AI in B2B Sales: Key Trends and Strategies to Join the Digital Revolution

Among many applications of AI for business, AI in B2B sales has gained a particularly impressive adoption among companies small and large. According to McKinsey, sales teams leveraging the technology report consistent efficiency upticks of 10-15%. They also report an increase in the time sellers dedicate to their customers rather than back-office activities such as pipeline management or invoicing.

AI adoption today gives you a significant competitive advantage, however, it can be challenging to understand where to start, which AI tools to choose, and how to maximize their potential.

This article explores the most impactful use cases for AI in B2B sales, offers practical tips for implementation, and highlights key tools that can help you stay ahead in the digital revolution.

What is AI in B2B Sales?

AI in B2B sales utilizes three key areas of technology: predictive models, generative AI, and agentic AI. These technologies empower autonomous data-driven decision-making and automate sales processes.

Understanding these technologies will help you see where AI can add real value to your sales efforts.

Predictive AI

Predictive AI is powered by machine learning (ML) algorithms and natural language processing trained on your historical data to identify patterns and make predictions. For example, predictive AI may support sales forecasting by analyzing previous deals and providing accurate forecasts for your current pipeline.

The insights from these AI models allow sales teams to forecast sales volumes, identify trends, assess purchase likelihood, and predict churn risks.

For instance, by analyzing CRM data, an AI algorithm might reveal that deals between $500,000 and $1,000,000 close faster when clients request advanced customer support. Based on this, AI can predict which deals are likely to close quickly and suggest strategies to accelerate the sales process.

Generative AI

Generative AI, as defined by Gartner, refers to technologies that create new content, designs, recommendations, or workflows by learning from vast amounts of original data and utilizing Large Language Models (LLMs). LLMs are the technology that makes it possible to interact with AI in conversational language.

B2B sales teams are actively using generative AI, even though a comprehensive implementation for business automation is not yet widespread. According to McKinsey's B2B Pulse Survey, only 21% of commercial leaders report full enterprise-wide implementation of GenAI, while 22% are piloting specific use cases.

For example, one of the current use cases for GenAI in B2B sales is generating sales pitches. Generative AI can analyze client data, industry trends, and successful past pitches to craft compelling narratives that address specific client needs, offering variations to suit different stakeholders.

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Agentic AI

Agentic AI refers to advanced AI systems that can make decisions and take actions to achieve specific goals autonomously based on context and feedback. In sales, agentic AI can take over specific sales tasks or processes without human intervention. For that, it utilizes knowledge of some actions, workflows, components, etc. that are determined by the user through the system where it operates.

In B2B sales, agentic AI can function as a virtual sales assistant, taking ownership of lead scoring, nurturing, and contract finalization for specific deals.

For example, an AI assistant can autonomously manage the lead nurturing process, building a nurturing strategy based on AI insights and then following up on leads, engaging them, generating personalized emails, and providing supplementary materials, all without needing human input.

Let's dive deeper into the specific AI-powered B2B sales use cases and see what value this technology brings.

Top Use Cases for AI in B2B Sales

Autonomous prospecting

By analyzing historical data and large publicly available datasets, AI systems can independently identify leads that align with your ideal customer profile. They can evaluate their potential by looking at signals like website traffic and engagement patterns. Once a high-potential lead is identified, the AI system can automatically engage with them, sending personalized emails, following up with messages, or even scheduling meetings.

This automation allows sales teams to focus on closing deals and building relationships rather than manual prospecting, increasing the number of opportunities they can source.

Lead qualification

AI-powered lead qualification is more precise and more efficient than the manual process. An AI model trains on your data to independently assess the relevance and quality of all the leads entering your pipeline based on company size, industry, budget, and buying signals. It discards irrelevant prospects and provides you with a list of qualified leads ready to be engaged.

Lead scoring

AI allows for flexible, context-dependent lead scoring that ensures that your sales agents engage the highest-value leads at all times. Due to machine learning, AI systems are able to discover hidden patterns and alert agents to the best leads.

For example, AI might analyze past buying behavior in a specific industry and discover that certain companies are more likely to make large purchases in the third quarter. The tool will assign a higher score to those leads during the third quarter and your sales team can then concentrate on nurturing these high-potential leads.

Pipeline analysis

AI-powered pipeline analysis offers B2B sales teams an efficient way to manage and optimize their sales funnel. AI tools can continuously monitor the sales pipeline, identifying non-responsive leads and eliminating them to maintain a cleaner and more productive pipeline.

It can also detect where leads get stuck in the process, allowing sales agents to intervene at the right time. Beyond just alerting sales teams, AI can autonomously launch reengagement campaigns, such as sending personalized emails or scheduling follow-up calls, to revive stalled prospects.

