How Sales Can Use AI Sales Agents … Right Now
AI has transformed how sales teams operate. In just a few short years, sales leaders have gone from asking whether they should use AI at all to how sales can use AI sales agents to drive real results.
Here’s the difference: Unlike prompt-based generative AI, agentic AI doesn’t wait for instructions. It acts autonomously. It analyzes, plans, and executes on its own to move sales forward.
And this next wave of AI is growing quickly. Gartner reports that while fewer than 1% of enterprise software applications included agentic AI in 2024, that number will jump to 33% by 2028, enabling 15% of day-to-day work decisions to be made autonomously. And Precedence Research projects the AI agent market will surge from $5.43 billion in 2024 to more than $263 billion by 2034.
For sales leaders, these numbers aren’t just predictions—they’re a wake-up call. What makes agentic AI so different from generative tools like ChatGPT? What are the most practical use cases for sales teams? And how can you start using AI sales agents today? Let’s explore.
What Are AI Sales Agents?
AI sales agents are like digital teammates who don’t wait for instructions. Instead of sitting idle until you prompt them, they dig into your sales and customer data, figure out what needs to happen next, and do it.
It’s important to note they aren’t here to replace your reps. They’re copilots. While your sellers focus on building relationships and closing deals, AI sales agents handle the grunt work: prospecting, qualifying, scheduling, and following up.
AI sales agents are digital teammates that anticipate what needs to happen next and take action for your sales team.
The difference from tools like ChatGPT is huge. Generative AI gives you an answer when you ask for it. AI sales agents go further, anticipating what’s needed, making a plan, and taking action on their own.
One sales rep, writing on Reddit, summed it up perfectly: These agents can “prepare, warm, and verify leads,” but when it comes to closing, the handoff to a human is what seals the deal.
Unlock the Future of AI in Sales Enablement
Discover how sales teams are using AI to boost efficiency, improve coaching, and accelerate revenue growth. Get the latest insights in Allego’s 2025 AI in Revenue Enablement Report.
Types of AI Sales Agents and Deployment Models
Not all AI sales agents look the same. Most fall into one of two categories: standalone tools or enterprise platforms with agents built in.
1. Standalone AI Sales Agents
Standalone AI sales agents are single-purpose tools designed to handle specific sales tasks, such as writing emails, scheduling meetings, or qualifying leads.
Because they’re focused on a single task, standalone agents are often more affordable and quicker to test than enterprise platforms. However, integration with your current systems can still be a hurdle, and adding too many standalone tools can create a fragmented workflow.
Here are a handful of standalone AI sales agents on the market today:
- Conversica: These AI sales agents qualify leads, reengage customers, and resolve issues.
- Lavender: Lavender agents help SDRs and AEs write emails, score emails, and suggest improvements.
- Regie.ai: Auto-Pilot AI agents can identify prospects, write personalized messages, and manage outreach sequences.
2. Enterprise Platforms with Built-in AI Agents
On the other end of the spectrum are full-scale platforms that come with AI agents as part of their larger suite of features. These tools go beyond one-off tasks and tie into your CRM and enablement systems for broader impact.
The advantage is that these platforms connect more deeply with your systems, often leading to cleaner data, shorter deal cycles, and more consistent coaching.
Examples include:
- Allego – Combines training, sales coaching, conversation intelligence, and sales content management, with agents for role-plays and dynamic recommendations.
- Salesforce Einstein – Delivers CRM-native predictions and personalized recommendations.
- Outreach – Provides AI-driven insights and engagement to optimize GTM workflows.
Standalone AI Sales Agents vs. Embedded: How to Choose
So which option is right for your team—a standalone AI sales agent or an enterprise platform with agents built in? The answer depends on your goals, budget, and how your sales organization is set up. Here are a few factors to weigh:
- Budget – Standalone tools usually have a lower upfront cost, which makes them easier to get approved and pilot. Enterprise platforms can deliver bigger long-term impact, but you’ll need more investment to get started.
- Goals – If you’re solving one specific problem—say, improving email outreach—a specialized standalone tool may be enough. If you want to improve efficiency across the entire sales cycle, an embedded platform is the better bet.
