AI for sales prospecting: use cases, tools, and tips

Each week, sales reps spend 70% of their time on something other than selling. 

What if AI could help change that?

Increasingly, sales teams are scaling their AI usage with valuable sales assistants that help them automate many recurring prospecting tasks, like researching potential customers, identifying the right leads at the right time, and scaling personalized messaging, so they can spend more of their weeks doing what humans do best: closing.

How to use AI for sales prospecting

AI sales prospecting tools are powered by a myriad of technologies including machine learning (ML), next-generation data analysis, and natural language processing (NLP). AI-powered prospecting tools can help reps find, qualify, and engage leads faster than ever before. 

These days, customers increasingly expect personalized experiences. Without the right sales tools, that’s a tall order for reps who are super busy and spend most of their time dealing with indirect or non-sales activities. 

This is an area where AI sales prospecting tools can be an absolute game-changer. According to HubSpot data, 81% of reps say that AI helps them spend less time on manual tasks while 78% say the technology enables them to work more efficiently. 

The bottom line? By incorporating AI sales prospecting tools into their tech stacks, sales teams can spend less time researching prospects and handling administrative tasks, giving them more energy to invest in selling.

AI sales prospecting use cases

Wondering how to use AI for sales prospecting? There’s no shortage of ways.

Versatile by design, AI prospecting tools have the power to transform workflows by helping sales professionals manage a variety of critical tasks:

• Automating prospect research. By automatically pulling data from places like LinkedIn, news publications, and company sites, AI can help reps surface key insights relating to roles, whether a prospect aligns with the ideal customer profile (ICP), and what their potential pain points might be.
  
  
• Personalizing sales outreach at scale. Using AI, reps can generate personalized emails based on prospect attributes, interests, and behaviors in just a few clicks.

• Prioritizing the best leads. Using unique lead scoring models, AI can automatically rank prospects based on their likelihood to convert. As a result, reps can spend more time focusing on the best leads and less on cold outreach.

• Identifying buying signals in real time. AI sales tools can track intent signals, like content engagement, website visits, and demo requests, and notify reps when prospects are ready to make a purchase.

• Summarizing conversations. AI can automatically transcribe calls and summarize conversations, creating easy-to-read summaries and highlighting key takeaways. At a glance, reps can identify objections, see action items, and AI-generated next steps. 

• Saving time on meeting prep. Using these summaries, reps can brush up on previous conversations and prepare for meetings. They can also suggest talking points, likely objections the prospect might have, and any relevant content to share ahead of the call. 

• Improving social selling. By monitoring social platforms for company news, job changes, and other relevant posts, AI can help sales teams improve social selling, recommending relevant ways to engage prospects on social media.

• Building lead lists. AI can automatically find prospects based on ICPs and other criteria, automatically filling in contact info, demographic, and firmographic data.

• Automating follow-up email reminders. The tech can also suggest the best time for follow-up messages, along with what those messages should contain based on previous interactions with the prospect. 

• Forecasting pipeline quality. Prospecting AI can automatically analyze leads to predict close probability and sales velocity, flagging any at-risk opportunities early on to help reps focus on the most important prospects.

Pros and cons of AI sales prospecting

While AI has the power to transform the way your sales team operates, it’s not without its challenges. Just ask Cursor, whose AI customer support bot falsely told users they could no longer use the software on multiple devices. 

Before you start using AI to supercharge your sales efforts, it’s important to understand the pros and cons of the technology so you avoid potential pitfalls.

Pros of AI prospecting tools

• Time savings. By automating prospecting tasks, including research and follow-ups, AI helps reps spend more time with leads.
  
  
• Improved lead targeting. AI uses data to identify high-intent prospects, enabling reps to spend their time more effectively while removing guesswork from the equation. 
• Personalization at scale. In just a few clicks, reps can create personalized emails based on unique prospect behaviors, circumstances, and traits.
• Real-time insights. AI automatically flags buying signals — think email opens and website visits — ensuring reps can follow up with leads as quickly as possible.
• Improved pipeline forecasting. Leveraging predictive analytics, sales managers can get a better understanding of which deals are most likely to close, which reps need support, and where to focus for maximum impact.

