AI Sales Automation 2025: Top Tools & B2B Trends Revealed

Q: How can AI be used in sales?

AI supports every stage of the sales cycle . It helps identify and qualify leads, personalize outreach, forecast revenue, automate admin tasks, and analyze conversations. Reps save time, managers get better visibility, and organizations close more deals with greater efficiency. AI enhances performance by making sales workflows more data-driven, timely, and scalable.

Q: Can I use AI to generate sales leads?

Absolutely. AI tools can identify sales leads , enrich lead data, detect intent signals, and qualify leads automatically. Platforms like Martal use AI to generate sales leads and prioritize them based on firmographics and buyer intent, enabling faster, smarter pipeline growth without relying solely on manual research.

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Major Takeaways: AI Sales Automation

How are autonomous AI agents transforming sales teams?

AI agents now handle up to 80% of SDR tasks—from prospecting to scheduling—freeing reps to focus on high-value conversations and strategic selling.

What role does generative AI play in personalized outreach?

Generative AI enables hyper-personalization at scale, improving response rates and conversions by tailoring content based on firmographics, behavior, and buyer signals.

Can AI really improve forecasting and pipeline accuracy?

Yes—AI-driven predictive analytics improve forecast accuracy by 20–30% and help sales leaders prioritize deals based on engagement signals and win probability.

Why is multichannel AI engagement a must-have in 2025?

With 80% of B2B buyer interactions now digital, AI helps orchestrate timely, personalized outreach across email, LinkedIn, phone, and chat to boost engagement by up to 40%.

How is AI changing the structure of the sales tech stack?

Sales orgs are replacing scattered point solutions with unified, AI-powered platforms to reduce costs, improve efficiency, and eliminate data silos that limit performance.

Which AI tools are essential for B2B sales success in 2025?

Tools like Martal AI SDR, Salesforce Einstein, and Gong offer AI-powered outreach, forecasting, and conversation analysis that directly improve conversion rates and ROI.

What’s the best way to implement AI in outbound sales?

Start with AI-enabled multichannel outreach, use predictive lead scoring, and combine automation with experienced reps for a hybrid approach that scales pipeline efficiently.

Introduction

Experienced B2B sales leaders know that change is the only constant – and in 2025, the biggest change-agent is artificial intelligence. AI-driven sales automation (AI sales automation) is transforming how we prospect, engage, and close, creating both massive opportunities and new challenges for B2B organizations.

In fact, most companies are betting on AI with 92% planning to increase investment in AI over the next three years to drive revenue growth and streamline sales (4). McKinsey even forecasts that generative AI has the potential to boost sales productivity by 3–5% of current global sales spend (5). In short, AI isn’t hype – it’s a game-changer for B2B sales.

But where exactly is AI making its mark in B2B sales, and how can revenue leaders capitalize? Below, we dive into 5 key trends reshaping B2B sales through AI sales automation. From autonomous “virtual SDR” agents to hyper-personalized outreach, these trends illuminate how selling is evolving – and what we can do to stay ahead. We’ll also highlight the top AI sales automation tools (with our own Martal AI SDR platform leading the pack) that savvy teams are using to outsmart the competition.

Our perspective is solution-focused: we don’t do fluff or vague futurism. As practitioners in AI-powered outbound sales, we at Martal have seen what works in the field. So let’s explore the trends, backed by hard data and industry examples, and identify the tools and strategies that can drive real results for your sales organization.

Skip to the end for a detailed comparison of the top AI sales automation tools and an FAQ section on common AI-in-sales questions.

1. AI-Powered Autonomous Sales Agents and Co-Pilots

82% of organizations plan to integrate AI agents into business operations within 1–3 years.
Reference Source: Capgemini

AI is moving beyond basic task automation to acting as a true “co-pilot” (or even pilot) for sales reps. In 2025, we see the rise of autonomous AI sales agents – software bots and assistants that can handle routine sales interactions, from initial outreach to meeting scheduling, with minimal human intervention. This trend encompasses AI chatbots on websites, AI assistants that draft emails or LinkedIn messages, and voice AI that can engage prospects on calls. It’s about AI not just assisting behind the scenes, but taking on front-line selling tasks.

Why it’s reshaping sales: These AI agents dramatically expand a sales team’s capacity. Imagine having virtual SDRs that prospect 24/7, never get tired, and respond to leads instantly. According to a global survey, 82% of organizations plan to integrate AI agents into business operations within 1–3 years (18), underscoring the expected impact in the near term. Early adopters are already gaining an edge. For example, some companies use AI email assistants that autonomously follow up with cold leads until a human response is required. The long-term potential is massive: teams that understand how to leverage AI agents will operate far more efficiently, letting human sellers focus on high-value conversations while AI handles the repetitive outreach and data gathering.

What AI agents can do today: Modern AI sales assistants can research prospects, draft personalized emails, answer common questions via chat, and even make initial calls using natural language processing. They function like entry-level sales reps. These agents interact with the environment (CRM data, emails, calendars) to take autonomous actions – much like a self-driving car navigates autonomously (1).

For instance, an AI bot can identify a new inbound lead, send a tailored welcome email, schedule a demo in the rep’s calendar, and set a reminder for follow-up – all without human input. Crucially, AI co-pilots are also emerging that work alongside humans in real time: tools that join sales calls to provide live coaching, or sit in your CRM to suggest next-best actions.

By 2028, Gartner predicts 60% of B2B seller interactions will happen through AI-driven conversational interfaces (up from less than 5% in 2023) (1) – a sign that virtual agents and chatbots will become a standard part of customer engagement.

Impact on sales teams: Embracing AI agents requires a mindset shift. Top-performing teams treat AI as a teammate – not replacing reps, but augmenting them. In practice, that means training your “AI SDRs” on your playbooks and letting them handle the grunt work. When routine emails, meeting bookings, and data entry are offloaded to AI, your human reps reclaim precious hours. One study found that sellers could save up to 2 hours per day by using AI to automate manual tasks – roughly 25% of their time – and reinvest that into selling (11).

Moreover, AI co-pilots can analyze 100% of sales conversations and provide real-time guidance, something no human SDR manager can do at scale. This democratizes coaching: even junior reps get instant feedback (e.g. suggested answers to objections, reminders to mention a feature), leveling up the whole team’s performance.

