People are “dating” AI bots. CEOs are being “advised” by digital agents. Doctors are using ChatGPT to draft patient notes. AI has moved on from “disrupting” the world to fundamentally rewiring it.

Sales is no exception. AI-powered prospecting tools and automated personalization have quickly changed how we operate — and how we sound.

These tools promise progress: faster pipelines, lead generation at scale, and more meetings booked. But beneath the metrics is a deeper issue. Trust is deprioritized in favor of speed, and buyers feel it. We stand at the precipice of an entire industry — one traditionally grounded in human interaction — flipped on its head.

We’re not moving toward better relationships or healthier bottom lines. We’re moving into the uncanny valley littered with poorly crafted cold outreach.

Creepiness is costing you

The “uncanny valley” originally described dolls or robots that look a little too close to humans — but just off enough to evoke unease. In sales, too much AI-driven personalization skews into the same territory.

Take the flurry of “personalized” notes that reference my college mascot or a podcast I was on. Recently, I received two messages on — both from sellers of hybrid collaboration tools.

One mentioned they were impressed by my career trajectory, and congratulated me on my football team’s win the previous night. The only issue? They mentioned the wrong team — a cardinal sin and the result of an AI hallucination.

The other noted they’d looked into our company’s model, and provided a quick assessment and a straightforward POV on where they thought we could benefit.

Guess which I responded to?

It’s understandable why so many sellers are turning to AI to automate: Nearly professionals report feeling burnout, and the majority are their quota.

The problem is the system itself and the misaligned incentives it runs on. Sellers are rewarded more for volume than value; pipelines are judged by growth, not quality. When you combine that pressure with tools that can blast thousands of messages in seconds, the result is predictable.

In the short term, this floods inboxes. In the long term, it corrodes credibility, laying the groundwork for buyers to become numb, suspicious and harder to reach, and placing a premium on real, human perspective.

Trust can’t be faked

Behavioral psychology and business research consistently reinforce one truth: Trust is the foundation of persuasion.

Research shows of people need to trust a brand before they’ll even consider buying from it. ones in stock performance, productivity and customer retention.

In my eyes, trust is built primarily through four signals: communication, competence, intent and consistency. Each of these takes time to build, and any of them can be lost in a single interaction.

And that’s where AI falls short. While it can mimic pieces of these, it can’t replicate the warmth, nuance and vulnerability that build real relationships. It doesn’t know when to slow down, when to ask better questions, or when to say “I don’t know.” Authenticity, even when admitting limitations, builds trust in ways that hollow personalization can’t.

People are already skeptical of AI in general: say they trust generative AI outputs, and 4 in 5 consumers can accurately content. By layering it into the very first sales interaction, companies lose more than deals. They lose long-term brand equity. They lose referral momentum. And perhaps most importantly, they lose goodwill — the invisible capital that fuels long-term growth.

Comfort is the last frontier

Especially in complex B2B environments, deals don’t close on information alone. They close on confidence, reassurance and human alignment.

During a recent call with a prospect, he was saying all of the right things, “we’re excited,” “we see the value.” But his posture was stiff, his gaze was uneven — subtle signs that, after two decades in sales, I’ve learned to recognize as hesitation.

After we hung up, the cues stayed with me, so I called the next day and asked directly. He admitted he hadn’t secured senior-level buy-in yet, but felt obliged to keep things moving after so much time invested. That unlocked a dialogue around real barriers to forming a partnership, laying the foundation for us to identify and align on actual, appropriate next steps (that ultimately helped us sign the deal).

Sometimes analyzing words on a transcript isn’t enough. You have to read between the lines and let human intuition guide you where the data can’t.

Because, at the end of the day, when people buy software, they’re not just buying a product; they’re also buying into a relationship.

Fully automated sales motions may win early with volume, but they often lose late. Without empathy, deals stall. Without rapport, onboardings fail. Without trust, renewals disappear.

In these cases, the lack of human interaction becomes a liability.

Sales runs on belief

As trust in institutions and media declines, buyers need more reassurance, not less. Companies have an opportunity to step up as reliable, responsive, human-first actors in their customers’ lives.

At its best, sales isn’t about pushing products. It’s about helping people find a better way forward. We just need to be intentional about how we use AI; not as a replacement for humans, but as a way to give them more room to do what matters.

