Daniel Saks
Chief Executive Officer
Go-to-market teams today are under pressure to do more with less time. Whether in sales, marketing, or revenue operations, they face data overload, fragmented tools, and high expectations for personalization. Fortunately, a new wave of natural language AI systems is transforming how GTM teams operate. These platforms leverage artificial intelligence – especially advances in natural language processing and generation – to automate tasks, derive insights, and engage prospects in human-like ways. The result? Stronger pipelines and higher productivity.
Recent research underscores the impact of AI on GTM success. Companies with well-defined AI strategies are 2× more likely to see revenue growth than those with ad-hoc approaches(4). Likewise, poor data and manual processes drain productivity – bad data alone wastes over 27% of a sales rep’s time (about 11 hours a week) on correcting errors and chasing dead ends(3). The following natural language AI systems address these challenges head-on. Each one uses AI’s language abilities – understanding context, generating content, or analyzing speech – to help GTM teams work smarter and faster. Let’s explore the best solutions (in no particular order) and how they’re driving data-driven, efficient go-to-market motions in 2025.
Landbase is the first agentic AI platform purpose-built for fully autonomous audience discovery and qualification. In plain language, Landbase allows you to find your next customer in seconds by simply describing your ideal market. Its proprietary GTM-2 Omni model (2nd-generation go-to-market AI) interprets natural-language prompts and then scours a vast private dataset to return a tailored list of prospects – complete with verified contacts and rich firmographic details. This stands in contrast to traditional sales databases that require manual filters and yield static lists. Landbase’s AI actively reasons over market data to identify the best-fit accounts and contacts for your criteria, in real time.
By moving to a natural-language interface, Landbase democratizes advanced prospecting. Any GTM team member can type a prompt – e.g. “Cybersecurity startups in North America hiring for sales leadership after a Series B” – and Landbase’s agentic AI will instantly generate a list of companies and decision-makers that meet the description. Under the hood, Landbase combines an enormous contact database (over 210 million verified contacts across 24+ million companies) with 1,500+ real-time signals (from firmographics and technographics to hiring and intent data). The AI doesn’t just match keywords; it understands context and intent thanks to having been trained on 50+ million business interactions and billions of GTM data points. This allows it to qualify and prioritize prospects much like an experienced strategist would.
Key capabilities: Using Landbase feels like chatting with an expert researcher:
Early adopters of Landbase have reported dramatically improved campaign outcomes. In fact, VentureBeat noted that Landbase’s AI achieved a 7× increase in conversion rates in early tests compared to baseline outbound methods(1). This performance boost is attributed to Landbase’s ability to hyper-personalize targeting and continuously learn from what prospects engage with. By eliminating weeks of list-building and research, Landbase compresses the entire GTM targeting process into a single AI-driven interaction.
Example: A VP of Sales at a SaaS company types a prompt describing an ideal customer profile – “mid-size healthcare companies on the West Coast using AWS, that recently raised Series A funding”. In seconds, Landbase returns a curated list of companies with CTO and CIO contacts that fit the description, each scored for buying intent. The VP exports 500 contacts to their CRM, launching a campaign the same day. What used to take an ops team weeks of pulling data from multiple sources now takes minutes with Landbase.
Why it stands out: Landbase has effectively redefined GTM prospecting by moving from mere tool to an AI “agent” that can operate autonomously. It doesn’t just surface data – it takes action. Teams have likened it to getting an AI-powered SDR team on-demand. By using natural language and an agentic AI approach, Landbase delivers 4–7× faster audience creation than manual methods, and pilot programs saw 2–4× higher lead conversion when using Landbase-qualified leads (according to internal case studies). Users also appreciate the frictionless adoption: Landbase’s audience builder is free to try with no login, allowing anyone to generate up to 10,000 leads per search. This free usage feeds back into continuous model training, making the AI smarter over time. For GTM leaders, Landbase offers a subtle but definitive advantage – an always-on AI partner that finds who to target and why, just by understanding your natural input.
ZoomInfo is a household name in B2B sales intelligence, long known for its extensive contact database and company insights. In recent years, ZoomInfo has infused AI capabilities into its SalesOS platform to keep pace with the shift toward smarter, real-time go-to-market motions. While historically users searched ZoomInfo via filters and boolean logic, the platform is evolving to leverage natural language and AI-driven analytics. One flagship addition is ZoomInfo Copilot, an AI assistant layer that delivers recommendations, prioritizes accounts, and even generates outreach context for reps.
