AI is changing how businesses operate, and sales teams are feeling the impact firsthand. While sales should be about connecting with customers and closing deals, many sales representatives find themselves buried under slow, repetitive tasks that drain their time and energy.
According to Salesforce, sales teams spend just 30% of their week actually selling. The rest goes to tasks like entering data, writing emails, or searching for leads. These are the areas where AI can help the most.
According to research from Harvard Business Review, companies that use AI in sales see up to 50% increases in leads and 40–60% cost reductions. But there’s a catch: AI only delivers these results when your sales team has the right data infrastructure supporting it. In other words, success depends on knowing which tasks to automate and having quality data to make AI systems work effectively.
In this article, we’ll explore how AI is helping sales teams do more with less. Whether you're new to AI or looking to leverage it further, this guide will help you take the next step.
Selling today is more challenging than ever. Buyers expect fast and personalized service. At the same time, sales teams are dealing with increased data, a greater number of tools, and heightened pressure to achieve their goals. Working remotely has added new challenges. Reps now rely more on digital tools to connect with buyers. This creates more data and more work.
McKinsey mentions that more than 30% of sales tasks can be automated using AI. This includes tasks such as writing emails, scoring leads, and updating CRMs. AI helps teams focus on what matters by handling the boring, repetitive tasks. This means less time spent on admin work and more time selling.
Here is the potential of AI for sales:
Before using AI in the sales process, it is important to understand the processes that are causing delays. Start by looking at tasks that take too much time. These are often manual and repetitive. AI works best when it replaces or speeds up these types of tasks..
Here are some common pain points that AI can fix:
Each of these bottlenecks can delay your sales cycle. They also lower team morale and reduce time spent selling. Finding and fixing these slow spots will set the stage for a smoother AI rollout.
AI is only as good as the data it uses. AI tools will not work well if your data is messy or incomplete. A strong data foundation is key to using AI in sales.
Sales data often comes from multiple sources, including CRMs, emails, calls, marketing tools, and spreadsheets. If this data is not organized, AI can not find useful patterns. Clean, structured data helps AI make smart choices.
Here are several key areas your team should focus on:
Poor data quality directly translates to poor AI performance in several ways. Incomplete records lead to biased models that overlook important customer segments. Duplicate entries cause AI to double-count activities and overestimate engagement levels. Most damaging of all, outdated information causes AI to base recommendations on conditions that no longer apply.
To address this, establish basic data rules, standardize the data entry process, use pipelines to transfer data between systems, and implement simple dashboards to monitor data quality. These investments in data infrastructure pay dividends when AI applications can operate at their full potential and deliver accurate insights and predictions that drive revenue growth.
A sales team using AI to write outreach emails saw a 3x increase in response rates. Another team cut CRM entry time by over 60% using AI automation. These are just some of the many use case examples of AI for sales. Here are some common ways AI is used in sales today:
AI scores leads by looking at past deals, customer behavior, and CRM data. This helps reps focus on the leads most likely to buy. For example, if a lead opens several emails and visits your pricing page, AI can mark them as high priority.
Some tools even adjust scores in real time as new actions happen, like a demo request or reply.
Finding the right contacts and writing emails can take hours. AI tools now help:
This means reps spend less time searching and more time selling.
AI can use historical sales data to predict the sales volume your team is likely to achieve this month or quarter. It can also update the forecast when deals move or stall. These tools can identify trends and seasonal patterns that are easily missed with manual methods.
What’s more, these smart tools update forecasts automatically in real time as deals progress, stall, or change in value. This means sales leaders get a much clearer, up-to-date view of what’s likely to close and which deals might be at risk.
For example, Takeda Oncology, a global pharma company, uses an AI-powered forecasting tool that combines patient data and treatment trends. It helps sales teams get accurate, real-time forecasts and adjust strategies on the go. This has improved how they plan outreach and allocate resources.
With this insight, teams can improve pipeline accuracy, track quotas more effectively, and make smarter decisions to hit their targets consistently.
Sales calls can be packed with important details. But it's hard to review them all manually. AI tools help by:
Some tools even analyze tone, pacing, and word choice to suggest better ways to pitch. This helps sales managers coach their teams more effectively and ensures important details don’t get lost after the call.
Moving from a lead to a signed contract takes time. It often involves pricing, approvals, proposals, and paperwork. AI helps speed this up.
It can:
This shortens the time it takes to close deals and reduces errors. For example, Invisible helped a solar provider automate proposal and CRM tasks across a large volume of deals, saving hours of manual work.
AI can improve your sales process, but you need a clear plan to make it work. Here are five steps to help you get started:
Begin by examining how your sales team operates today. Find the tasks that take too much time or feel repetitive. This could be data entry, lead follow-up, or quoting. Make a list of where things slow down.
AI needs large amounts of structured, high-quality data to be effective. Many sales teams struggle here. You should:
If your data is messy or siloed, AI predictions and insights will be unreliable.
Avoid generic AI tools that promise everything. Instead, look for solutions built for specific use cases:
It is also important to look for tools that fit your sales model and are easy to adopt. Piloting several options with your team before committing helps ensure you pick the right fit.
You don’t need to use AI across the whole team on day one. Pick one process to improve. Test the tool. Get feedback from your team. Adjust and improve. Once it works, expand to other parts of your sales funnel.
People are often unsure about new tools. Train your team on how to use AI. Show them how it saves time or helps them hit goals. Collaborate with sales, operations, and IT to ensure everyone is aligned. This makes adoption easier.
These steps can help avoid common mistakes and get real value from AI. Start slow, focus on data, and always tie the tool to a clear problem.
The potential of AI in sales is expanding quickly, and more companies are starting to embrace it. According to Gartner, by 2025, over 30% of all B2B sales organizations will have integrated AI-powered tools into their core workflows.
Here are some of the key trends shaping the future of AI for sales:
AI for sales is not a quick fix. It is a journey that takes time, planning, and effort. The best way to start is by finding the slow, manual tasks in your sales process. From there, focus on building a solid data foundation that can support AI tools effectively.
AI can help your sales team work smarter, save time, and close more deals when done right. To explore how AI can enhance your sales, begin by auditing your current workflows and data. This will show you where AI can have the biggest impact.
Learn how Invisible can help you kickstart your sales organization’s AI journey by auditing workflows and data infrastructure, identifying opportunities, and spinning up AI solutions fast with our expert workforce.