No matter how sophisticated AI becomes, it can’t replace the moment of belief. The point where someone decides to trust you, your company and the future you’re offering. In an era of uncanny outreach, the most radical thing you can do is be unmistakably human.

is the senior vice president and head of growth at , a leading enterprise meal benefits platform. Landsman is a seasoned executive with more than 20 years of experience in SaaS and food tech sectors. His expertise spans startup scaling, partnership development, organizational leadership and market expansion. As former head of corporate sales at Seamless, his work helped to facilitate its merger with in 2013. At , Landsman led strategic partnerships and enterprise sales efforts, contributing to its 2021 IPO.

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led the round, which included participation from , , and .

With this latest financing, Dreamdata — which has dual headquarters in Copenhagen, Denmark, and New York — has raised $67 million since its 2018 inception. The company’s last raise was in December 2022 with an $8 million Series A led by . CEO declined to reveal at what valuation Dreamdata raised its latest round, saying only that it was “an incredibly significant increase” when compared to its previous venture funding.

Dreamdata’s goal is to provide “the most complete B2B buyer journey map anywhere by joining ads, website visits, emails, CRM  … into one clean timeline per account,” according to Turner. Examples of functions its platform can perform include syncing “high-intent” audiences to ad platforms such as or , triggering notifications to a sales team, or running marketing workflows.

“That gives marketers a trustworthy ‘single source of truth’ to see what’s working, prove ROI, and then act on it, with AI assistance,” Turner said. “We do both activation and attribution. We’re not just a reporting tool; we are building the operational infrastructure for the B2B marketer.”

, , , r and are among its “thousands” of customers.

AI has had a profound effect on many sectors such as biotech and cybersecurity, as many startups have added the technology to their platforms. Marketing is no exception, as Dreamdata is only the most recent marketing tech startup to get funding.

In February, marketing and personalization startup locked up an $80 million Series C led by , minting it as a new unicorn at a $1.2 billion valuation. Also in February, Toronto-based raised a $235 million growth round led by — the late-stage venture and growth investment arm of . The startup has a multichannel programmatic advertising platform that uses AI and automation to help with digital marketing efforts.

Overall, global venture funding to sales and marketing tech startups totaled $5.9 billion through Oct. 10, 2025, per Crunchbase . That’s down 11.9% compared to the $6.7 billion raised in the same time period in 2024.

Sustainable growth

Dreamdata operates its business under a SaaS model with a component of usage-based pricing. The company has more than doubled its annual recurring revenue while maintaining the same number of employees it had one year ago (50), according to Turner.

“We are operating with disciplined ambition via sustainable growth,” he said, noting that Dreamdata is focused on growing its business in Europe and North America.

One of Dreamdata’s biggest differentiators from traditional competitors, such as ’s Marketo Measure/Bizible, Turner claims, is that it’s designed for “forward-looking action” as opposed to focusing on what happened in the past.

, co-founder and managing partner of PeakSpan Capital, leads the GTM technology investing at the venture firm and said he’s been partnering with companies in the space for over 15 years.

“It is with that long-tenured perspective and context that I have developed a deep appreciation for the problem Dreamdata is solving. Accurate revenue attribution has been a persistent challenge for years and years, and the problem today is complex and multi-faceted,” he told Crunchbase News via email. “The modern customer journey is convoluted, spanning numerous channels and disparate touchpoints, so understanding with high confidence what contributes most to a conversion is incredibly complex.”

In Melymuka’s view, Dreamdata’s offering solves the challenge of revenue attribution while also leveraging signal data and AI to support activation and execution.

“Relative to other solutions in the market, Dreamdata delivers far and away the quickest time to value – despite the complexity underpinning the solution,” he said.

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After spending six years as a vice president at , Arjun went on to found , a consumer news ratings engine that was . There, he later led ’s AI Newsfeed. Anita was previously VP of marketing at .

The pair came to the conclusion that the days of relying solely on SEO or content marketing were long gone. So in October 2023, they teamed up with to start , an agentic AI platform that aims to help B2B companies establish credibility in relevant professional online communities — in other words, become influencers of sorts.

Previously, “companies wrote content that was indexed by , and prospective customers landed on the company’s blog via search. This playbook no longer works in the AI era,” Anita said.