Sales teams are gaining value from AI in many daily tasks. Top uses include creating content (e.g. sales emails), drafting follow-ups, personalizing outreach, and updating CRM data – all chores that an AI “teammate” can handle to free up reps. By acting as always-on assistants, AI sales agents help reps reclaim time for higher-value activities.

How to leverage this trend: Start by deploying AI assistants in low-risk, high-repetition areas. For example, use an AI scheduling tool to automate meeting bookings or an AI email assistant to nurture cold prospects who haven’t responded. Ensure these agents are fed with quality data – integrate them with your CRM and marketing stack so they have context to act wisely.

We also recommend a human-in-the-loop approach initially: have reps monitor AI interactions and provide feedback. This “training period” helps the AI learn nuances and builds your team’s trust in the system. In our experience, combining AI agents with human oversight leads to the best outcomes – the AI handles volume, while humans handle judgment.

As your comfort grows, you can gradually give the AI more autonomy (e.g. allowing an AI bot to qualify inbound leads via chat or phone). The key is to treat AI as an extension of your team.

Sales leaders should set clear guidelines (for tone, when to hand off to a human, etc.) and measure the results. When done right, AI agents can dramatically scale your outreach and responsiveness, giving your organization a “virtual workforce” that boosts pipeline without proportional headcount.

2. Hyper-Personalization at Scale with Generative AI

AI-powered personalization can boost customer conversion rates by up to 57%.
Reference Source: Lead Forensics

A generic, templated sales pitch will not work in 2025. Today’s buyers expect outreach that feels customized to them – their industry, their specific pain points, maybe even them personally. The second big trend is using generative AI to achieve hyper-personalized outreach at scale. Generative AI (like GPT-4 and other large language models) can instantly create content – emails, LinkedIn messages, proposals – tailored to each prospect’s context. This allows sales teams to personalize like never before, without spending hours on research and copywriting for every single touch.

Why it’s reshaping sales: Personalization has a direct impact on conversion metrics. According to recent B2B data, AI-driven personalization can boost conversions by up to 57% by delivering more relevant messaging (9).

Buyers engage when they feel you truly understand their business. Traditionally, personalization didn’t scale – an SDR might only customize emails for top-tier accounts and rely on sales email templates for the rest. Now, generative AI flips that script, making it feasible to tailor outreach across your entire prospect list. AI models can pull in details from a prospect’s LinkedIn, company news, CRM notes, etc., and weave that into a message that reads as if it was hand-written for that individual. The result? Higher open rates, reply rates, and ultimately more meetings.

Enabling technologies: The tools behind this trend include AI writing assistants (like GPT-based email writers) and AI-powered research bots. For example, there are AI sales email tools now that, with one click, generate a custom outreach email that references the prospect’s industry and a recent trigger event (say, a funding round or a new product launch).

All a sales development representative has to do is maybe tweak a line or two and hit send. Similarly, AI can dynamically insert personalized snippets into sequence templates – such as a line about how “[Prospect’s Company]’s recent expansion in [New Market] is something we’ve helped similar firms tackle.” This level of personal touch across thousands of prospects was impossible manually. Generative AI changes the game by serving as an “infinite copywriter” for your team.

However, a caution comes with this power: quality data is crucial. Generative AI is only as good as the information it’s fed. Feeding your AI content assistant with incorrect or irrelevant data will produce mediocre (or even embarrassing) output. As noted in one analysis, successful generative AI in B2B sales hinges on high-quality, connected data (1). In other words, ensure your CRM and data sources are clean and rich – the AI needs factual fodder about the customer’s needs and your solutions to generate useful messaging.

We’ve found that integrating data like past interactions, firmographics, and intent signals yields much more compelling AI-generated emails. When the AI “knows” the prospect recently downloaded a certain whitepaper or that their company uses a specific technology, it can reference those specifics to catch the buyer’s attention.

Real-world impact: Generative AI is proving especially valuable for top-of-funnel engagement and account-based selling. Sales development reps can now handle far more accounts by automating the tailoring of messages. For instance, SDRs at some companies use AI to write the first 80% of an email (the personalization and value proposition), and they add the final 20% human touch before sending.

This has been shown to significantly increase response rates compared to generic blasts. Personalization isn’t just for email either – AI can personalize cold call scripts, LinkedIn InMails, proposals, and even product demos (by configuring demo environments to each prospect’s scenario). By 2025, we expect hyper-personalization to be table stakes. Buyers will tune out anything that doesn’t speak directly to them. Forward-thinking teams are already using AI to scour social media for prospect triggers, analyze website behavior for intent signals, and then auto-generate tailored talking points for the next sales call.

How to leverage this trend: To ride the personalization wave, equip your team with generative AI tools that plug into your sales engagement workflow. Many sales engagement platforms now have AI writing assistants built-in. You could also use standalone tools (e.g. an AI email generator that connects to your CRM).

Train your team on prompt engineering – the art of giving AI the right instructions.

For example, we create prompt templates like “Draft a 100-word email for [Prospect Name], [Prospect Title] at [Company], about how [Our Solution] can help [Specific challenge] they’re facing, referencing [recent event or fact about Company].”

With the right prompt, the AI will produce a highly customized draft. Encourage reps to always review and tweak AI-generated text to ensure it’s accurate and on-brand (avoiding that unmistakable “robotic” tone).

Finally, combine AI personalization with A/B testing. Use AI to generate two variants of a message, send both, and see which performs better – the learning can further train your models or prompt strategies. The bottom line is AI lets you scale “doing your homework” on every prospect. In 2025’s competitive landscape, that level of tailored outreach is often what separates the vendors who get ignored from those who get the first meeting.

As you scale personalization, keep in mind that 74% of buyers value personalized offers, shaping their loyalty to your brand (7).

Source – Salesforce – State of the Connected Customer

3. Predictive Analytics and AI-Driven Sales Forecasting

By 2027, AI is projected to initiate 95% of seller research workflows, removing much of the manual guesswork from forecasting.
Reference Source: Gartner – The Role of AI in Sales

The art of sales is becoming increasingly scientific, thanks to AI’s prowess in data crunching. Our third trend is the rise of predictive analytics in sales – AI algorithms that forecast outcomes and guide decision-making with uncanny accuracy. In an environment where every deal and dollar counts, AI-driven forecasting and lead scoring are helping sales leaders move from gut feel to data-driven strategy. From predicting which sales ready leads are most likely to convert, to projecting this quarter’s revenue more precisely, AI is supercharging the sales ops and strategy functions.