Cons of AI prospecting tools

• Hallucination risk. AI can produce false information, so avoiding these errors requires human oversight, especially in the early stages of design and usage. 

• Automation fatigue. If AI-generated messages are too obvious, prospects might ignore them. At the end of the day, people still prefer buying from people..

• Privacy concerns. In addition to ensuring that data collected on prospects and customers is held in a compliant and secure manner, organizations also need to make certain that the AI safeguards important internal data (e.g., intellectual property and trade secrets). 

• Requires clean data. AI is only as effective as the data that powers it. For this reason, organizations need to make sure the data they’re using for AI is highly accurate.

• Upfront training and configuration. You can’t just deploy AI and expect great results. Success starts with training your team to use the technology productively and tuning the system so it supports your unique business goals.

6 best AI sales prospecting tools

With the right tools, AI sales prospecting can help your sales org unlock its full potential. With that in mind, let’s examine six popular AI sales prospecting tools on the market today to give you a better idea of what’s available.  

1. LeadIQ

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G2 score: 4.2 out of 5 stars (1,095 reviews)

LeadIQ is a sales prospecting platform designed to help reps accelerate prospecting workflows, personalize outreach at scale, automatically enrich contact data, and track buying signals.

LeadIQ features:

• Top-rated global company and contact data 
• Identify potential leads that match your ICP
• Automatic data enrichment for website form fills and other prospect actions
• GenAI-powered email creation with Scribe
• Automated company, contact, and champion tracking

LeadIQ pros:

• Easy to use with intuitive, user-friendly design
• Comprehensive contact data, including EMEA data, that’s highly reliable
• Easy to implement for rapid ROI

LeadIQ cons:

• Can be expensive for small teams (try our free Chrome extension if that’s you!)
• Works best in conjunction with other tools like LinkedIn Sales Navigator, Salesforce, HubSpot, Gong, Outreach, and Salesloft2. Salesforce Agentforce

LeadIQ use cases:

• Sales prospecting automation
• Tracking sales triggers (e.g., champion tracking)
• Data enrichment

2. Salesforce Agentforce

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G2 score: 4.4 out of 5 stars (129 reviews)

Salesforce Agentforce is enables sales teams to create autonomous AI agents that can handle a variety of SDR tasks on their own, including lead management and qualification, without human intervention. Using Agentforce, reps can write prompts to create and extend agents trained on CRM data, with little to no coding required.

Agentforce features:

• Build AI agents in a few clicks, without needing to know how to write code or understand machine learning
• Create custom guardrails to ensure agents operate within boundaries you define while keeping data secure
• Enlist Salesforce Professional Services to get expert insights into how you can accelerate your business with agentic AI and get up and running within four weeks

Agentforce pros:

• No-code/low-code capabilities with drag-and-drop simplicity to customize AI agent behavior to specific use cases 
• AI agents help reps write emails, summarize meetings, offer real-time assistance, and far beyond
• Always-on agents that can answer questions, identify dissatisfied customers and address their concerns, troubleshoot issues, process payments, and more

Agentforce cons:

• A bit of an initial learning curve, with users reporting that initial implementation and setup and be hard to get completely right on the first few tries
• Variable pricing at $2/conversation, which can be expensive for budget-conscious teams

Agentforce use cases:

• Lead management and qualification
• Upselling and product recommendations
• Website chat

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3. AiSDR

G2 score: 4.7 out of 5 stars (51 reviews)

AiSDR is an AI-powered SDR assistant that automates sales prospecting workflows by booking meetings, generating leads, and engaging prospects with personalized emails. With deep prospect research, the ability to surface prospects that align with your ideal customer profile, and automated follow-ups, AiSDR increases outbound sales efficiency and helps teams focus on what matters most: closing deals.

