More Leads, More Pilots, More Stakeholders: Sales and Marketing in the AI Era

Artificial intelligence is creating a cohort of startups that are growing revenue at a breakneck pace. It’s also upending the role of their sales and marketing teams.

While many of the attributes that made a business successful in the software-as-a-service (SaaS) era remain, taking products to market in the AI era has become more complex. This article unpacks some of the recent changes we’ve observed as the operating team for EQT’s early-stage investing arms.

The new sales

Let’s start with sales, where the arrival of AI has shifted the role to be more technical. Sellers who know their product and competitors well have always had an advantage. Yet the AI era requires all members of a sales team to handle detailed queries from customers and prospects, not just the sales engineers.

“Sales enablement is critical,” says Manny Medina, founder of EQT-backed AI monetization platform Paid. “You can’t afford to put team members who are mediocre sales talent in that role. With the velocity of product and market change, you need your best leading those efforts.”

The forward-deployed engineer has also become a must-have hire. This role ensures that the AI tool you’ve just sold becomes deeply integrated into a customer’s workflows, while bringing back real-world insights to your product and go-to-market teams.

“Forward-deployed engineers are this bridge between client and engineering,” says Stan Massueras, who leads a large part of the go-to-market team in Europe for AI voice startup ElevenLabs. “They add credibility to the voice of the customer.”

The hesitant buyer

Even with the right technical sales roles in place, not every business wants to run headlong into AI.

“Being AI-native and being very AI-forward as a product isn’t something every customer is equally excited about,” says Ed Steele, founding operator at AI job search tool Jack & Jill. “We have to take them on a journey, and we find that we have to build for two kinds of customers: the early adopters and the doubters.”

“Much like the early days of SaaS – where there was deep skepticism about the cloud and its safety – we have some convincing to do,” he says. ”Go-to-market teams face a mixed reception toward AI.”

Bringing AI into an organization is one of the highest-stakes decisions a company can make right now. That means more internal stakeholders and a more complex sales cycle.

“Who makes the call?” says Latané Conant, chief marketing officer at agentic AI customer service startup Parloa. “The lane of buying has become unclear as businesses now have execs in charge of AI and an AI innovation department as well as the CIO and business unit.”

To win over hesitant stakeholders, pilots have become a given in the selling process.

“Gone are the days when you can paint a vision, sign a contract, and leave the rest to the customer; instead, we are in an environment where pilots are everywhere,” says John Haddock, chief business officer at legal AI startup Harvey. “The best sales teams are continuing to bring value and build relationships throughout the pilot process.”

The build vs buy debate

While AI is creating new markets, it’s also causing some potential clients to question if they need to stump up for external tools. Can they just vibe code their own? The “build versus buy” debate, a hot topic in the early days of SaaS, has returned.

SaaS emerged because companies didn’t want large IT teams maintaining internal tools. But companies can have short memories, and right now they are swept up in the excitement of having the potential to do more with less.

At the EQT operating partner team, we’ve seen this movie before. We feel strongly that build isn’t going to win out over buy. Yes, vibe coding is transformative. It will absolutely change how companies prototype and improve personal productivity, replacing clunky spreadsheets with more streamlined automated solutions. But when it comes to operating mission-critical, customer-facing applications, the fundamentals of software management haven’t changed, and vibe coding simply isn’t fit for that purpose.

Software still needs maintenance, security and identity management. We believe most successful companies share a common discipline: protecting their engineering resources like a scarce asset and pointing them directly at customer problems, not internal tools. The hangover from vibe coding is coming faster than people expect. Once the excitement wears off, engineering leaders are going to sober up to the brutal reality of untangling a sprawling mess of AI-generated applications that no one fully owns or maintains. The pendulum will quickly swing back to buying software rather than building it.

Founders, however, have to compete in the market as it exists today. Hesitant buyers, new pricing models and more stakeholders – plus the build-versus-buy distraction – are all making the sales cycle longer and more complex than anything we saw in the SaaS era.

The startups getting this right are doing three things well:

• Hiring talent that can operate at the technical depth the product demands
• Not over-automating
• Treating buyer hesitation not as an obstacle but as the job.

Ultimately, they’re making sure they have a sales function that’s as thoughtfully designed as the product itself.

Winning client attention

Beyond sales, the AI revolution is also changing the role of startup marketing teams. As companies launch products more frequently, marketing needs to move fast to keep clients informed of the potential benefits.

“It can be a lot of work to match marketing to this pace, and user absorption becomes difficult,” says Katie Burke, chief operating officer at Harvey. “This makes being really clear on the critical problem you are solving and the ‘relevance’ of the solution important.”

Des Traynor, co-founder of AI customer service platform Fin, says he’s learned to release bigger and more finalized features rather than make incremental changes.

“You only get the attention on a feature once, so it’s just frankly easier if it arrives quite complete,” he says. “We struggle to market what we’ve built; we struggle to enable sales reps on the 20-plus new meaningful features we ship every week, and our customers need to understand all this to get max value from Fin.”

Fin also merges several new features into wider launch narratives. “Rather than saying ‘we have A/B testing, alerts, monitors, real-time issue detection, progressive rollouts, etc’, we just have an event that’s all about trust and safety,” Traynor says.

As AI disrupts both sales and marketing, the startups adapting well are doing four things right:

• Hiring talent that can operate at the technical depth the product demands
• Not over-automating
• Treating buyer hesitation not as an obstacle but as the job.
• Ensuring their customers maximize the value of all the new products they’re delivering.

Ultimately, the best-placed startups make sure their sales and marketing functions are as thoughtfully designed as their products.