Artificial intelligence tools can dramatically cut the time businesses spend responding to requests for proposals and fine-tuning quotes, but it is important for companies to understand when it does and does not make sense to employ it, two consultants said on a recent Professional Pricing Society podcast.

“As we know from the release of ChatGPT, we saw there was a lot of interest among pricing professionals and there’s also a lot of potential for AI to revolutionize the quoting process. But there’s a huge gap in between practical knowledge, concrete examples and the theory of how it might happen,” said Brooks Hamilton, principal of Austin, Texas-based Hamilton AI Strategy Advisors. 

The trick is to break down the multi-step and time-consuming process of responding to RFPs, developing price quotes and getting approvals, Hamilton said. The steps vary from company to company but often involve tedious and repetitive input of data into Excel spreadsheets that make pricing experts want to “rip their hair out,” according to Lydia DiLiello, CEO and founder of Capital Pricing Consultants. 

For example, when a pricer gets an RFP and puts it together, typically that step is just the first step in the process. They then need to take the quote to their boss and get permission to send it out the door, which invariably can’t happen until the questions that usually surface around a variety of pricing scenarios are answered, DiLiello said. These often include “what if” scenarios around the impact of various changes to pricing and volume of the product or service that is sold, she said.

“Well now, what that means to the person sitting there is, ‘I gotta go back and spend four hours crunching this number to get an answer,’” she said. “No you don’t. You feed it into the AI tool, let it crunch for 10 minutes and you’ve got an answer. Now you make a decision as the human and go back to your boss with a proposed recommendation.” 

In terms of what in the pricing arena is ripe for AI adoption, she said it is often repetitive tasks that are “hugely time consuming.” Ideal opportunities to use AI include when handling large sets of data demanding a repetitive function and mapping out various “what-if” scenarios, she said. 

“The change-in-volume scenarios, the change-in-price point scenarios — all of which our senior executives constantly ask for — no longer become a three-day ordeal,” she said, noting that she has seen estimates that AI can cut the time businesses spend on price quotes by between 30% and 70%. “It becomes 15 minutes of inputting the variables, hit the button and let the AI crunch.”  

Speeding up the time in which businesses can respond to RFPs can drive profits, Hamilton said. In talking to businesses, he said many are not currently able to respond to requests for bids fast enough. “In order to win you first need to submit a bid,” he said. “If our clients can respond to every bid they have a request for they will probably have a higher revenue rate.” 

Hamilton also cautioned that it is important to understand the areas where AI is not an appropriate tool to use. AI is great in figuring out repetitive tasks but “we need to be the ones making the value judgments and evaluating what we send to our customers and how it fits into the larger picture of our go to market strategy,” he said. 

DeLiello and Hamilton are scheduled to give a workshop on using AI to speed the quoting process at a Professional Pricing Society conference in Chicago later this month.