Email generation

Generative AI can draft highly personalized emails based on previous interactions with prospects, your sales playbooks, and past emails written by sales reps. Instead of agents manually reviewing customer data or conversation histories, AI tools quickly analyze these details and craft perfectly tailored messages that resonate with each recipient. This not only saves time but also improves the effectiveness of outreach, helping sales teams deliver persuasive and relevant communication.

Meeting preparation

AI can be an invaluable tool for meeting preparation by gathering and analyzing critical information from multiple sources, including CRM data, social media activity, and publicly available information about the lead. It can generate detailed reports that highlight the client's key needs, pain points, and motivations.

When paired with your sales scripts and playbooks, AI also suggests personalized talking points and strategies with the highest likelihood of success, tailored to the specific data of the lead. This gives sales reps all the insights and support they need to engage effectively, increasing the chances of converting the lead into a customer.

Post-meeting CRM logging and task generation

AI can streamline data logging and CRM maintenance by analyzing client calls and emails and automatically converting them into actionable CRM entries. It can also generate tasks and action points, such as creating a plan for the rep to collect case studies from existing clients in the same industry, verifying the company’s road map, and scheduling the next meeting.

Some of these actions, like gathering relevant case studies and scheduling the next meeting, can be done autonomously by an AI assistant, while the sales rep can take care of more complicated tasks.

Lead management assistance

An AI assistant can significantly enhance lead management by tracking your pipeline in real-time and leveraging historical data to pinpoint critical moments. It can alert sales reps to high-priority prospects and the optimal times for engagement, ensuring timely follow-ups. It can also suggest the most impactful sales collateral for specific solutions or competitive scenarios. Furthermore, AI can advise on appropriate discounts, analyzing customer behavior and market trends to fine-tune incentives.

This AI-powered approach ensures that leads are engaged at the optimal moment, with personalized messaging designed to maximize impact.

Cross-/Up-selling

By analyzing customer needs and preferences, AI tools can automatically recommend additional products or a higher-tier product. The tool may highlight these suggestions for the sales rep or send an AI-generated automated email presenting all the options to a potential client. This way, some parts of the cross-/up-selling process, such as the initial proposal, can be automated by AI while human sales agents can focus on engaging and converting the lead.

Sales forecasting

AI-powered sales forecasting outperforms traditional methods by leveraging its ability to process vast amounts of data and adapt in real-time. This enables AI to deliver more accurate predictions that integrate multiple data sources and adjust dynamically based on market trends and changes in your sales pipeline.

Additionally, AI tools can quickly generate custom sales forecasts tailored to specific methodologies and datasets you choose. For sales teams, this simplifies the forecasting process and significantly increases the accuracy of forecasts.

Lead nurturing

AI-powered B2B sales software can effectively design and execute personalized lead nurturing campaigns for each prospect in your pipeline. AI analyzes customer data and identifies the most successful nurturing strategies based on historical performance with similar customer profiles. It then automates the entire process, from crafting customized marketing materials to scheduling meetings and engaging leads through online channels.

Sales reps are only notified when intervention is needed, such as when a lead fails to complete an important form or respond to an email. This automation significantly reduces the time sales teams spend on nurturing, ensures consistency, and minimizes the risk of losing leads due to human error.

Training your staff

AI can significantly enhance the training and development of sales teams through conversational intelligence tools. Generative AI coaching offers personalized, data-driven feedback, analyzing sales calls, comparing individual sales reps’ performance with top-performing colleagues, and providing tailored guidance for improvement. It can continuously assess seller activity, offering real-time coaching that aligns with each rep’s selling style.

Additionally, AI can identify essential skills for success and flag potential hires with matching capabilities, helping companies recruit top talent.

Pricing optimization

AI algorithms can suggest optimal pricing strategies for each customer based on the analysis of market data, customer behavior, and competitor pricing.

Knowledge management

AI assistants can help manage playbooks, best practices guides, pitch drafts, and presentations, suggesting the best-suited collateral for each engagement with a lead. AI can also generate case-specific articles based on CRM data, creating detailed use case descriptions that can be referenced for other deals in the future.

Digital seller

In the near future, AI agents may take over several aspects of the sales process, automating routine tasks and operating alongside sales agents, not just assisting them.

For instance, AI can engage and nurture lower-priority leads until they are close to making a purchasing decision, while human sales agents focus on high-value prospects that require more personalized attention and a human touch. This division of labor allows sales teams to operate more efficiently, maximizing the impact of both AI and human expertise in driving conversions.

Challenges of AI for B2B Sales

While AI can deliver significant value to B2B sales, there are challenges that may complicate its implementation and affect the effectiveness of AI tools. In this section, we will highlight several key aspects companies should consider when integrating AI into their B2B sales processes. Understanding these potential obstacles will help businesses better prepare for AI adoption and avoid common pitfalls and unsatisfactory results.