“People no longer search the same way and are either passively browsing social feeds or actively researching on AI,” she added.

Enter Rocksalt. The company operates on the premise that for small and medium businesses to be discovered in this new age, they need to find a way to get their in-house “experts to build authentically credibility in the social forums where their audience hangs out,” noted Anita. Those forums include and communities.

“The problem for such ‘experts’ is that engaging on social forums is inefficient,” she said. “It’s hard to know which conversations are worth engaging in.”

The startup aims to help with that issue, she said, by surfacing “the most high-value conversations” so that it’s easier for executives and subject-matter experts “to engage consistently and build awareness in these feeds.”

Rocksalt claims it can help companies grow organically and build AI relevancy by having their executives be in online forums, engaging in discussions and answering questions, and it claims they can do it in just 10 minutes a day.

New funding for growth

To grow Rocksalt further, the San Francisco-based company has raised $3.5 million in seed funding led by , it told Crunchbase News exclusively. also participated in the round, along with angel investors such as , and President .

The company plans to use its new capital to expand to other platforms such as and . It also wants to add capabilities “to create and repurpose content to answer questions at scale.”

AI that understands intent

Anita is quick to differentiate Rocksalt from keyword monitoring tools for different platforms. Their offering, she maintains, is not keyword-based.

“We are an AI platform that understands the user’s intent and surfaces conversations that are beyond keywords,” she noted. “We also have comment-assisting functionality that guides users in engaging authentically without generating generic AI comments.”

Rocksalt, which operates on a SaaS model, has several customers including , and as well as close to 15,000 free users on its Slack and LinkedIn products.

Founders’ marketing pedigree

It’s not the first time the siblings have worked together. Anita also worked at The Factual in addition to serving in other senior marketing roles. Arjun said her marketing experience was crucial in starting Rocksalt.

“While building The Factual I learned how important marketing is to strategy and how I wasn’t very good at this because I tended to overly focus on product,” he said. “I swore that if I did another startup I’d have marketing support from day one, and that is what Anita brings to the mix.”

Meanwhile, Anita calls herself “an accidental entrepreneur.”

“Because we’re siblings, the trust issue was solved on day one and so we are able to move fast: He obsesses over product and data, I live in the customer conversation,” she said. “That complementary loop lets us course-correct in hours, not weeks.”

, partner at Lightspeed Venture Partners, said he was drawn to the founding team’s depth of experience.

“Rocksalt is helping to rewrite the inbound playbook,” he said. “Today’s savvy buyers trust experts, not a flood of marketing content designed for SEO. The leadership team at Rocksalt … is making it easier for businesses to invest in organic marketing. Inbound marketing will never be the same.”

AI marketing startups on track for funding high

Venture funding to startups at the intersection of AI and marketing has soared this year, Crunchbase data shows, and is on pace to match the high mark achieved in 2021.

Through the first half of 2025, startups in the space have raised more than $344 million globally, a giant leap compared to the $65 million raised in the first half of last year and already well over the $252 million raised in all of 2024. Marketing and AI-related startups raised more than $705 million globally in 2021, the peak year, according to Crunchbase data.

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The five-year-old e-commerce company became a unicorn last September after raising $200 million in a round led by Tencent Holdings and that valued the company at $1.1 billion, according to . Yijiupi also secured $100 million from . The financing brings the company’s over its lifetime to nearly $600 million. Other backers include and .

The digital retailer sells liquor and wine to offline retailers and convenience stores. But it’s diversifying as of late.

According to , Yijiupi has launched “a new website that has two separate channels-’alcohol, beverage and packaged food’ and ‘grocery and snacks.’ ”

As of last September, according to , the startup was operating in 83 Chinese cities. At that time, the publication reported that Yijiupi was aiming to hit a GMV (gross merchandise volume) of RMB 20 billion (or about US$ 2.83 billion) by the end of last year, up “from its more than RMB 12 billion (US$ 1.7 billion) figure in 2017.”

Overall, online retail sales in China have continued to exceed, and grow faster than, those in the United States, according to a recent referencing Chinese government data. Specifically, online retail sales in China totaled about $1.33 trillion in 2018, up nearly 24 percent from 2017, , a government agency.

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