The pain point: Traditional sales forecasting is notoriously challenging and often inaccurate. Sales managers spend countless hours in spreadsheet hell trying to reconcile reps’ optimistic projections with reality.

But with 95% of seller research workflows expected to be initiated through AI by 2027, much of this guesswork could soon be automated (8).

Source: Gartner – The Role of AI in Sales

Mis-forecasts lead to nasty surprises in revenue and strained trust between sales and the C-suite. Similarly, reps often waste time on leads that look good superficially but were never likely to close, while truly hot prospects might be overlooked due to human bias or oversight. AI aims to solve these issues by analyzing vast swaths of data (pipeline activity, historical deal outcomes, buyer behavior signals) to identify patterns and probabilities far beyond human capacity.

What AI can do: Modern sales AI platforms offer predictive lead scoring, which automatically ranks or scores leads and opportunities based on their likelihood to convert or close. They factor in hundreds of signals – from firmographic fit to engagement level (emails opened, website visits), to salesperson activities and even sentiment from call transcripts. This allows reps to prioritize the most promising deals.

On the forecasting side, AI systems can continuously analyze the pipeline and output a probabilistic forecast (e.g., there’s an 85% chance we’ll hit at least $5M this quarter). These systems often highlight why – for instance, noting that a spike in early-stage pipeline in a certain region boosts the projection, or that a key deal slipping a stage has lowered the probability of hitting quota. AI-augmented forecasting is thus more dynamic and evidence-based than static Excel models. Leading firms are already seeing results.

Using AI-driven forecasting can reduce errors by up to 30%, enhance precision, and drive a 5–10% increase in revenue (6).

Beyond forecasting, AI predictive models help in resource allocation and coaching. For example, if AI deal scoring flags a deal as high-risk (maybe based on negative buyer sentiment on calls or lack of recent activity), managers can intervene early or reallocate resources to save it. If it flags an opportunity as highly likely to close, you might expedite legal/procurement processes to ensure smooth landing. On the flip side, AI can predict which sales reps might miss quota (by analyzing their activity patterns versus successful behaviors), allowing proactive coaching or sales support.

Real-world example: Outreach, a sales engagement platform, uses AI in its “Deal Insights” to predict deal health. Reps get a color-coded risk assessment on each opportunity, with AI pointing out factors like “No executive buyer engaged” or “Last interaction was 20 days ago” that correlate with deals stalling. This kind of AI insight helps sales teams focus effort where it matters most. Another example is Clari (a revenue operations platform) which employs AI to roll up forecasts from reps and spot gaps or upside. Clari’s users have reported big jumps in forecast confidence and the ability to course-correct in-quarter because the AI highlighted pipeline coverage shortfalls early.

Impact on B2B sales strategy: With predictive AI, sales leaders in 2025 are far less in the dark. They can commit to targets with more confidence because AI has analyzed all the data breadcrumbs leading to a deal. Moreover, AI can illuminate which actions truly drive deal progress. It might reveal, say, that deals where a VP-level stakeholder attended the first meeting have a 2x higher close rate – instructing your team to involve power buyers earlier. These evidence-based insights take some of the guesswork out of sales strategy. Importantly, reliable AI forecasts also help align sales with other departments (like finance and supply chain) since projections are more trustworthy.

How to leverage this trend: To get started, ensure you have the data foundation – AI can’t predict in a vacuum. Consolidate your customer interaction data (emails, calls, CRM updates) so the AI models have rich input. Many CRM systems now have built-in AI forecasting tools (e.g., Salesforce Einstein has AI deal scoring and forecast insights baked in). You can also explore standalone revenue intelligence platforms that integrate with your CRM and sales engagement software. When introducing AI predictions, do so transparently: explain to your team why the AI is suggesting a certain forecast or score (most tools will show contributing factors). This helps build trust in the system. We’ve found it useful to run AI forecasts in parallel with your old method for a quarter or two – compare outcomes and gradually lean more on the AI as it proves its accuracy. Additionally, use predictive insights for coaching: if AI identifies that a rep isn’t engaging enough stakeholders in their deals (thus lowering their win probability), sales managers can coach that behavior specifically.

In essence, think of predictive sales AI as an early-warning and decision-support system. It won’t replace leadership judgment, but it will greatly augment your visibility into the pipeline. In 2025’s volatile market, that’s a superpower. Teams that harness predictive analytics can allocate resources more efficiently and close the right deals faster, driving up win rates and reducing unpleasant surprises at quarter’s end.

4. AI-Enhanced Multichannel Outreach and Digital Engagement

80% of all B2B sales interactions will occur through digital channels.
Reference Source: Gartner – The Future of Sales

B2B buyers are everywhere – email, LinkedIn, phone, video, even WhatsApp in some regions – and they expect you to meet them on their terms. The fourth trend recognizes that sales in 2025 is a multichannel game, and AI is the key to orchestrating it effectively.

We’re living in a digital-first era: by 2025, 80% of all B2B sales interactions between suppliers and buyers will occur in digital channels (10). That means sales teams must excel at reaching out through a mix of email, social, and virtual meetings (with the occasional call or in-person touch where appropriate). AI comes into play by determining when, where, and how to engage each prospect for maximum impact.

Why it’s reshaping sales: Buyers control the journey today. Research shows that the majority of business buyers agree that technology improves decision-making, with 85% of Millennials and Gen Xers and 72% of Baby Boomers reporting they are better informed about product choices (7).

Source: Salesforce – State of the Connected Customer Research

By the time a rep gets involved, the buyer might already have a shortlist and a wealth of information. In this environment, a single cold call or a lone email won’t cut through the noise. You need a coordinated cadence of touches across channels to nurture and connect with prospects. AI helps by analyzing engagement data to optimize this cadence. For example, AI can figure out that a particular prospect responds better on LinkedIn than email, or that after two unopened emails, it’s time to try a phone call or a different message approach. This adaptive sequencing is crucial – it’s hyperautomation of the sales outreach sequence.

Multichannel coordination: Modern sales engagement platforms use AI to recommend the next touch: if a prospect opened your email but didn’t reply, the system might prompt an SDR to send a LinkedIn message referencing the email. If a prospect clicked a link in your email, the AI might suggest scheduling a call ASAP since interest is high.

Essentially, AI monitors digital body language across channels and triggers the best action. It also handles timing – sending emails at the time of day the contact is most likely to engage, or spacing out touches optimally (maybe your data shows Day 3 and Day 7 after initial contact are key windows).

