Revenue teams are having trouble understanding their customers. In Gong’s report “The State of Revenue Growth 2025” Gong surveyed several revenue team leaders, and only 27% of them were confident that their team members fully understood their customers, their needs, and their buying behavior. There were several reasons for this: the market is changing rapidly, there is a Lack of reliable insights, and sales training is inadequate.
Why revenue teams do not understand what customers want?
- Rapid change of the market
- Lack of reliable insights
- Inadequate sales training and enablement
To solve this problem Gong suggested that team leaders need to equip their teams with tools that can help their teams get real-time actionable insights as CRM systems are becoming old-fashioned and falling short. 90% of the respondents to Gong’s survey said that CRMs are not providing a comprehensive understanding for their customers and only one-third of the respondents agreed that their CRM is providing strong ROI. But here comes the real question, What tools can these teams shift to, and can AI solve this problem?
Study: Traditional CRMs are not providing comprehensive understanding of customers.
AI Sales assistants
AI has become the trend of our century as we see lots of LLMs emerging so frequently and startups are integrating these LLMs into some features creating lots of SAAS tools for different types of needs. But it did not stop there, Also big software providers and CRMs are integrating AI into their systems to automate the tasks a user needs to be done.
These integrations had a huge benefit for the users whether they were SMEs, solopreneurs, or big Enterprises as automating administrative work and researching can save sales professionals over 2 hours daily. Which can be spent on contacting and communicating with prospects rather than doing these tasks.
AI sales tools can save sales professionals over 2 hours daily.
The problem here is that these integrations came with extra cost. For example, if you are a Salesforce user you need to pay $75 to have the ability to use their AI model Einstien. Another example is Gong itself. You need to pay platform fees “it doesn’t make any sense for me” in addition to the user subscription which can cost you up to $150k for a team of 50 members. The last example is Apollo. In addition to its big database of leads, Apollo has so many great features that might be inaccurate, but it is still there and sales professionals still find it cool. But they worked a lot on the functionalities and features and forgot about making the user interface more friendly and better looking than just a huge Excel sheet.
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Integrating AI with sales
According to Gong’s report, 48% of the leaders stated that their revenue teams are using AI tools to make the process go faster and generate stronger ROI. And 24% are not integrating AI yet but they have plans for this in the future. While only 27% are not planning to make these integrations. Although AI is not adopted widely, yet 85% of revenue professionals are experimenting with AI on their own with their use cases.
We can conclude from these numbers that the AI software providers need to not only focus on providing better plans for enterprises But also offer plans for individuals as they are already looking for tools to help them whether their leaders are providing these tools or not.
Also in my point of view, the AI software providers need to find a way to provide their plans for lower prices as the companies are already struggling with the economic downturns worldwide. Whether they are in Europe and facing high energy prices or they are in the USA and facing high inflation, these downturns have already raised the expenses for these companies resulting in huge layoffs, and as they are looking for ways to generate more revenue and putting a high pressure on revenue professionals to fill the revenue and expenses gab for them. This may make it hard for SMEs to adopt AI to their sales process as they don’t have enough resources to do it.
Conclusion
The adoption of AI For sales professionals and revenue teams has transformative potential but faces challenges like high costs, limited accessibility, and economic pressures. Many tools are priced out of reach for SMEs and solopreneurs, while traditional CRMs are falling short. AI providers must address these gaps by offering affordable, flexible pricing plans, improving user experiences, and tailoring solutions for both enterprises and individual users. With global economic downturns increasing financial strain, providers should consider discounts and incentives to make AI tools accessible. Addressing these challenges can drive broader adoption, empower revenue teams, and deliver stronger ROI across the board.