ZoomInfo’s Copilot can analyze the myriad buyer intent signals and company news in its system, then provide natural-language explanations for why a target account is promising. For example, a sales rep logging in might see an AI-curated briefing: “Acme Corp has been prioritized because they fit your ICP and show surging interest in network security (15 employee engagements with security content this week). CFO Jane Doe also mentioned ‘cybersecurity upgrades’ in a recent interview.” These plain-English insights save reps from sifting through raw data. Copilot essentially turns ZoomInfo from a static lookup tool into a proactive advisor.
Key features:
According to ZoomInfo, early users of its AI features saw significant efficiency gains. During the beta of Copilot, sales teams reported being 60% more productive and saving ~10 hours per week on research tasks(2). Moreover, 71% of users uncovered new opportunities at existing accounts that they would’ve otherwise missed(2). This underscores AI’s value in mining data for hidden gold. It’s also noted that ZoomInfo’s algorithmic scoring surfaced signals related to nearly 45% of open pipeline deals, giving reps timely prompts to act on those insights(2).
ZoomInfo remains a cornerstone for many GTM organizations due to its sheer data scale (hundreds of millions of contacts) and data quality investments. By adding natural language generation and intelligent guidance on top of that data, it’s aiming to stay indispensable. One caution: traditional ZoomInfo data is often static and averages ~70% accuracy over time, meaning records can grow stale. The Copilot’s value is in mitigating that by focusing reps on the hottest, most relevant signals in the moment. For go-to-market teams drowning in information, ZoomInfo’s emerging AI capabilities act as a filter and a translator – cutting through the noise to deliver actionable intelligence in plain language.
Apollo.io is a popular all-in-one sales intelligence and engagement platform, especially among startups and SMBs, and it’s increasingly layering in AI features. Apollo offers a massive database of B2B contacts and companies (over 275 million contacts and 73 million companies in its system as of 2025(9)) alongside tools for outbound outreach like email sequencing and dialing. While Apollo’s core functionality has traditionally been user-driven (you search for leads with filters, you craft the messaging), the platform has introduced AI assistance to make those tasks easier.
Apollo’s use of AI is currently more assistive than fully autonomous. It doesn’t yet have a conversational query interface for finding leads; users still input criteria through forms. However, Apollo’s AI can:
One of Apollo’s biggest draws is efficiency in prospecting. With its vast data, a single rep can build a targeted list and start sequencing emails all within Apollo, without jumping between tools. Teams leveraging Apollo have reported a 16% lift in outbound opportunities simply by having more accurate data and integrated outreach tools in one place(9). The platform claims that in 2025 alone, users executed over 47 million prospecting actions (emails, calls, etc.) through Apollo(9) – illustrating its broad adoption. It also boasts over 1 million users worldwide(9). This wide user base provides Apollo’s AI with plenty of interaction data to learn from.
While Apollo’s AI is not as front-and-center as some others on this list, it demonstrably saves time. By unifying contact search and engagement, sales reps can cut down sourcing time by 50% or more, and the platform’s recommendations have been shown to boost outreach productivity. In one review, a user noted that using Apollo’s enriched data and templates allowed their team to contact 30% more prospects per week than before, since less time was spent on research and list prep (anecdotal, but echoed by many SMB teams). Apollo itself has highlighted that teams using the platform’s all-in-one workflow close 20% more deals on average compared to those piecing together data from multiple sources – likely because no lead falls through the cracks when everything is in one system.
Bottom line: Apollo.io is often the entry point into AI-assisted prospecting for smaller GTM teams. It’s “AI-enhanced” rather than AI-driven – meaning humans remain firmly in control, but benefit from incremental intelligence features. For teams that aren’t ready to hand the reins to an autonomous system, Apollo provides a comfort zone: you still set the strategy and input, and the platform turbocharges your efforts with its database and some AI suggestions. It’s a cost-effective way to improve prospecting and outreach, though it doesn’t yet match the fully natural language, agentic experience of more advanced solutions. Think of Apollo as an SDR’s co-pilot: it won’t fly the plane for you, but it will make navigation a lot easier.
Gong is the market leader in conversation intelligence, which uses AI to analyze sales calls, meetings, and emails to uncover insights. For GTM teams, Gong acts like an AI-powered coach that listens to what prospects and customers are saying – and then provides guidance to help close more deals. It’s a prime example of natural language AI because it relies on NLP to understand and derive meaning from human conversations.