Digital channel expansion: AI is also enabling new channels like conversational chatbots and SMS to be part of the sales process without adding burden to reps. For instance, an AI sales chatbot on your website can qualify visitors 24/7; if it determines the visitor is a hot lead (based on their questions or firmographic data), it can route the conversation to a human or schedule a meeting. That’s a new “channel” working for you hands-free. Likewise, AI can personalize content on your website for known prospects (if an AI recognizes a return visitor from a target account, it might display a custom case study on the landing page). All these digital engagements create a cohesive experience so the buyer feels consistently catered to, regardless of where they interact.

Importance of integration: A major aspect of this trend is integrating sales and marketing efforts. Sales automation AI tools are increasingly overlapping with marketing automation to ensure prospects get a seamless journey. For example, AI can coordinate an email campaign (sales) with retargeting ads (marketing) to the same lead, and adjust messaging if the lead engages with one or the other. For sales teams, having a centralized AI-driven platform that spans multiple channels prevents the classic “left hand doesn’t know what right hand is doing” issue. It’s inefficient if your SDR calls a prospect unaware that marketing just sent them a nurture email that morning. AI systems can unify these touchpoints and even automate responses – e.g. automatically removing a lead from a sequence if they register for a webinar (since they’ve moved to a different stage of engagement).

How to leverage this trend: Audit your current outreach sequence – how many channels are you using, and how well are they synced? If it’s mostly single-threaded (just emails or just calls), it’s time to go multichannel. Implement an AI-enabled sales engagement platform that supports email, phone, social touches, etc., and uses analytics to optimize cadence. You’ll want a tool that can track prospect interactions across all channels in one place. Then, start small by letting the AI optimize email send times or suggest touches, and gradually enable more automated steps.

A good approach is to create tiered outreach strategies: for example, Tier 1 prospects get a highly personalized, AI-optimized sequence involving email + LinkedIn + a call + perhaps a personalized video, whereas Tier 3 might get a more automated email-heavy cadence. AI can handle these variations easily. Ensure also that sales and marketing collaborate on this – align on messaging and share data.

We also recommend incorporating what we call a “digital listening” component: use AI lead generation tools to monitor buyer intent signals (like who’s visiting your pricing page or what content they download) and trigger sales outreach based on that. It’s multichannel outreach initiated by buyer behavior, which tends to be very effective because it’s timely and relevant. In summary, AI-driven multichannel orchestration is about being everywhere your buyer is, with the right message at the right time. The days of a one-channel strategy are over – if you’re not engaging on multiple fronts with AI intelligence guiding you, your competitor will be, and they’ll likely win the deal.

5. Consolidation of the Sales Tech Stack and All-in-One AI Platforms

Companies that consolidate sales tech stacks see a 15% increase in sales productivity and a 20% reduction in costs.
Reference Source: McKinsey & Company

Our final trend goes beyond any single tactic – it’s a strategic shift in how sales organizations manage their technology. In the past decade, sales teams accumulated a sprawling stack of tools: one for CRM, another for emails, a dialer, a data provider, a sales intelligence app, a call recording tool, a proposal generator… and so on.

In 2025, this is reaching a tipping point. Forward-thinking companies are consolidating their sales tech stack – and leveraging AI to do it. The goal is to eliminate siloed point solutions in favor of all-in-one AI-powered sales platforms that streamline workflows. In essence, AI is becoming the operating system of the sales org, not just a collection of apps.

Why it’s reshaping sales: Efficiency and effectiveness. When reps juggle 12 different tools, productivity suffers. There’s context-switching, inconsistent data flow, and multiple logins.

Tech overwhelm is real. It is found that sales professionals who are overwhelmed with technology are 43% less likely to reach their targets (2).

Meanwhile, companies pay for redundant capabilities and suffer from integration headaches. By consolidating tools, organizations can cut costs and make life easier for reps and ops alike. But consolidation doesn’t mean giving up capabilities – rather, moving to unified platforms that cover multiple functions, often powered by AI to enhance each function.

AI as the unifier: Many modern sales platforms are building AI into their core, effectively offering a one-stop-shop. For example, some solutions now combine a database of leads, an email/phone sequencing tool, and an AI that enriches contacts and automates outreach – all in one interface.

Our own Martal AI Sales Platform is a prime example (more on that in the tools section): it replaces the need for separate email automation, dialing, data sourcing, and sequencing tools by providing an integrated AI-driven outbound engine. This means less admin work and a single source of truth for data. Companies are shifting from a patchwork of apps to a cohesive AI-enabled system underpinning the entire sales process.

Benefits of consolidation: There are concrete gains from this approach. Companies that have consolidated their sales and marketing tech have observed significant improvements.

Fewer tools mean less time training reps and troubleshooting, and more time actually selling. Data also flows seamlessly end-to-end (e.g., the moment a lead engages, it’s instantly reflected everywhere it needs to be, without relying on clunky integrations). Additionally, AI thrives on data – a consolidated platform has access to all the relevant data in one ecosystem, making its predictive and automation capabilities more powerful. By contrast, if your call recordings are in one system and your email engagements in another, an AI trying to analyze win likelihood might miss half the picture. A unified platform solves that.

Cultural shift: Adopting an all-in-one AI platform often requires change management. Reps may be used to their favorite point solutions, and ops teams to theirs. But the trend in 2025 is toward simplification. Sales leaders are asking: “Do we really need five different tools when one can do it all with AI?” Increasingly, the answer is no. We’ve seen many mid-market companies swap out multiple subscriptions in favor of a single AI sales platform to reduce complexity. Importantly, this doesn’t mean less functionality – if you choose the right platform, it actually means more power, because AI can create synergies. For instance, an AI that’s part of your engagement platform can automatically log CRM activities (solving the adoption problem of CRM), or dynamically adjust sales cadences based on pipeline changes, things that weren’t possible when each tool was isolated.

How to leverage this trend: Take stock of your current sales tech stack. Identify overlapping features and integration pain points. Then evaluate modern platforms that cover multiple needs – for example, does your CRM offer built-in AI features that eliminate the need for a third-party tool? Could a sales engagement platform with a native dialer and AI insights replace separate dialing and call analysis tools? When comparing, look closely at the AI capabilities: the best all-in-one platforms have agentic AI (sales agents), automation, analytics, and content generation all integrated. Implementation should be phased – perhaps start by consolidating two or three tools and demonstrate quick wins (like less time spent on manual data entry or one source to check for all prospect interactions).