AiSDR features:

• Reactivate closed-lost deals by automatically reinitiating conversations with prospects who declined your offer in the past and picking up right where you left off
• Increase email deliverability by automating mailbox setup and email warm-up

AiSDR pros:

• Designed using proven tactics, frameworks, and best practices recommended by more than 50 sales experts
• Omnichannel outreach, with agents engaging prospects across email, LinkedIn, and text and even creating personalized scripts to assist reps on phone calls
• Integrations with Calendly, Google Workspace, HubSpot, LinkedIn Sales Navigator

AiSDR cons:

• Initial setup and configuration can be time-consuming and resource-intensive for some teams
• Can be pricey, starting at $900 per month for 1,000 emails sent
• Some users report a lack of customization options

AiSDR use cases:

• Book sales meetings automatically
• Find users of competing technologies and try to win their business 
• Engage accounts that fit your ICP, asking qualifying questions, answering inquiries, and handling objections

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4. Customers.ai

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G2 score: 4.8 out of 5 (429 reviews)

Customers.ai is an AI sales and marketing platform that helps businesses identify anonymous website visitors and turn them into qualified leads — and ultimately customers.

Customers.ai features:

• Identify anonymous website visitors accurately to generate more revenue by converting otherwise untrackable users into customers
• Integrations with popular sales channels, including Shopify, Google Ads, and Meta Ads, which makes it easier to launch successful remarketing campaigns

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Customers.ai pros:

• Sync anonymous website data directly to Meta for more precise ad targeting (helpful for B2C in particular),
• Claims to be the considerably more accurate that the average website de-anonymization service
• Reduce email spam rates 5x by learning who anonymous website visitors are and avoid being marked as spam

Customers.ai cons:

• Learning curve, with users reporting the platform has seemingly endless configurations, which can feel intimidating when you’re starting out
• Customer support may be lacking
• Can be costly for small teams

Customers.ai use cases:

• Website visitor identification
• Abandoned cart recovery
• Email marketing and deliverability

5. Clay

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G2 score: 4.9 out of 5 stars (154 reviews)

Clay is an automated data enrichment, outreach, and research platform that uses AI to help to-to-market teams build targeted lead lists and automate sales prospecting workflows. 

Clay features:

• Automate CRM data enrichment from over 130 separate data sources
• Save time and ditch manual research with AI agents that find information on their own and bring it back to the team
• Use AI formulas to create conditional workflows that save money and ensure each lead follows the most appropriate enrichment steps (e.g., only looking for phone numbers if business emails can’t be found)

Clay pros:

• Workflow automation, with a community directory of plug-and-play “Claybooks” that help teams streamline repetitive tasks and reclaim time
• Automatic lead scoring that leverages over 100 data providers and Clay’s AI research agents to help reps learn as much about prospects as they can
• Solid customer support, with a Slack community of more than 20,000 users

Clay cons:

• Learning curve for some users; implementation can be tricky and initial usage can eat up credits as teams learn how to use the platform
• Advanced features are only available in premium tiers, which start at $134/month

Clay use cases:

• Automatic data enrichment
• Data management & hygiene
• Lead scoring

6. Gong

G2 score: 4.8 out of 5 stars (6,201 reviews)

Gong is a revenue intelligence platform that uses AI to analyze sales conversations, extract actionable insights, and provide real-time coaching recommendations for better sales outcomes.

Gong features:

• Detect buying signals automatically using Gong Agents, which identify risks, trends, and concepts beyond simple keyword matching
• Sales forecasting tools that are AI-powered and pull data from over 300 signals to more accurately predict sales outcomes
• AI-powered pipeline management that enables teams to quickly inspect deals, access associated customer insights, and see where the pipeline stands at any given time

Gong pros:

• Enrich prospect data thoroughly with first-party interaction data and signals pulled from Gong’s robust partner ecosystem
• Spend more time building relationships and selling with AI-recommended actions and a chatbot that will tell you anything you want to know about specific accounts
• Real-time view into customers, prospects, and revenue with a centralized analytics dashboard that tracks the metrics that matter most to your team

Gong cons:

• Pricing information isn’t available on the website
• Some users report AI inaccuracy & AI limitations

Gong use cases:

• Sales coaching
• Sales forecasting
• Deal execution

How to evaluate AI prospecting tools

While AI sales prospecting tools can revolutionize the way your team sells, not every solution is created equal. With tons of tools on the market today, it’s important to do your due diligence to ensure you end up with a solution that fits your team’s needs best.