Gong automatically records and transcribes sales calls (Zoom meetings, phone calls, etc.), then analyzes the transcripts for patterns. It picks up on things like customer pain points, product features mentioned, objections raised, competitor names, and sentiment/tone. For emails and chat exchanges, it similarly parses the text. The AI then identifies trends and suggests best practices:
Gong’s system is trained on an immense dataset of sales conversations, allowing it to understand context and intent in what buyers say. It doesn’t just look for keywords; it can determine if a customer’s question is actually expressing a hidden concern (e.g., “Is that discount available next quarter?” might be a signal of timeline hesitation). Gong’s AI even assesses sentiment – whether the buyer sounds optimistic or skeptical. All this comes in the form of natural language feedback to the team. For instance, a rep can get an alert: “The customer’s tone turned negative when discussing implementation. Consider bringing a sales engineer into the next call.” This is incredibly valuable real-time coaching derived from language analysis.
Key features:
Gong’s impact is often seen in improved sales effectiveness metrics. A notable finding: teams that fully leverage conversation intelligence see win rates increase around 50% compared to those who don’t(6). In practice, that could mean going from closing 1 in 5 deals to 1 in 3 – a massive revenue boost. Additionally, organizations report that forecast accuracy improves because Gong highlights which deals are truly healthy (e.g., multiple buyer contacts, compelling event discussed) versus those at risk, taking gut feeling out of the equation. One Gong case study showed a 18% uplift in win rate after managers used Gong insights to coach reps on introducing ROI discussions earlier in the sales process (the data revealed successful reps mentioned ROI in early calls, leading to that coaching change).
For GTM leaders, Gong provides an unprecedented window into the “black box” of sales conversations. It turns unstructured natural language data – hours of talk – into actionable intelligence. The result is a more data-driven sales culture, where enablement isn’t based on hunches but on what the AI objectively finds. In an era where revenue teams are often distributed and virtual, tools like Gong ensure no insight from a customer conversation is lost. It’s like having an AI analyst attend every meeting and whisper improvements to your team, helping close deals faster and more consistently.
HubSpot has long been a go-to platform for inbound marketing and CRM, and now it’s embracing AI and natural language interfaces across its ecosystem. In 2023, HubSpot introduced ChatSpot.ai, a conversational AI assistant that connects to your HubSpot CRM data. Essentially, ChatSpot lets GTM team members ask questions or give commands in plain English and gets things done in HubSpot – from pulling reports to drafting content. This, combined with HubSpot’s other AI-driven features, makes HubSpot a powerful natural language AI system for GTM teams, particularly in marketing and sales operations.
With ChatSpot, you can literally chat with your CRM. For example, a sales manager might type: “Show me all deals in Q4 over $50k that are stuck in proposal stage” and ChatSpot will retrieve that list from HubSpot CRM without the user clicking through filters. Or a marketer could say: “Draft a follow-up email for a lead who downloaded our ebook on data security” – the AI will generate a personalized email using context from that lead’s record and content from the ebook. This lowers the technical barrier to getting insights or content from HubSpot; you don’t need to be an analytics expert or great copywriter, the AI helps with both.
Key AI features in HubSpot:
HubSpot’s all-in-one approach augmented by AI drives measurable results, especially for smaller GTM teams with limited resources. Companies using HubSpot’s AI features have reported marketing efficiency gains like 3-4× faster content creation and significant lift in engagement. One mid-market user noted that after deploying AI chatbots and predictive lead scoring, their sales reps’ productivity increased ~12% and early pipeline grew ~20% because reps focused on AI-prioritized leads (source: internal HubSpot case study). Another benefit: email open rates improved by 30% in a test where subject lines were optimized by HubSpot’s AI suggestions versus human-written ones(7).
For GTM teams, HubSpot’s embrace of natural language AI means the tools get smarter without getting more complicated. Team members can interact with complex data or create sophisticated campaigns just by telling the platform what they need. This lowers training time and accelerates execution. HubSpot is particularly effective for inbound-focused organizations where understanding customer behavior and rapidly following up is key – the AI handles a lot of that heavy lifting behind the scenes or through an intuitive chat interface. In sum, HubSpot is turning into an “AI co-pilot” for marketing and sales, embedded right into a familiar platform many teams already use.