At Martal, we strongly advocate for an integrated approach, which is why we built our platform to be an all-in-one outbound solution. We’ve seen clients dramatically improve SDR productivity when they don’t have to jump between a list provider, an email tool, and a calling app – instead, one AI system handles it end-to-end. Whatever solution you choose, aim for the mantra: “fewer tools, more cohesion.”

By consolidating and letting AI coordinate your sales process, you eliminate friction and give your team the resources to drive revenue. In 2025, winning sales orgs will be those that cut the clutter and leverage one powerful, AI-driven system to orchestrate their outreach, follow-ups, and insights.

Having explored the five major trends in AI-driven sales automation – from autonomous agents to unified platforms – the question remains: what tools can help you capitalize on these trends? In the next section, we’ll highlight the top AI sales automation tools to watch in 2025, including how each aligns with the trends above. These tools are empowering sales teams to work smarter, and we’ve included a detailed comparison to help you navigate the options.

Top AI Sales Automation Tools to Watch in 2025

In the rapidly expanding landscape of AI sales tech, a few standout platforms are leading the charge. Below we compare five of the top AI sales automation tools that B2B sales leaders should have on their radar in 2025. Each of these tools addresses different aspects of the trends we discussed – from AI-driven outreach to predictive forecasting – and can potentially deliver significant performance gains. As Martal, we’re proud to include our own Martal AI Sales Platform at the top of this list, given its all-in-one AI-powered approach to outbound sales. Let’s dive in.

1. Martal AI Sales Platform – AI SDR & Outbound Automation

Overview: The Martal AI Sales Platform (also known as Martal “AI SDR”) is a full-service, AI-driven outbound SDR platform that combines automation with human expertise. It’s essentially an all-in-one outbound engine – incorporating prospect data, multichannel outreach (email, LinkedIn, phone), and AI assistants – designed to generate leads and set appointments on behalf of your team. We built Martal to help B2B companies scale their sales pipeline without expanding headcount, by acting as an outsourced sales agency and SDR team augmented by powerful AI.

Key Features & Strengths:

AI-Powered Outreach: Martal’s agentic AI automates roughly 80% of the repetitive SDR tasks – from finding and qualifying prospects to sending personalized cold emails and LinkedIn messages (12). Your “AI SDR” engages leads across channels and only hands over to humans when a lead is warm, saving your reps countless hours.
Massive B2B Database: Users gain access to Martal’s 220M+ contact database with built-in data enrichment (13). The platform continuously updates contacts and applies intent signals, so you always have fresh, high-potential leads to target. No need to buy separate lead lists – the data is baked in.
All-in-One Tool Consolidation: Martal replaces the need for a dozen different sales tools. (The average SDR team uses 12 tools, but Martal’s platform replaces them with one (13).) It handles email sequencing, dialer, CRM integration, lead tracking, analytics, etc., in a unified workspace. This means less admin and more selling.
Proven Outbound Results: Backed by 15+ years of sales data, Martal’s AI optimizes campaigns for high response. Clients see dramatic improvements – typically 4–7× more responses and meetings compared to traditional outbound efforts (13). By automating busywork and optimizing timing/content, Martal significantly boosts conversion rates.

Why Watch in 2025: Martal stands out as a pioneering “AI SDR as a service.” It’s ideal for lean B2B teams or any organization that wants to accelerate outbound sales with minimal internal SDR resources.

With Martal, you not only get a cutting-edge AI platform, but also Martal’s human sales experts who monitor and fine-tune lead generation campaigns (ensuring that the AI’s output remains top-notch and human-sounding).

This hybrid approach means you benefit from AI speed and scale plus seasoned sales judgment. In 2025, as companies seek to do more with less, Martal offers a ready-to-go outbound machine: we handle the tools, data, and initial outreach, while your sales team focuses on closing deals.

For experienced sales leaders, Martal can effectively act as an extension of your team – your AI-powered fractional SDR team. If your goal is to quickly fill the top of the funnel and set qualified appointments, Martal’s platform deserves a serious look.

2. Salesforce Sales Cloud Einstein (Salesforce AI) – AI for CRM & Forecasting

Overview: Salesforce, the world’s leading CRM, has deeply integrated AI into its Sales Cloud offering through Einstein AI and the newer Sales GPT features. Salesforce Einstein acts like an AI assistant living inside your CRM – it can analyze your sales data, automate tasks, and even generate content, all within the Salesforce platform. In 2025, Salesforce’s AI capabilities are quite advanced, making Sales Cloud not just a database of record but a smart co-pilot for sales reps and managers.

Key Features & Strengths:

Automated Data Capture & Insights: Einstein automates logging calls, emails, and events, freeing reps from data entry. It also combs through that data to deliver insights like lead scoring, opportunity health, and next best actions. For example, Einstein Lead Scoring prioritizes leads by win likelihood, and Einstein Opportunity Insights might alert you if a deal is drifting (e.g., “No customer activity in 14 days”).
Einstein GPT for Sales: This is Salesforce’s generative AI capability. It can auto-draft personalized emails, generate call summaries, schedule follow-ups, and even suggest next steps for opportunities (16) – all contextually tailored to the CRM data on that record. A rep can literally click a button after a sales call and have Einstein GPT produce a summary and an email follow-up to send to the prospect (16). This saves time and ensures nothing falls through the cracks after meetings.
Predictive Forecasting and Analytics: Salesforce Einstein Forecasting uses AI to improve forecast accuracy by learning from your past pipeline patterns. It gives sales leaders an AI-informed projection and identifies key factors influencing it. Additionally, Einstein Discovery (analytics) can find trends in what attributes closed deals have in common, etc., empowering data-driven strategy. Salesforce has reported that companies using Einstein AI features see measurable lifts in win rates and productivity.
Ecosystem and Integration: Because it’s Salesforce, Einstein seamlessly integrates with your customer data, as well as other Salesforce clouds (Service, Marketing). It can, for instance, integrate with Slack via Slack GPT to provide AI insights right in your team chats (16). The benefit here is centralized intelligence – Einstein is embedded in the tools your team already uses daily.