By following these seven steps, you can increase the chances you end up with an AI prospecting system that really moves the needle.

Step #1: Define clear objectives

First things first: What do you hope to accomplish by investing in AI sales prospecting tools? Do you want to streamline research? Automate cold email outreach? Figure out which high-quality leads to target first? Are you trying to help reps optimize workflows and work more productively? Worried about growing the sales pipeline?

Whatever the case may be, you need to define your north star and then set measurable goals to track your progress. For example, maybe you want to improve cold outreach conversion rates, increase meetings scheduled, or accelerate time to first contact. 

Once you’ve defined your objectives, start looking for tools with use cases that address your team’s pain points. Don’t buy AI for the sake of buying AI; invest in something that can truly lead you to better business outcomes.

Step #2: Assess internal readiness

After you understand what you hope to accomplish with AI, it’s time to look inward to determine whether your organization is ready to unleash the next-gen technology.

To do this, evaluate your current sales processes, team bandwidth, and data infrastructure to make sure everything’s ready for AI. Are your reps tech-savvy enough to roll with the punches and use new tools? Or will you need to train them?

Pro tip: Before investing in AI, examine the tools already in your stack to see if any of them offer AI-powered features. Over the last few years, all sorts of vendors — like Salesforce, HubSpot, and LeadIQ — have added AI to their platforms. Translation: You might already have access to AI tools without even realizing it!

Step #3: Involve key stakeholders

Sales leaders might pick what they think is the best tool on the planet. But if it doesn’t meet your team’s needs, or if nobody wants to use it, what’s the point?

Before making a decision, bring relevant stakeholders to the table, including sales, operations, marketing, IT, and leadership, to get their input. Putting a cross-functional team together increases the chances the tool you ultimately select will solve real problems and have buy-in from the team, all while having IT’s blessing.

Step #4: Create a feature checklist

Based on your objectives, figure out which features are must-haves and which are nice-to-haves. For example, you might want a tool that integrates with your CRM and can accelerate lead generation efforts. The ideal solution might also ship with automation capabilities, including automatic data enrichment, and built-in compliance support.

By figuring out which features are essential to your goals, you can start narrowing down your short list as you compare different offerings and cross off the ones that don’t have the capabilities you need.

Step #5: Request demos and trials

Now that you’ve selected a few finalists, it’s time to engage with vendors for a trial. While you’re testing each platform, explore realistic use cases to assess the platform’s user experience and simulate what real-world performance might look like.

For the best results, invite some folks who’ll ultimately end up using the software to get involved. Pick their brains to see whether the tool is making a difference.

Step #6: Evaluate vendor reputation and customer support

After you’ve seen the products with your own eyes, spend time reading reviews on sites like G2 and TrustRadius to see what real-world customers have to say about each of them — specifically about how the tool has been beneficial and what the support experience is like.

When it boils down to it, a tool is only as good as the company behind it. So, make sure the platform you ultimately select is built and supported by a talented and responsive team.

Step #7: Analyze cost versus value

Before finalizing a decision, consider pricing models in the context of potential ROI, and make sure you understand how each vendor charges (e.g., a flat fee or usage-based billing). 

On one hand, you need to determine whether a more expensive solution is justified because it can deliver measurable business outcomes. On the other, you want to make sure that you don’t choose a solution that ends up hitting you with tons of hidden fees. 

Test drive LeadIQ’s AI prospecting capabilities today

Here at LeadIQ, our sales team uses AI every day across the funnel to cover more ground and win more business, including being our own customer zero. 

We use our own product every day and our team is currently hard at work adding new AI-powered features to LeadIQ to make it even easier for our sales team to crush their numbers — and help your team do the same.

Request a demo today to learn more about how you can transform the way you prospect with better data, faster enrichment, and write personalized sales emails using real data.