Harnessing AI in sales: Strategies for smarter selling

Integrating AI in sales: from vision to value

The question of how, if, and when to implement AI in sales to work alongside existing CRM solutions is at the forefront of executives' minds around the world. Yet, according to McKinsey, only 21% of B2B sales teams at enterprise companies report having fully integrated AI automations and tools into their processes, while 22% have conducted limited pilot programmes.

These statistics are more impressive, however, when adjusted for adoption timeframes. In 2025, large language model (LLMs) chatbots already enjoy a usage level of nearly 45%. It is clear that these new AI tools for B2B sales are not just improving workflows and outcomes; they are becoming essential for companies to remain competitive.

The good news for CROs and CIOs? Unlike the scale and scope of traditional SaaS migration implementations, deploying AI B2B sales and marketing solutions can be completed relatively quickly and affordably. And, instead of ROI taking months to be felt throughout an organisation, benefits to sales teams are evident almost from day one.

But every organisation is different, and so selecting the right approach is imperative. Stakeholders must have a clear vision of which challenges they are trying to solve, who will be using the AI B2B marketing and sales tools, and how they will measure the success of a new AI software investment.

Using AI-driven sales strategies to address pain points

A sales team's performance can be affected by everything from legacy software limitations and company culture to market conditions and management decisions. However, they all tend to share certain challenges. The following AI in sales examples illustrate how its capabilities can support and address challenges for most B2B teams:

Administrative overload: Agentic chatbots and virtual assistants can handle initial enquiries from prospects, write e-mail updates and responses, and flag follow-up tasks to help salespeople use their time more efficiently while shortening B2B sales cycles.

Connecting the data dots: Context and history regarding a customer or deal often spans months and involves many people and moving parts. AI agents can gather all relevant details in an easy-to-read report, so salespeople have everything needed at their fingertips when meeting with or responding to prospective clients.

Lead scoring in the sales cycle: Sales teams are keen to follow up on leads but often lack insights into which ones are most likely to convert, and in which financial quarter. By using machine learning, lead scoring features help to predict each prospect's purchasing stage and can significantly improve sales results.

Forecasting and prediction: In-depth data analysis and pattern matching identify sales trends, anticipate disruptions, flag customers for potential attrition, and more. Armed with timely insights, sales teams can adapt their approach to products or address issues that prevent negative impacts while potentially increasing sales.

Building business relationships: Offloading administrative tasks frees up time for salespeople to focus on personal contact with prospects and customers, learning about their needs and objectives. This enables them to tailor and customise solutions for each client. AI sales tools can also assist with gauging sentiment, flagging issues, forming insights for negotiations, and more.

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How new AI in sales automation can improve results

Unlike other recent automation technologies that primarily improve productivity, the latest AI capabilities for B2B sales can now play an active role in generating revenue alongside your sales staff. Many companies have worked out how to use AI in sales and are now beginning to implement virtual sales agents. Preliminary results from these creative use cases are encouraging:

• Getting in touch at the right time
  Teams with well-tuned AI-driven sales strategies and automations benefit from the system acting as their eyes and ears to monitor current customers and sought-after prospects. Agents monitor changes in leadership, product launch announcements, location expansions, and more. When appropriate, sales teams are prompted at the right time with new data and suggested pitches to facilitate engagement.
• Activate new segments
  Keeping up with fast-moving industry changes is challenging and can leave business leadership feeling blindsided by events such as supply chain disruptions and price fluctuations. Automated AI sales agents monitor social media sentiment, track competitor developments, follow specific news topics, and help anticipate product demand in a new market. This enables companies to respond appropriately and proactively.
• Tailored sales coaching
  While every successful salesperson has many strengths, no one strikes gold every time. However, by using AI sales tools to analyse negotiation tactics and identify win/loss patterns, teams can build an internal best practice guide to elevate each representative's performance. Companies can include this in their induction process to help new employees get off to a flying start.
• AI co-selling support
  While still in development, innovative sales teams are beginning to build complex agentic workflows, which act as virtual sales assistants. For example, the agent can conduct research, gather contextual data, create an initial sales presentation, and provide price negotiation considerations before a salesperson ever makes their first call.

Providing AI decision-makers with the details they require

When choosing AI-driven sales and marketing tools, astute executives get ahead of budgeting objections by making their cost/benefit analysis specific and easy to understand for a non-technical audience. This works well as finance often falls within the remit of company leadership, who may not immediately recognise the value of an innovative technology investment.

Here are key benefits to include when discussing the implementation of AI in B2B marketing and sales software for your organisation:

• Enhancing, rather than adding
  Unlike large-scale IT projects, AI solutions for B2B sales are designed to integrate with existing software, workflows, and roles within a company. Representatives are prompted and guided within existing dashboard environments, so adoption feels intuitive and helpful. In addition, these tools are transferred to salespeople's mobile apps, so they are supported wherever the working day takes them.
• Incremental, rather than immediate
  If leadership is not certain about a department-wide rollout or licensing commitment, start small. Prioritise which team could benefit most from AI sales automations and agents. Next, provide real-world use case examples from your sector, and propose a three to six-month pilot programme to test its effectiveness.
• Visible, rather than opaque
  Agree on a specific timeline and the KPIs you will measure against, then let the B2B AI sales programme run. Unlike ERP digital transformations, where the ROI is not immediately apparent, your team will quickly know if they are meeting more prospects, saving more time, and closing more deals.

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Looking ahead: AI for B2B sales and marketing

The age of AI is in full swing, and businesses of all sizes around the world are assessing how to take advantage of its many benefits. Companies shifted from questioning whether AI tools were worth the investment to prioritising AI-driven sales strategies in a short period of time. In fact, according to Forbes, "75% of B2B automation decision-makers in Forrester’s Automation Survey, 2024, indicated that they expect their organisation to invest in sales automation in the next 18 months."

Some salespeople may have reservations about adopting AI tools into their workflow, as well as concerns about AI taking over their role. However, it is clear that customers still need and expect a human element in their supplier and partner relationships. Rather than replacing anyone, new B2B AI sales tools enable more in-depth, genuine connections and collaborations between both sellers and buyers; and that is a win for everyone.

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