriel Cohen spends his week on a question most field service vendors still treat as a marketing slogan: how does the next job actually get won, scheduled, and billed. He is Vice President of Go-To-Market at Klipboard, a field service management platform for companies that schedule jobs, dispatch technicians and invoice from the same record. His job is not to argue against software. It is to put the product in front of the operators who can grow with it, then prove that growth in completed work, not in a slide deck.

Go-to-market is a growth job, not a demo job

Cohen came up through sales and operations in industries where field teams were often last to see a new tool. That background now sits inside a go-to-market brief. He looks for firms that already have demand and are losing it to missed slots, slow quotes, and invoices that leave the building a week late. The pitch is specific. A heating or electrical company that can see who is free, what the last visit involved, and whether the job is ready to bill can take on more work without adding a second office person to chase paper.

That is why he talks about go-to-market in operational language. A campaign that fills the pipeline is wasted if the firm cannot schedule the extra jobs. A closed deal is wasted if the first month of use never makes it onto the van. Cohen treats onboarding, first completed jobs, and time-to-invoice as part of the same motion as the sale.

Where AI actually helps a field firm grow

The AI conversation in field service is noisy. Cohen keeps it on growth. He is interested in tools that help a scheduler fill the day, help a sales lead turn a site visit into a quote faster, and help a manager see which customers are ready for another visit before the work walks to a competitor. Used that way, AI is a growth layer on top of the job record, not a replacement for the people who do the work.

"AI is useful when it gets a firm to the next job faster," Cohen says. "A better forecast of who needs a visit, a quote that does not sit in someone's drafts, a schedule that does not leave a technician idle at 2pm. That is go-to-market. That is growth. It is not a chatbot for the sake of a chatbot."

He has watched operators buy software and then stall because nobody showed them how the product turns into extra capacity. His answer is to put AI on the tasks that already decide revenue: which lead to call, which slot to offer, which completed job is ready to invoice. When those three move faster, the firm can take more work. When they do not, no amount of reporting will grow the business.

The same record, more work through the door

Klipboard's GTM story, as Cohen tells it, is a shared job record that sales, operations and finance can all use. The scheduler needs to see who is free. The technician needs the history and the parts. Finance needs the completed visit turned into an invoice before the week is out. If those three views come from the same record, the company can sell more work without reconciling three versions of the truth at month end.

Field service makes that gap expensive. A missed photo, a job left open, or a visit that never left a phone is not a reporting issue. It is a delayed invoice and a customer who cannot be offered the next visit. Cohen's argument is that AI and a single platform are how a firm grows through that mess: faster quotes, fuller days, cleaner billing. Software is the system. Growth is the point.

Sell the first month, not the feature list

Change management still sits inside his go-to-market work, but the aim is adoption that produces growth. He pushes prospects to involve field staff before the contract is signed, and to name the two or three tasks that actually slow the week down. Get those live in the first month, with AI sitting on the jobs that create capacity, and the rest of the platform has a chance of being used.

For Cohen, a successful launch is not a dashboard that looks good in a board meeting. It is a field firm that is booking more work because the schedule, the quote and the invoice finally move at the same speed. "If we cannot show a customer how this helps them grow in the first 30 days, we have not done go-to-market," he says. "AI is one of the ways we get there. The product has to be the other."