Why Watch in 2025: Salesforce Einstein is a top tool to watch mainly because Salesforce is ubiquitous in B2B sales – and they are continuously innovating their AI capabilities. If your organization uses Salesforce, activating Einstein features might be the fastest way to inject AI into your sales process. In 2025, Salesforce is pushing the envelope with things like real-time data signals (via their Genie platform) feeding Einstein, and deeper generative AI for all parts of the sale. For a VP of Sales, Einstein offers a way to augment your entire sales process within one platform: your reps get AI-driven productivity tools, your managers get better forecasts and pipeline analytics, and your customers ideally get faster responses and more personalized engagement grounded in CRM data. Plus, Salesforce’s AI is largely point-and-click to enable – no coding or separate contracts required for many features. Given Salesforce’s market dominance, their AI features are likely to set industry standards. Note: To fully leverage Einstein, your Salesforce data quality needs to be solid (garbage in, garbage out). But with a good CRM hygiene, Einstein can be a game-changer in helping your team work smarter and close more deals right from the familiar CRM interface.

3. HubSpot Sales Hub & ChatSpot – Inbound Sales Automation & AI Assistant

Overview: HubSpot’s Sales Hub is another popular platform that has embraced AI to assist sales teams, especially in the mid-market segment. HubSpot offers an all-in-one CRM, marketing, and sales platform, and has introduced a suite of AI features under names like HubSpot Sales Hub AI and ChatSpot. ChatSpot, launched by HubSpot’s founders, is a conversational AI assistant (powered by ChatGPT) that connects to HubSpot CRM to help with tasks via simple chat commands. Overall, HubSpot’s AI aims to make the sales process more guided and efficient for reps using the HubSpot ecosystem.

Key Features & Strengths:

AI-Powered Sales Assistant (ChatSpot): ChatSpot is like having a personal sales concierge. Reps can literally type requests in natural language, such as “Show me all companies in my CRM with >500 employees in the fintech industry” or “Draft a follow-up email for the lead I met today”, and ChatSpot will execute it (15). This saves time navigating the CRM or crafting emails. It can book meetings, create reports, add contacts – all through chat. For salespeople who aren’t power users of CRM, this is a friendly interface to get things done quickly.
Predictive Lead Scoring & Insights: HubSpot Sales Hub includes predictive lead scoring (using machine learning on your engagement data to score contacts). It also shows deal insights and at-risk deals based on lack of activity or engagement. For instance, HubSpot can highlight if an opportunity’s engagement level is below average when it’s at a certain stage, prompting the rep to take action.
Content Assistance: HubSpot’s AI Content Assistant can help reps write emails, email subject lines, or even sales sequences. It can suggest improvements to make messages more engaging (similar to a Grammarly but sales-focused). HubSpot has infused AI in templates and snippets to enable personalization at scale – reps can generate tailored snippets about a prospect’s company to add into outreach.
Integration of Marketing & Sales Data: Because HubSpot is a combined marketing-sales platform, the AI can leverage data from both sides. For example, it knows what emails a lead opened and what web pages they viewed, which can feed into better lead qualification and personalized outreach recommendations. HubSpot’s AI might alert a sales rep when one of their contacts shows surging interest (like repeated site visits or multiple content downloads), suggesting it’s a good time to reach out – effectively an AI-driven MQL (marketing-qualified lead) notification.

Why Watch in 2025: HubSpot is known for its ease of use and unified platform, making its AI features very accessible to sales teams that might not have dedicated ops or IT support. In 2025, HubSpot is rolling out more advanced AI (they’ve codenamed some initiatives like “Breeze” which includes an AI prospecting workflow agent).

For companies that prefer a lighter-weight, user-friendly CRM, HubSpot’s AI capabilities can level the playing field with larger enterprises. A VP of Sales or CMO can appreciate that HubSpot’s AI helps align sales and marketing – for instance, the AI can automatically qualify and route leads, or suggest the best time for sales to follow up on a marketing campaign response. The ChatSpot functionality is quite cutting-edge; by giving every rep a conversational AI interface, it can drastically reduce the friction of using CRM data (which in turn means better adoption of the system). As AI continues to evolve, expect HubSpot to integrate more with everyday sales motions (imagine a voice-enabled ChatSpot on your phone summarizing your pipeline or coaching you before a call). If you’re a HubSpot shop, leveraging these AI features is a no-brainer. And if you’re considering sales platforms, HubSpot’s momentum in AI plus its all-in-one nature make it a top tool to consider for 2025, especially for inbound-focused sales teams or those wanting an easy yet powerful system.

4. Outreach (with Kaia AI) – AI-Enhanced Sales Engagement

Overview: Outreach is a leading sales engagement platform widely used by SDR and sales teams to manage multichannel prospecting sequences at scale. In recent years, Outreach has supercharged its platform with AI, notably through Outreach Kaia (Knowledge AI Assistant) and other machine learning features. Outreach helps sales teams execute and automate their email, call, and social outreach, and now AI is woven in to provide real-time guidance and automation during those activities.

Key Features & Strengths:

Kaia Real-Time Conversation Intelligence: Outreach Kaia is an AI assistant that joins your sales calls (e.g., Zoom meetings or phone calls) and provides live support. During a call, Kaia can transcribe the conversation in real time, display relevant “battle cards” or info based on keywords, and even suggest answers to questions. For example, if a prospect asks about pricing and that triggers the keyword, Kaia might pop up your pricing page or a prepared response for the rep to use. It’s like having a virtual sales coach whispering in your ear, ensuring you don’t fumble key details. Post-call, Kaia generates a summary and highlights action items, so reps don’t have to take intensive notes (17).
AI-Powered Email & Content Suggestions: Outreach uses AI to help craft better emails and sequences. It can analyze what content or subject lines are getting replies and suggest improvements. There’s also sentiment analysis – Outreach’s AI can detect email reply sentiment (e.g., is the prospect interested, brushing you off, or asking to unsubscribe) and automatically adjust the sequence (for example, move them to a nurture track if they seem mildly interested, or task a human follow-up if they signal strong interest). This ensures leads are handled appropriately at scale without one-by-one human triage.
Predictive Lead Scoring & Deal Insights: While Outreach is primarily for top-of-funnel engagement, it has expanded into deal management. Its AI can monitor ongoing email threads and meetings to assess deal health (similar to a light version of what Clari or Gong do). It might recommend adding more touches for a prospect who hasn’t responded in a while or flag deals with no executive engagement as high risk. Outreach also introduced Intent Reporting that uses AI to gauge which contacts are showing buying signals across the sequence.
Efficiency Gains: The practical effect of Outreach’s AI features is a significant efficiency boost. Teams using Outreach often report being able to manage 2-3× more accounts or leads per rep, thanks to automation. With AI, those gains extend further: reps save time with auto-generated call notes, they get coaching without needing a manager on every call, and new SDRs ramp up faster by following AI prompts. Outreach cites that teams using its platform improve outbound prospecting results substantially – while exact figures vary, one case study saw a 50% increase in meetings booked after rolling out Outreach with AI enhancements, attributed to more timely touches and better messaging.

