How to use AI in sales

Companies can use AI in sales to make sales processes more efficient, analyse customer data and automate recurring tasks. From lead qual­i­fic­a­tion and customer com­mu­nic­a­tion to sales analytics, AI systems can reduce teams’ workloads and create new ways to per­son­al­ise the sales process.

What does AI in sales mean?

AI in sales means using ar­ti­fi­cial in­tel­li­gence to support or partially automate tasks within the sales process. AI can process customer data, identify patterns and provide in­form­a­tion that helps sales teams make decisions and assist customers. AI can also play a sup­port­ing role in customer ac­quis­i­tion.

Unlike tra­di­tion­al auto­ma­tion, modern AI systems can also analyse un­struc­tured content such as free-form text, con­ver­sa­tions or documents. This opens up new use cases across the entire customer journey.

How do you use AI and AI agents in sales?

When using AI in sales, companies should focus on parts of the sales process that involve recurring tasks, large volumes of data or frequent customer in­ter­ac­tions. The first question should not be which AI tool to choose, but what could be improved in the sales process. This might include slow responses to enquiries, too much manual work in lead scoring or customer con­ver­sa­tions that take a lot of time to prepare for and follow up on.

Companies also need to decide whether a standard AI tool is enough, or an AI agent makes more sense. For in­di­vidu­al tasks such as writing an email or sum­mar­ising a con­ver­sa­tion, an AI assistant is usually enough. AI agents are useful for multistep workflows where they process in­form­a­tion and then perform actions on their own, such as booking an ap­point­ment or for­ward­ing an enquiry.

Qualify leads more ef­fi­ciently

Not every new lead is equally relevant to the sales team. AI can evaluate in­form­a­tion from enquiries, CRM data or previous in­ter­ac­tions and help pri­or­it­ise leads based on pre­defined criteria. How well AI can do this depends on the quality of the data available. If customer data is in­com­plete, outdated or spread across multiple systems, the quality of the as­sess­ment will also drop.

Automate customer com­mu­nic­a­tion

For questions that come up fre­quently, AI can handle the first stage of customer com­mu­nic­a­tion. Chat or phone as­sist­ants can, for example, provide in­form­a­tion about services, collect contact details or record what a potential customer needs. AI agents can also work with other systems. If it’s connected to a calendar, for example, it can check available time slots and make a booking.

Prepare for and follow up on sales con­ver­sa­tions

Before customer meetings, teams often need to gather in­form­a­tion from different sources. AI can organise existing customer data, emails, messages or product in­form­a­tion and turn it into a concise meeting brief. After the meeting, it can summarise the con­ver­sa­tion and identify out­stand­ing issues or next steps.

Prepare proposals and follow-ups

Gen­er­at­ive AI can draft proposal letters, sales emails or follow-ups using the in­form­a­tion provided for the task. This is useful when their content is similar but needs to be adapted to the industry, target audience or how the con­ver­sa­tion went.

Analyse sales data

AI can also help companies analyse sales data alongside handling day-to-day sales tasks. It can identify patterns in the pipeline, compare sales op­por­tun­it­ies, or highlight changes in close rates and pro­cessing times. This can help pinpoint where leads tend to drop out of the sales process.

How can companies develop a strategy for using AI in sales?

De­vel­op­ing a suc­cess­ful strategy for using AI in sales requires more than simply adopting in­di­vidu­al AI tools. Companies need to combine tech­no­logy, sales processes and human expertise. They should start by identi­fy­ing where AI can deliver clear value in the sales process.

When enquiry volume is high and the sales team has limited capacity

Many companies regularly receive new customer enquiries through different channels. These may come through online forms, direct enquiries or other digital com­mu­nic­a­tion channels.

The challenge is to respond to all incoming enquiries quickly while also identi­fy­ing which potential customers are most promising. When enquiry volume is high, reviewing each enquiry manually at the outset can take a lot of time.

Typical chal­lenges include:

• long response times to new enquiries,
• a lot of effort spent on the initial as­sess­ment of potential customers,
• missing in­form­a­tion that the sales team needs for the next step.

How to integrate an AI sales agent into the sales process

A sales strategy that uses AI should focus on areas where recurring workflows can be automated and sales teams can be freed up. An AI sales agent can support different parts of the sales process. In the initial phase, for example, it can help by:

1. Capturing incoming enquiries: The agent records incoming enquiries and organises the relevant in­form­a­tion.
2. Assessing customer needs: The agent analyses the enquiry and helps the sales team un­der­stand what the potential customer needs.
3. Qual­i­fy­ing potential customers: The agent uses a set of criteria to determine which potential customers should move to the next stage.
4. Preparing in­form­a­tion for the sales team: The agent organises the relevant in­form­a­tion so the team has what it needs for the next step.
5. Handing qualified leads over to the sales team: The sales team takes over and handles the next steps directly with the potential customer.

One example is the IONOS AI Ac­quis­i­tion Manager: it auto­mat­ic­ally creates social media posts for specific target audiences, schedules them for pub­lic­a­tion and adapts content to current trends. This helps companies sys­tem­at­ic­ally expand their reach and attract new potential customers – without requiring marketing expertise or manual work.

When companies combine automated workflows with human expertise, the sales process becomes more efficient. AI can help with day-to-day work such as handling customer enquiries. AI sales agents can go further by sup­port­ing multiple stages of the sales process, including analysing sales op­por­tun­it­ies and helping teams decide what to do next.

How can AI and the sales team work together more ef­fi­ciently?

An AI sales agent can take recurring tasks off the sales team’s plate and help them respond to enquiries faster. The goal is not to automate the entire sales process. Instead, AI can handle the routine work while the sales team steps in where personal advice and human judgement are needed.

Used this way, an AI sales agent becomes part of the wider sales process rather than just another stan­dalone tool. By combining auto­ma­tion with human input, sales teams can respond to potential customers more quickly and spend more of their time on the work that needs their attention.

What are some of the benefits and chal­lenges of using AI in sales?

AI can take routine work off the sales team’s plate and help them work through sales data more ef­fi­ciently. But it does not replace strategic planning or the personal re­la­tion­ships that are important in sales.