- Tech Stack – Look at the systems you already have. Will this new tool replace something, or just add another layer? Standalone tools can create overlap if you’re not careful, while enterprise platforms may simplify things by unifying data.
- Team Size – Small teams often benefit from standalone tools because they’re quick to spin up. Larger, more complex teams typically see more value from enterprise platforms that can scale and integrate deeply.
- IT Support – A standalone tool might require lighter IT support, but don’t underestimate integration needs. Enterprise platforms demand more upfront resources but can pay off in cleaner, more reliable data once fully in place.
The bottom line: if you’re testing the waters, start small with a standalone tool. If you’re ready to transform the way your sales team operates, consider an enterprise platform that brings everything under one roof.
How Sales Can Use AI Sales Agents: 6 Practical Methods
AI sales agents aren’t just hype. They’re already driving measurable results. In fact, SuperAGI found companies using them boosted sales efficiency by 30% and cut operational complexity by 25%. So, what does that look like in practice? Here are six real-world ways your team can start putting AI sales agents to work right now.
1. Automated Prospect Outreach and Follow-up
Researching prospects and following up takes massive time. Yet 80% of sales happen between the fifth and 12th contact. AI agents like Regie.ai or Lavender can take those first touches off your plate by sending personalized cold emails, adjusting tone based on buyer behavior, and keeping conversations moving until your reps step in to build the relationship and close the deal.
2. Lead Qualification and Scoring
Few things frustrate reps more than spending time on bad leads. Conversational AI agents from Drift or Conversica can engage prospects right away, ask qualifying questions, and pass along only the opportunities worth pursuing. The result is less wasted effort and more focus on real prospects.
3. Scheduling Meetings
Even with scheduling tools like Calendly, coordinating calendars takes time. AI sales agents like Chili Piper and Kronologic simplify the process. They automatically book meetings with the right rep or even send a calendar invite as the first outreach—cutting down on delays and missed opportunities.
4. Role-Playing and Coaching
Practice builds confidence, but it’s not always easy to arrange. AI-driven role-play simulators, such as Allego’s Live Dialog Simulator, give reps a safe place to practice conversations and receive immediate feedback. New hires get up to speed faster, and experienced reps can keep their skills sharp.
5. Conversation Intelligence
Listening to hours of recorded calls isn’t practical for most managers. Conversation intelligence tools use AI to summarize discussions, highlight risks, and suggest coaching points. Reps get timely feedback, and managers can focus on the areas that matter most.
6. Reengagement of Dormant Leads
Your CRM is full of leads that went quiet. AI sales agents can scan that data, find the ones most likely to reengage, and send tailored outreach. Tools like Realoq’s RE-Engage and Synthflow AI Voice help bring those prospects back into the pipeline without adding work for your reps.
5 Benefits of AI Sales Agents
A January 2025 Gartner poll found that nearly 20% of organizations have already made significant investments in agentic AI, with another 42% making more conservative moves. Why are companies leaning in? Because AI sales agents deliver benefits that directly impact sales performance.
- Greater Efficiency
Reps spend less time on repetitive, low-value work—like combing through CRM data or sending routine follow-ups—and more time on conversations that drive revenue. - Faster Lead Response
In sales, speed matters. McKinsey found that 40% of customers expect a business to respond within an hour, and nearly 80% expect it within 24 hours. AI sales agents can respond instantly, keeping leads engaged before interest fades. - Scalable Personalization
Personalized outreach works, but it takes time. AI agents can tailor emails and messages automatically, giving prospects the individualized experience they expect—without requiring hours of manual effort from reps. - Always-On Coverage
AI agents don’t sleep. They can follow up, answer routine questions, or qualify leads around the clock, ensuring opportunities aren’t missed when your team is offline. - More Time for Selling
The biggest benefit is focus. When AI agents handle the admin work, reps get back the time they need to build relationships, earn trust, and close deals.
