The next evolution of AI in sales: Regie.ai’s co-founders share 6 predictions for 2025

Over the past 30+ years of leading sales teams, I've had a front-row seat to watch wave after wave of technology transform how sellers sell. From the rise of computer telephony integration in the ‘90s to the Salesforce’s launch of the first customer relationship management (CRM) platform, each advancement solved certain problems – while inevitably creating new ones.

But what we're seeing now with AI feels different: it's not just another tool in our stack; it's fundamentally changing how we think about sales engagement.

Together, Sri and I founded Regie.ai because we saw an opportunity to push the boundaries of what AI could do for go-to-market (GTM) teams. While everyone else was focused on building point solutions, we were thinking about how to make AI a true partner in the sales process. We launched our first AI-powered solution before ChatGPT made generative AI a household name, and we've maintained that forward-thinking approach as the technology has evolved.

Now, as we look ahead to 2025, we're seeing several key trends that we believe will reshape how GTM teams work in the wake of AI. Some of these changes are already underway, while others are just beginning to emerge. But all of them point to a future where AI becomes an even more integral part of the sales process – not by replacing human sellers, but by amplifying their capabilities in new and powerful ways.

Let's start by looking at how we got here because understanding this journey is crucial to seeing where we're headed next.

{{cta-1}}

Where we've been: The convergence of sales & AI

Throughout my career, I've gotten to observe how sales organizations have structured themselves around available technology, with each advancement reshaping not just our tools but our entire organizational models. While we were evolving our sales approaches, AI was on its own transformative journey that would eventually revolutionize how we think about sales engagement. 

Here's how these parallel paths developed and ultimately converged:

• 1980s - early 1990s: The beginning of the end of “door-to-door selling”:
  • ‍In sales: Obviously, door-to-door selling had been around a while by this point, but I came into it close to the end of its heyday. (I liked to call it a "professional paper route.") Our teams organized around geographical territories because that's what the era demanded. Without technology, we established our entire selling motion on building face-to-face relationships. While this created strong connections, it was incredibly difficult to scale.
  • ‍Meanwhile, in AI: Early researchers were quietly developing the first neural networks, though none of us in sales knew this would matter to us decades later.‍
• Mid-1990s: The “smile and dial” era:
  • ‍In sales: The emergence of computer telephony integration (CTI) transformed everything. Suddenly, we could run phone systems on affordable PCs. This technology didn't just give us new tools: it gave birth to entirely new organizational structures. Inside sales teams emerged because we could now put hundreds of reps on phone banks and reach customers at unprecedented scale.
  • ‍Meanwhile, in AI: Speech recognition research was gaining momentum, though accuracy remained too poor for commercial use. The foundations were being laid, but practical applications were still years away.‍
• Early 2010s:
  • ‍In sales: The arrival of sales engagement platforms (SEPs) marked a watershed moment in sales technology. For the first time, we had a true workflow engine built specifically for sales teams. These original SEPs did basic – yet critical – tasks like:
    • ‍Email tracking: They gave reps visibility into when leads engaged with emails (e.g., opens, link clicks). These insights helped sellers identify when their messages gained attention, enabling them to prioritize follow-ups at the right moment.
    • ‍Task management: These platforms acted as digital to-do lists for sales teams, organizing daily tasks like sending follow-up emails or making calls. By consolidating these actions into one interface, they eliminated much of the guesswork and manual tracking from a rep’s workflow.
    • ‍Basic sequencing: Early SEPs introduced simple email sequencing tools, letting reps pre-schedule a series of emails to be sent over time. While customization was minimal (compared to today’s standards), this feature helped sales teams maintain consistent engagement with leads without relying on constant manual effort.
    • ‍Centralized communication history: Early SEPs also acted as repositories for all communication with a prospect. Reps could easily review prior interactions to better tailor their future outreach.
  • ‍Meanwhile, in AI: Natural language processing made some key breakthroughs, though commercial applications remained limited. In 2012, Google's neural networks successfully recognized cats in YouTube videos without explicit programming. While this might sound trivial now, it marked the beginning of modern deep learning. Few of us in sales realized this would eventually transform our entire industry.‍
• 2018-2019: The “spray & pray” era:
  • ‍First signs of convergence: The first wave of AI-powered automation tools arrived in sales. Though still primarily template-based and lacking true context understanding, they helped reduce the volume of repetitive tasks sellers performed and streamlined follow-ups with segmented email lists or autoresponder campaigns. However, these tools didn’t allow for much targeting precision or message personalization, which began to create fatigue and distrust with prospects.‍
• 2020-2022:
  • ‍Early integration: We launched Regie.ai's first AI-powered solution, focusing on intelligent content generation and personalization at point (and at scale) before it became mainstream. We saw the potential for AI to be more than just another tool - it could be a true partner in the sales process. Early adopters began seeing this vision, though many remained skeptical.‍
• 2022-present:
  • ‍True convergence: ChatGPT catalyzed widespread AI adoption within the industry, and something fundamentally changed. For the first time, we weren’t just organizing our sales teams around technology - we were organizing with it. This marked a crucial shift from previous eras where teams adapted to tech, to one where AI and human sellers work as true collaborators.