6sense is a leader in applying AI to account-based marketing and sales. It’s an account intelligence platform that uses natural language processing and big data to figure out which companies are in-market and what they’re interested in – often even before those companies directly engage with you. For GTM teams practicing ABM or targeting large deals, 6sense provides an “extra sense” (hence the name) by analyzing anonymous buyer behavior and predicting who is likely to convert soon.
6sense’s AI platform aggregates intent data from numerous sources: web visits (even anonymous ones via IP tracking), search terms, engagement with content across the web, and third-party data providers. It then matches this to accounts in your CRM and ideal customer profile. The output is a prioritized list of target accounts with a stage prediction (e.g., Awareness, Consideration, Decision). Essentially, it’s reading the digital body language of prospects. Natural language processing comes into play by analyzing the content consumption – for example, if multiple people at a company are reading articles about “cloud data security” on tech sites, 6sense’s NLP algorithms categorize that interest and infer that the company may be researching solutions in that area.
Key capabilities:
The power of 6sense is evidenced by significant lifts in conversion rates for ABM programs. According to 6sense, companies using its AI to guide their account targeting see on average 40% higher email response rates and engagement lifts versus broad-based outreach(8). By zeroing in on accounts that are showing buying signals, sales teams waste less time – one case study noted a client achieved 2X increase in pipeline within a quarter of implementing 6sense, simply because reps focused on the hottest 10% of their target list that the AI identified. Furthermore, marketing teams report more efficient ad spend: rather than blanket targeting, they serve ads to 6sense “in-market” accounts and have documented significantly better click-through and conversion on those ads (often 2-3× higher CTR than generic targeting, per 6sense’s own benchmarks).
In summary, 6sense acts like an AI-powered radar for GTM teams, scanning the horizon of the B2B buying landscape and alerting you in plain language to the signals that matter. It answers questions like “Who should we talk to next?” with data-driven precision, which is immensely valuable given that studies show up to 70% of the B2B buying journey happens anonymously before a prospect ever fills out a form or talks to sales. By illuminating that dark funnel, 6sense helps GTM teams be in the right place at the right time with the right message. It’s a quintessential example of AI turning massive textual and behavioral data into clear, actionable insights.
Conversica is a pioneer in the field of AI-powered virtual sales assistants. In essence, Conversica provides an AI “sales development representative” that autonomously engages leads in two-way conversations via email (and sometimes SMS). This is a prime example of a natural language AI system because the Conversica assistant writes human-like emails to prospects, responds to their replies, and nurtures them just as a human SDR would – all using NLP to understand incoming messages and NLG (natural language generation) to craft responses.
Think of Conversica as an automated follow-up machine. When leads come into your funnel – say, someone fills out a demo request or downloads a whitepaper – the AI assistant will reach out promptly and persistently. A typical Conversica email might read: “Hi John, I’m following up on your interest in [Company]'s solutions. Did you want to schedule a quick call to learn more? Happy to coordinate a time.” If the lead doesn’t respond, the assistant will send polite follow-ups over the next few weeks, gently nudging. When the lead replies, Conversica’s AI reads the email to determine intent. If John replies “Yes, I’m interested but busy, maybe next month,” the AI will recognize the positive intent and respond accordingly (“Understood. I’ll reach out in a few weeks to find a convenient time.”). If John says “No, not interested” or “Already purchased a solution,” the AI will gracefully close out or ask a clarifying question. Once a lead indicates genuine interest (e.g., “Sure, let’s set up a call”), Conversica notifies a human salesperson to step in and take over the conversation.
Conversica’s system has been trained on millions of email interactions and is built to handle the nuances of human replies – including things like out-of-office messages, ambiguous answers, or objections. It leverages NLP to categorize replies (interest, no interest, not now, ask for more info, etc.) and respond with appropriate tone and content. Importantly, Conversica’s AI is multilingual and can carry conversations in multiple languages, broadening its usefulness for global teams.
Key benefits:
Conversica’s impact on lead conversion is impressive. According to data shared by the company, customers on average achieve a 24× return on investment in pipeline value using these AI assistants(9). The reason is simple: by engaging and warming up leads that human reps might miss or not have time for, Conversica recovers opportunities that would have been lost. In terms of conversion rates, Conversica often cites that 40–50% of leads that engage in conversation with the AI eventually convert to a sales meeting or qualified opportunity(9). That’s a very high conversion from initial interest to pipeline, underlining how effective diligent, timely follow-up can be when done at scale. In one case study, a company (Corelight) reported a 12.5% lead-to-opportunity conversion rate using Conversica to follow up with thousands of dormant leads(9) – a rate better than many teams get from fresh, hand-raised leads, achieved on leads that otherwise would have been left untouched.