Why Watch in 2025: Outreach has been a pioneer in the sales engagement space and continues to lead with AI innovation (competing closely with Salesloft, another platform, which also has AI features). If your sales development or outbound team is large, a tool like Outreach with baked-in AI is almost essential in 2025 to remain efficient and effective. It directly aligns with Trend #4 (Multichannel Outreach) by providing a single system to coordinate email, calls, and social touches – and the AI ensures this coordination is smart and adaptive. Outreach’s Kaia is also a standout; as remote selling remains prevalent, having real-time AI support in virtual meetings is a competitive advantage. Sales leaders should watch Outreach because it’s likely to keep integrating more AI (they acquired Canopy, a revenue intelligence firm, indicating more predictive deal analytics to come). In summary, Outreach is a top tool for any organization looking to scale outbound sales, and with its AI capabilities, it helps not just scale activity, but improve the quality and impact of each interaction. It’s a platform truly built around how modern sales teams work, making heavy use of data and AI to refine the human touch.

5. Gong – AI Conversation Intelligence & Revenue Insights

Overview: Gong is the poster child of AI in conversation intelligence. It records and analyzes sales calls, meetings, and emails to deliver insights that help improve sales effectiveness. Gong’s platform creates a “reality layer” of customer interactions – meaning it captures what was actually said in sales conversations (as opposed to what a rep might input into CRM). Using AI, Gong turns this trove of unstructured data into actionable coaching and deal guidance. By 2025, Gong has expanded its capabilities to cover not just call analytics, but broader revenue intelligence, making it a key tool for sales enablement and management.

Key Features & Strengths:

Call Recording & Transcription: Gong automatically records sales calls (Zoom, Teams, phone, etc.) and transcribes them with high accuracy. But it’s not just recording – it’s analyzing everything. Gong’s AI parses through calls to identify topics discussed, talk ratios, questions asked, competitor mentions, and more. Sales leaders get visibility into every conversation without being there.
AI-Powered Insights and Trends: Gong crunches thousands of calls to find patterns. For example, it might discover that deals that mention “budget” in the first call have a 2x higher close rate, or that successful reps ask 5+ open-ended questions on discovery calls while lower performers ask fewer. It provides these insights to enable data-driven coaching. Gong can flag risky behaviors too, like if a rep is doing too much talking (say, a talk-to-listen ratio of 80/20 when the best practice is around 55/45).
Deal Warning Signals: Beyond coaching, Gong has features for deal management. It can alert managers if a key meeting hasn’t been scheduled, or if stakeholder engagement is low. For example, Gong might highlight that in a certain deal, no next meeting is on the calendar or the champion hasn’t spoken in a while – signs the deal might be stalling. It also tracks sentiment over time, so you can see if a deal’s correspondence is turning more negative or less frequent, prompting intervention. Some companies credit Gong with helping them increase win rates and forecast more accurately due to these early warnings.
Coaching and Onboarding: For sales managers, Gong is a godsend for coaching. You can easily find coachable moments (e.g., filter to all calls where pricing objections occurred, to coach reps on handling that). It also allows creating scorecards or trackers for reps’ calls, either manually or using AI suggestions. New reps ramp up faster by listening to top performers’ calls (Gong can compile a library of “good calls” on specific scenarios). This scales best practices – frontline managers have reported spending more time on proactive coaching rather than shadowing calls, because Gong surfaces what to coach on automatically.

Why Watch in 2025: As sales becomes more virtual and data-driven, Gong remains one of the most powerful tools to ensure quality in sales interactions. It directly addresses Trend #4 (digital engagement) by extracting insight from those digital interactions, and Trend #1 (AI co-pilots) in the sense that it’s like an AI coach sitting in on every call. In 2025, Gong and similar platforms (Chorus, etc.) are increasingly being used not just by sales, but by customer success and marketing to understand customers. Gong is extending into forecasting and has features to summarize account status across touchpoints. For CROs and VPs, Gong provides a level of visibility and team improvement that’s hard to achieve otherwise. It basically answers: “What’s happening on all those calls and meetings? And how can we do better?” With Gong’s AI, you can correlate behaviors to outcomes, making it clear what tweaks will boost revenue. Competitively, if your team is using Gong and your rival isn’t, your reps might simply be better prepared and coached in each deal. That’s huge. So, Gong is absolutely a top tool to consider. Even if you use another conversation intelligence tool, the concept is vital – and Gong currently leads the pack in AI sophistication and market share, making it the one to watch (and beat). By leveraging Gong, sales leaders can create a culture of continuous improvement fueled by real customer voice data, driving sustained revenue gains.

These five tools – Martal, Salesforce Einstein, HubSpot, Outreach, and Gong – represent some of the best of AI sales automation today. They each address different pieces of the sales puzzle, and in many cases can complement one another. For instance, we often integrate Martal’s outbound platform with CRM (Salesforce/HubSpot) so that AI-generated leads flow into the CRM where Einstein or HubSpot’s AI can then nurture them further. Or using Outreach alongside Martal for teams that want to run their own sequences internally while Martal runs in parallel as an external boost. The common thread is that AI is at the core of these solutions, enabling smarter, faster execution of sales activities that were historically manual and time-consuming.

When evaluating AI sales tools, consider your team’s specific needs:

Is top-of-funnel pipeline generation the bottleneck?
Do you need better visibility and coaching for your reps?
Are you trying to enhance your CRM workflow?

Perhaps you need a bit of all of the above. Importantly, ensure any tool you choose can integrate with your existing systems and has the usability your team will embrace. The best AI tool is the one your team actually uses – so look for intuitive interfaces and strong support/training from the vendor.

One encouraging note: adopting AI in sales doesn’t have to be an all-or-nothing overhaul. You can start small, like using Einstein just for email drafting, or Martal for a pilot campaign in one region, or Gong for one team’s calls – and then expand once you see results. Each of the tools above has customers who started with a trial or a limited scope and then grew usage as ROI became evident. The key is to get started, learn, and iterate.

