
According to a study from agentic sales messaging app business Discovery, sales teams have not found conceptual AI to be a significant help in terms of making work easier. The main reason is that AI lacks the human factor.
You might assume that it’s the best program for AI because profits are about conversation, but language versions even talk about conversation, but I have an opinion when I sell, when I try to communicate something to you, according to Breakthrough CEO and co-founder Adit Abhyankar in an appointment with TechRepublic.
Between February and March 2025, Breakthrough surveyed 500 US and UK-based selling managers, supervisors, and managers who worked for businesses with more than 50 people.
Salespeople have a hard time using AI to perform specific tasks.
Selling as an industry is also deciding which things definitely need a human touch. According to Abhyankar, confidence between people is a key factor in these things. While many people are using AI, which surprised Abhyankar because of its widespread application in the study, the challenge is finding the best uses for it.
What AI does is that it incredibly quickly gives you points that seem plausible,” said Abhyankar. And what actually happens is that it’s really simple to get a well effect because it appears really nice at first glance when you read it. However, when you examine it in more detail, you realize that in reality, it’s not very nice because it doesn’t really convey what I was trying to say.
Working with AI becomes” unwieldy” when salespeople have to explain to the conceptual AI what it did bad, according to Abhyankar.
Nearly half ( 47 % ) of sales professionals surveyed reported that they spend between 31 and 60 minutes a day on generic AI tools, which is the same amount of time they spend on CRM tasks.
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Typically, sales team use general AI.
According to Adit Abhyankar, chief executive officer and co-founder of Breakthrough,” the main use circumstance for AI for marketers straight today is around material generation,” according to the interview with TechRepublic.
55 % of teams used AI to generate sales material, while 42 % of teams used it to generate general content. 47 % of people who used AI to conduct research on prospects, 40 % to prepare for meetings, and 39 % to create presentations.
What tasks should be made up of tasks for humans and those for AI?
” I believe what’s more likely is that we will improve our ability to distinguish between this human task and an AI task,” he said. He cited AI as an example of how a salesperson can make a slide, allowing them to meet attendees at events more quickly.
AI may be able to identify the most actionable insights from a conversation, but it is unable to identify business leads.
Without having any prior experience with your business, he said, it’s difficult to pitch something to a potential client. Trust is strengthened by sincere interactions and warm, sincere greetings.
Other pain points identified by salespeople in the study included inaccurate results and hallucinations, AI tools that didn’t understand their specific needs, and too many iterations being required to get useful results.
Privacy is less of a concern than “losing control.”
23 % of sales professionals concerned about privacy and data security when using AI, according to Breakthrough. Because sales professionals are most likely to use an AI product in their own businesses, privacy is a relatively minor issue. The probabilistic system spewing out unanticipated, off-topic content is a bigger issue, according to Abhyankar.
” I would say that the privacy risk is a well known problem that has been solved before, while this risk that AI creates things that you don’t control and that might actually harm your brand is not something we know how to control yet, and that’s not a well known problem,” he said.
It’s still challenging to demonstrate AI’s ROI.
For a variety of reasons, it is challenging to demonstrate the ROI of AI. AI might not be able to offer strategic advice that can be used to make money in the sales industry. Another factor: Comparing the amount of time saved to the amount of extra work done can be difficult to determine productivity savings.
You’re working more with less time, so you’re more productive, but the company as a whole isn’t because it hasn’t really figured out what to do with those extra three hours you’ve saved, according to Abhyankar.
This uncertainty is a natural progression, he said, referring to “how technology normally operates.” ” You end up with capability, and only once you understand it can you truly increase business value,” says one quote.