Challenges and Considerations of Agentic AI
Agentic AI brings a lot of promise, but it’s not without challenges. As Gartner’s Anushree Verma cautions, leaders need to “cut through the hype” and make smart, strategic choices about how and where they apply this technology.
The most common concerns include:
- Quality of results: Will the AI’s output be accurate, useful, and human-sounding—or will it miss the mark?
- Fit with sales and marketing: How well do AI agents align with the processes and materials your marketing team has already built?
- Impact on people: How will these tools change a rep’s day-to-day experience? Could they cause anxiety about being replaced?
- Technical, security, and compliance risks: From data privacy to integration with complex CRMs, there are serious questions to address before rolling out at scale.
The best way to manage these challenges is with a thoughtful rollout:
- Start small by piloting one low-risk use case.
- Involve IT, enablement, and sales ops early to ensure security and adoption.
- Be transparent with reps about what the AI will and won’t do. (It’s there to take work off their plate, not replace them.)
Handing over tasks to an autonomous tool can feel uncomfortable at first. But remember: AI is just that—a tool. The goal isn’t to replace your sales team; it’s to give them back the time and focus they need for the parts of selling that only humans can do.
How Sales Can Use AI Sales Agents: 8 Steps to Get Started
Rolling out AI sales agents doesn’t have to be overwhelming. The best approach is to start small, prove value, and then build from there. Here’s a step-by-step process that works:
- Assemble a decision-making team: Bring in sales enablement, IT, and sales ops early. They’ll help ensure security, adoption, and integration.
- Pick one task to automate: Start with something low-risk but time consuming, like scheduling or lead qualification.
- Choose a tool to test: Select an AI sales agent designed for that task, and make sure it fits into your existing workflow.
- Run a trial or demo: Use a pilot program to see how it performs in real situations.
- Test with a small group: Roll it out to a handful of reps first so you can catch issues early.
- Track results and feedback – Look at both the numbers (efficiency, conversion) and how reps feel about using it.
- Refine your approach: Adjust workflows, settings, or training before scaling.
- Expand gradually: Once you’ve proven success, roll it out to more teams and add additional use cases.
Some beginner-friendly platforms to explore include SalesGPT (open-source, sales-focused workflows), Knotie-AI (voice engagement with strong data transparency), and Allego (real-time, embedded sales enablement agents).
The key is not to rush. By piloting carefully and building trust with your reps, you’ll create the foundation for long-term success with AI sales agents.
Practical Agentic AI Is Here (to Stay)
Autonomous AI sales agents may sound futuristic, but they’re already part of how modern sales teams work. This isn’t something to put off for later—teams using AI agents today are reclaiming hours, generating more qualified leads, and improving productivity.
You don’t need to overhaul your entire sales process to see results. Start small. Automate one task. Prove the value. Then expand. Along the way, keep your reps front and center—because AI is at its best when it supports, not replaces, the human side of selling.
The teams that figure out how sales can use AI sales agents effectively today will be the ones setting the standard tomorrow.
About the Author: Jeremy Bender is Director of Sales Enablement at Allego. As such, he is an in-house resident expert on the revenue enablement landscape and is responsible for equipping Allego’s go to market teams to provide solutions to our customers.
Unlock the Future of AI in Sales Enablement
Discover how sales teams are using AI to boost efficiency, improve coaching, and accelerate revenue growth. Get the latest insights in Allego’s 2025 AI in Revenue Enablement Report.
FAQ: AI Sales Agents
- What is an AI sales agent?
An AI sales agent is an autonomous tool that uses AI to handle sales tasks like outreach, lead qualification, scheduling, and follow-up—freeing reps to focus on selling. - How are AI sales agents different from tools like ChatGPT?
ChatGPT responds to prompts, while AI sales agents act on their own. They analyze data, anticipate needs, and take action without waiting for instructions. - Will AI sales agents replace human sales reps?
No. They’re designed to be copilots, not replacements. AI sales agents handle repetitive tasks, while humans focus on building relationships and closing deals. - How can sales teams get started with AI sales agents?
Start small by automating one simple task—like scheduling or lead qualification—test a tool with a small group, measure results, then expand from there.