For GTM teams, Conversica slots into the process typically right after marketing captures leads or when sales has a long list of old leads to re-engage. It ensures no lead falls through the cracks by acting as a tireless assistant that’s always polite and always on message. The conversations feel human enough that many recipients don’t realize an AI is behind the emails; they simply appreciate the timely response and follow-up. And because the AI hands off to humans at the right moment, there’s a seamless transition when a lead is hot. Conversica essentially lets your team cover the “long tail” of leads that would overwhelm a human team, turning meh leads into meetings and boosting pipeline without additional headcount. It’s a clear example of AI augmenting human effort – doing the initial grind of outreach so your sales reps can focus on the leads that actually respond.
Persana AI is an emerging GTM automation platform that takes a highly automated approach to outbound sales. It offers what can be described as autonomous AI sales agents that handle much of the sales development process, from researching prospects to sending personalized outreach and even following up. In other words, Persana aims to be a “virtual SDR team” powered by AI. This naturally involves heavy use of natural language AI, since Persana’s agents are crafting emails, parsing replies, and mirroring human-like interactions in the sales process.
Persana connects to a wide array of data sources (over 75+, according to the company) to draw in contact and account information. Its flagship AI agent, named “Nia,” can automate up to 90% of the SDR workflow – including identifying potential leads based on signals, enriching their info, and engaging them with emails and sequences(5)i. Persana uses a “waterfall enrichment” approach: it pulls data from many providers (like ZoomInfo, LinkedIn, Clearbit, etc.) to ensure each lead’s info is as complete and accurate as possible(5). Then Nia will send out outreach, adapting messages based on each prospect’s unique context (industry, role, recent activities) – a level of hyper-personalization made possible by AI analysis of those data points(5).
When prospects engage, the AI can reply back, answer simple questions, and only loop in a human salesperson when the lead is qualified and ready to talk or when the conversation goes beyond the AI’s script. Essentially, Persana’s AI agents try to do everything a human SDR would do up to the point of booking a meeting.
Key features:
Persana’s users have reported substantial efficiency and pipeline gains. On the efficiency side, teams using Persana say they save 8–10 hours per week per rep on prospecting tasks(5), since the AI handles the grunt work. More impressively, Persana claims that its customers have seen a 95% increase in qualified leads generated after implementing the AI agents(5) – essentially nearly doubling the output of their top-of-funnel. Additionally, by automating prospecting, Persana can dramatically compress sales cycles. The company cites that some teams cut sales cycle times by 65% and increased conversion rates by 30% by focusing human effort only where the AI has nurtured warm interest(5).
While Persana is a newer entrant and perhaps less widely known than some others on this list, it exemplifies the cutting edge of agentic AI in GTM. It’s particularly attractive for organizations that have high volumes of potential prospects and signals to monitor – far more than a human team could ever stay on top of. By letting an AI army handle the volume, companies can achieve scale (one Persana user said “it’s like we added 10 SDRs overnight” without the payroll). Of course, one must ensure quality and brand voice are maintained; Persana provides templates and oversight tools so managers can review what the AI is sending. But as those stats indicate, when executed well, autonomous prospecting agents can fill pipelines fast. Persana proves that natural language AI isn’t just for chatbots or analysis – it can actually conduct outbound sales conversations from start to finish, changing how GTM teams approach scaling their outreach.
It’s time to stop wasting time on outdated data tools and manual processes. The fastest way to revenue is starting with the right audience. Now, finding that audience is as easy as typing a sentence.
Landbase has redefined what GTM automation means by moving from a “tool” to an agentic system of action. It operates as an extension of your team – one that works tirelessly and intelligently to fuel your pipeline. From intent to identification to activation, Landbase covers the front-end of go-to-market in a way no legacy system can.
If you’re a sales leader seeking speed and accuracy, a marketer wanting better leads at scale, or a RevOps professional aiming to optimize every stage of your funnel, Landbase’s agentic AI is the advantage you’ve been waiting for. It offers the kind of leverage that changes the game – transforming GTM efforts from manual and reactive to automated and proactive.
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