Poor data quality

AI models depend on accurate historical sales data to make predictions, generate content, and recommend next steps. The more well-documented your past deals are, the more precise and effective these AI-driven recommendations will be. Any inaccuracies or gaps in your data can lead to incorrect insights, erroneous forecasts, and crude content.

If your company struggles with data organization, it may be beneficial to first focus on improving data management using AI tools for gathering and logging CRM data. Establishing a clean, structured data foundation is crucial before implementing AI-powered automation or content generation solutions.

Privacy and information security

Like any system that handles sensitive company and customer information, AI software can pose security risks due to potential attacks and data breaches. Additionally, generative AI applications introduce unique vulnerabilities, as your data may be used to train LLMs, which can result in your confidential information and intellectual property being inadvertently included in the generated content accessible to external users.

To mitigate these risks, it's essential to choose AI software with robust security certifications and advanced protective measures. Additionally, carefully review the terms of service for applications utilizing generative AI to assess their privacy standards and the use of data.

Lack of AI governance

Many AI tools operate as "black box models," meaning their underlying technology is not transparent, making it difficult to understand their internal processes and decision-making. This lack of transparency can be problematic in complex B2B sales scenarios, where clarity is essential.

Furthermore, some AI systems lack comprehensive governance tools that allow users to monitor how the models function, potentially leading to unnoticed errors. For instance, you might not realize that a model was trained on insufficient data, resulting in skewed recommendations for a particular type of customer. Therefore, it is crucial to have robust governance tools in place to comprehend why AI models generate specific suggestions and to intervene if the model begins to get biased.

Poor implementation

Due to poorly planned implementation, many companies fail to fully utilize AI's potential. This often occurs when organizations select software that requires advanced technical expertise, attempt to deploy AI across multiple areas simultaneously, or fail to adequately train their sales teams on how to effectively use AI tools. These challenges can spread resources thin and end up in overspending.

Before purchasing AI-powered sales automation software, sales leaders should identify impactful use cases to test AI first. To ensure long-term value, it's helpful to research the investment strategies of their software providers regarding future capabilities. A clear implementation roadmap is essential to avoid technical debt and reduce costs.

Inaccuracies in generated content

The current state of GenAI models leaves room for improvement – occasionally they may make up facts, make reasoning errors, or generate output that represents social biases and world views derived from its training data. Make sure there are humans verifying generated results before they are sent to clients.

Many of these issues can be resolved by investing in a reliable and powerful AI solution.

How to Choose AI Software for B2B Sales

Here are some key tips to help ensure your AI implementation is successful and delivers the best results:

• Define use cases and scope: Start by identifying specific use cases for AI, such as sales forecasting or an AI-powered sales force automation (SFA) platform. Prioritize them based on business value, impact AI can make, time to value, and cost.
• Align AI with your sales objectives: Ensure that your AI tool supports key sales objectives.
• Involve sales teams: Include sales reps and subject matter experts in the selection process to ensure the tool complements existing sales workflows. Poor understanding of seller needs can lead to failed implementations.
• Research vendors: Check industry reports, customer reviews, and third-party evaluations. You can go with established vendors with proven ROI or choose new vendors offering trials or freemium products to minimize risk before committing.
• Determine budget and resources: Evaluate the cost of the tool against your available resources and budget. Plan for both the software and the required training and implementation resources.
• Opt in for an end-to-end integrated platform: Choose tools that can scale across your organization to prevent isolated solutions. Avoid a fragmented tech stack by ensuring the AI platform integrates well across departments.
• Assess data policies and security: Understand the data requirements for the tool, how it will be used, and ensure that customer and company data are properly protected. Choose vendors with robust security certifications.
• Test the tool before the purchase: Take advantage of free trials or freemium versions to test the tool’s functionality and fit before making a larger investment.

5 AI-powered B2B Platforms for B2B Sales

In this section, we want to highlight 5 AI-driven B2B sales systems that address a range of use cases. This brief list is compiled based on insights by industry analysts and is meant to be an introduction to the AI software available for B2B sales on the market.

Creatio

Creatio is a no-code AI-native platform to automate workflows and CRM. Its main advantage is the combination of no-code and AI, which empowers non-technical users to build custom CRM processes with incredible flexibility and time-to-value. Creatio AI helps you create new workflows and functionalities from no-code components based on your descriptions in natural language.