Finally, keep an eye on emerging tools as well. Areas like AI-driven proposal generators, contract analysis, or AI for sales training simulations are growing. But the five tools we covered are a great starting point given their proven track records and robust capabilities.

Martal’s Tiered AI-Powered Outbound Strategy – Get Results with Cold Calls, Emails, LinkedIn & More

Leveraging AI in sales is not just about technology – it’s about strategy. At Martal, our approach to AI-powered outbound sales is built on a tiered, multi-channel strategy that combines the best of automation with a human touch. We use cold calls, cold emails, LinkedIn outreach, appointment setting, outsourced lead generation expertise, and B2B training in a synchronized way to maximize engagement with target prospects. Here’s how our strategy works and why it delivers superior results:

Multi-Channel Orchestration: As discussed in the trends, reaching prospects on multiple channels is critical. Our outbound campaigns typically blend email + LinkedIn + phone calls in a cohesive sequence.

For example, an outreach cadence might start with an AI-personalized email, follow up with a LinkedIn connection and message, then a call from an SDR, etc.

Each touchpoint is informed by the last – if the prospect clicked a link in the email, we reference that in the call. AI plays a big role in optimizing this: our platform analyzes which channel a prospect is most responsive to and tailors the sequence accordingly.

This omnichannel approach ensures we meet prospects where they are, and it’s one reason Martal’s clients see 4–7× higher response rates than standard single-channel outreach (13).

Agentic AI + Human SDRs (“Hybrid” model): We deploy AI agents to automate 80% of repetitive work – things like sending initial emails, handling follow-ups to no-responses, logging activities, and even qualifying questions via email (14).

But we don’t leave it all to AI. Our experienced outsourced SDRs (human agents) oversee the process, step in for live conversations, and handle nuanced interactions. This tiered system means AI does the volume, humans do the nuance. It’s incredibly effective: the AI can scale personalized outreach to hundreds or thousands of contacts, while our human team engages only once interest is shown, ensuring no opportunity is lost due to lack of personal touch. We also train our team and clients’ teams – providing B2B sales training on how to work alongside AI and how to convert the leads that AI nurtures. This integrated approach amplifies results while maintaining quality control.

Appointment Setting and Beyond: Martal’s ultimate goal for clients is to fill their calendar with qualified sales meetings. Through our B2B appointment setting service, AI-driven lead generation and persistent multi-channel touches, we identify interested prospects and then our team confirms their fit and sets up appointments with our client’s sales reps.

We handle the back-and-forth of scheduling (leveraging AI to offer optimal meeting times) and ensure a warm handoff. Because we engage prospects across calls, emails, and LinkedIn, by the time a meeting is booked, the prospect often has a positive impression of our client’s brand (having seen valuable content or insights in our outreach).

This makes the first sales meeting more productive and increases the chance of moving to proposal/quote. Essentially, we serve as your AI-augmented SDR department that not only can find leads but converts them into real opportunities.

Why it works: Our tiered strategy recognizes that AI and humans each have strengths. AI brings speed, scale, and data-driven precision – it never forgets to follow up, it learns the best send times, it diligently logs every activity. Humans bring creativity, empathy, and complex problem-solving – they can navigate nuanced objections, build rapport, and adapt on the fly. By marrying the two, Martal offers a solution that outperforms purely manual sales development and is far more effective than a “pure AI” approach with no human oversight. We’ve invested 15+ years of sales expertise into training our AI (and our people), so clients benefit from both cutting-edge tech and battle-tested tactics.

If you’re a sales or marketing leader looking to accelerate growth in 2025, we invite you to experience this firsthand.

We’ll evaluate your current outbound approach and show you how our AI-powered outbound strategy can fill your pipeline with qualified leads. In this no-obligation call, our experts will share how a tailored mix of cold email, LinkedIn outreach, calls, and AI touchpoints could work for your business – and outline the kind of results you can expect.

Our aim is to provide actionable insights. If it seems like a fit, we can explore engaging our AI SDR platform and team to become your growth engine.

Book your free consultation and take the first step toward transforming your B2B sales through AI-powered outbound. Let’s unlock your next phase of revenue growth, together.

By now, it’s clear that AI sales automation is not about replacing salespeople – it’s about empowering them. The trends and tools we’ve covered all point to one thing: when used correctly, AI lets your team focus more on what they do best (building relationships and strategy) by handling the heavy lifting (data, research, routine outreach, analysis). In 2025, B2B sales is at an inflection point. Those who embrace AI will find themselves closing more deals with less effort, while those who don’t risk falling behind in efficiency and effectiveness.

As you consider implementing AI in your sales organization, remember to start with clear objectives (e.g., “increase SDR productivity by 50%” or “improve forecast accuracy to >90%” or “boost lead conversion rate by 2×”). Then pilot one or two technologies that align to those goals, get quick wins, and scale up. Change management is important – involve your team, address their questions, and celebrate their successes as they adopt these new tools.

At Martal, we’re optimistic about the future where AI and humans work hand-in-hand to create smarter sales processes and stronger customer connections. The five trends reshaping B2B sales in 2025 – AI sales agents, hyper-personalization, predictive analytics, multichannel engagement, and tech stack consolidation – all reinforce the central theme: sales is becoming more intelligent. With the right strategy and tools, your team can harness that intelligence to outperform the competition.

References

FAQs: AI Sales Automation

What’s the best AI tool for sales automation?

The best tool depends on your goals. For outbound lead generation, Martal AI SDR offers an all-in-one solution with data, outreach, and SDR support. For CRM enhancement, Salesforce Einstein or HubSpot Sales Hub excel with built-in AI features. If call coaching or conversation insight is a priority, Gong leads in conversation intelligence. Choose a platform that fits your tech stack and supports your sales motion.

How can AI be used in sales?

AI supports every stage of the sales cycle. It helps identify and qualify leads, personalize outreach, forecast revenue, automate admin tasks, and analyze conversations. Reps save time, managers get better visibility, and organizations close more deals with greater efficiency. AI enhances performance by making sales workflows more data-driven, timely, and scalable.

Can I use AI to generate sales leads?

Absolutely. AI tools can identify sales leads, enrich lead data, detect intent signals, and qualify leads automatically. Platforms like Martal use AI to generate sales leads and prioritize them based on firmographics and buyer intent, enabling faster, smarter pipeline growth without relying solely on manual research.