In addition to AI-powered no-code development, Creatio offers many out-of-the-box adjustable AI use cases for sales automation, including:

• AI-powered sales forecasting can be based on custom LLMs our ready-made algorithms to provide precise predictions.
• AI lead scoring prioritizes high-value leads based on your historical data and playbooks.
• Pipeline analysis shows in real-time what's happening with leads in your pipeline and highlights those that require your attention.
• Email generation utilizes generative AI to help you write personalized emails based on CRM data and sales enablement materials.
• Lead management automates lead engagement to ensure consistent communication.
• Next best actions recommendations provide sales agents with data-driven suggestions on steps to improve their chances of closing a deal.

Creatio AI offers significant support to sales managers and agents. It can quickly analyze and summarize a lead's journey, provide performance reports, and suggest actionable steps for improving your sales strategy. Users can simply input a request or ask a question, and Creatio AI responds with relevant information and materials, making it easier to understand your pipeline and take the right actions.

The platform is user-friendly and doesn't require extensive training while being incredibly customizable at the same time. In addition to CRM capabilities, it offers turn-key workflow automation for 10 industries including financial services, manufacturing, and insurance, and 700+ integrations and add-ons to connect third-party tools.

Creatio's AI capabilities are included in the base software along with a number of AI tokens. This makes AI-powered B2B sales automation available to any Creatio customer, no matter the tier of your subscription.

Pricing: The price for Creatio's no-code platform starts at $25 per user/month and the Sales Creatio product costs $15 per user/month. A free two-week trial is available.

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Allego

Allego is a comprehensive sales enablement platform designed to improve the way sales teams learn, collaborate, and sell. It combines a variety of AI features to support training, content management, and real-time sales coaching, allowing teams to be more efficient and effective.

Based on real-time data, AI agents provide personalized coaching, which is especially useful for companies that need to train remote teams or manage large sales forces. Sales simulations create realistic practice scenarios that help reps build confidence and improve selling skills.

AI-powered search enables sales reps to instantly find and access critical sales content, learning materials, and internal knowledge. Moreover, Allego equips sales teams with AI-driven recommendations, delivering tailored sales content and learning based on specific deal stages, customer industries, or product lines.

After customer interactions, Allego's AI call analysis provides actionable insights and recommendations for follow-up steps, helping to shorten sales cycles and improve the quality of future interactions.

Pricing: Pricing is available on request. Allego doesn't offer free trial.

Apollo

Apollo is a comprehensive sales tool designed to support prospecting, outreach, and engagement processes for B2B sales teams. It combines features like a lead database, CRM functionalities, and automation tools to help sales professionals discover new leads, manage relationships, and streamline their workflows.

Apollo's AI covers four major use cases for sales automation:

• Lead scoring based on historical CRM and Apollo data to prioritize the best-fit leads.
• Enhanced email writing through AI-driven personalized recommendations, rephrasing, and message analysis.
• Automated outreach with AI-assisted sequences and personalized and well-timed touchpoints.
• Sales conversations’ analysis that transcribes and summarizes key insights, providing sales teams with actionable follow-ups to improve win rates.

Pricing: Apollo's pricing starts at $49 per user/month. There's a free version available that includes AI-assisted email writing and limited workflow automation capabilities.

Gong

Gong is a revenue intelligence platform designed to help sales teams improve their performance by providing deep insights into customer interactions. It uses AI to analyze conversations across multiple channels and extract insights that can enhance sales strategies.

Gong tracks all interactions with potential customers throughout the sales pipeline, identifying at-risk deals, highlighting critical moments, and helping sales leaders manage their pipeline more effectively.

Additionally, Gong provides data-driven coaching insights based on conversations with top-performing sales reps.

Pricing: Gong's pricing is available on demand. The vendor offers a free trial.

Second Nature

Second Nature is an AI-powered sales training platform that helps sales teams improve their skills through interactive, lifelike simulations. Its core technology is called Jenny, a virtual sales coach designed to mimic real-world sales conversations. Jenny engages sales reps in realistic role-playing scenarios, providing feedback and guidance in real-time.

Key advantages include real-time feedback on performance, personalized coaching tailored to individual needs, and progress tracking to highlight areas for improvement. By using Second Nature, companies can boost the confidence of their sales reps, ensure consistent messaging, and reduce ramp-up time for new team members.

Pricing: Pricing is available on request. The vendor offers to try simulations experiences with Jenny for free.

Enhance Your B2B Sales with AI-native No-code Platform

More and more companies are implementing AI for B2B sales, with sales and marketing seeing the biggest jump in adoption in the last year. AI in B2B sales can greatly increase your sales teams’ productivity, save resources, and boost revenue by automating insights' mining and workflows.

To stay ahead of the competition you need to carefully evaluate AI use cases that can bring you the most value and select the right AI platform. The combination of powerful AI features and no-code allows Creatio to provide and easy-to-use customizable platform with state-of-the-art AI capabilities for sales automation. Sign up for a free trial and see how Creatio can empower your sales teams.