Looking at this journey, you can see how sales and AI developed along parallel paths for decades before finally converging in recent years. While sales teams were evolving their organizational structures around each new technology, AI was gradually developing the capabilities that would eventually transform those very structures. This convergence is what makes the present moment so exciting - and what makes our predictions for 2025 particularly compelling.

{{cta-1}}

Prediction #1: Agentic AI will go mainstream in 2025.

You might’ve noticed it already, but the copilot era is already starting to wind down. While this kind of AI assistant technology certainly did a great job of introducing organizations to AI's capabilities, they're ultimately just another tool requiring human involvement and supervision – and a significant contributor to tech stack bloat. In 2025, we expect to see a mainstream shift toward agentic AI solutions: autonomous software systems that can perceive their digital environment, make decisions, and take actions that drive toward specific goals — all with minimal human input. This shift will move the market away from the “yet another piece of tech your reps need to learn” scenario introduced by copilot products and toward solutions that deliver discrete units of work outright for your team. 

What moves us past simple copilot automation is agentic AI’s ability to handle complex workflows that previously required significant human orchestration. Instead of simply generating personalized email drafts – which was novel a year ago for generative AI – agentic AI (via AI Agents) will be able to execute end-to-end parts of that rep workflow, including sourcing ICP leads, analyzing their account and person level data, identifying engagement patterns, sending relevant emails at dynamic intervals, and looping reps in for follow up on only the most engaged audiences - all while continuously learning and adjusting based on results. 

The real game-changer, however, is in how these systems handle intent and engagement. Instead of forcing customers through predefined paths, AI Agents are able to understand and consider the context of each interaction and adapt its approach accordingly. This means better experiences for customers and more efficient operations for businesses.

Take the example of cold calling. While copilot tools once helped summarize call notes and action items, AI Agents can warm up leads through other lower intent channels with relevant, well-timed touches, while simultaneously prioritizing call tasks with personalized call scripts for only the most engaged audiences for your reps to call on. 

The most successful companies won't just be the ones who adopt agentic AI: they'll be the ones who strategically deploy it to handle process-driven tasks while empowering their human team members to dedicate their time to activities that require creativity, empathy, and strategic thinking. Early adopters are already seeing the impact, using Agents to turn cold prospecting into warm lead follow-up and handle the kinds of repetitive and mundane “necessary evil” tasks that would typically consume hours of an SDR or prospecting sales reps’ time.

{{cta-1}}

Prediction #2: "Agent washing" will hit new heights.

We're already seeing vendors slap the "AI Agent" label on solutions that can't actually work independently or make decisions – and, unfortunately, we expect to see this trend explode in 2025. True AI Agents can take ownership of entire workflows - they analyze situations, make informed choices, and execute complex tasks without the need for constant human oversight. But many so-called "Agents" are just rebranded automation tools, pre-programmed sequences, or strung-together workflows. 

The distinction matters because it impacts the real value these tools can deliver. True AI Agents can transform how sales teams work by taking ownership of time-consuming processes and making intelligent decisions about when and how to engage prospects. Meanwhile, many solutions marketed as "AI Agents" are actually just basic automation tools that are limited to sending pre-written messages or following rigid, predefined sequences. These simplified tools add to sales teams’ tech fatigue without solving the fundamental challenges they face: too much work and not enough resources to deliver it effectively.

Our advice to GTM leaders: don't let clever marketing fool you into thinking you're investing in true AI capabilities. Consider questions like: Can the system actually reason through problems and make autonomous decisions? Can it truly own a workflow end-to-end? Can it adapt its approach based on learned outcomes? These are the capabilities that separate genuine AI Agents from solutions riding the latest wave of AI hype.

📖 READ NEXT: “AI sales agents vs. “agent washing”: What to watch for when buying an AI solution”

Prediction #3: Tech & team consolidation will accelerate.

We expect that 2025 will be a pivotal year for consolidation – both in terms of technology and team structure. The current landscape of point solutions isn't just unsustainable; in fact, it's actively hindering rep productivity.  In a recent State of Sales Report, Salesforce found that 66% of reps reported feeling like they were drowning in tools. This tech overwhelm, combined with mounting tasks and expectations, has created a perfect storm: according to Gartner, 77% of sellers now struggle to complete their basic tasks efficiently. Clearly, when you find yourself in a spot where your reps are juggling dozens of tools and can't even finish their core responsibilities, something’s gotta give. 

Specifically, we predict that consolidation will happen on two fronts. 

1. The first front: tech stack consolidation. Specifically, we'll see companies move away from fragmented point solutions and toward integrated platforms that can handle multiple aspects of the sales workflow. But this won’t just be about having fewer vendors to manage: it'll be about creating seamless workflows where AI, specifically AI Agents, can operate effectively across your entire stack.
2. The second front: team transformation. As AI takes on more of the repetitive, process-driven work, organizations will need to fundamentally rethink how they structure and deploy their human talent. But let’s be clear: this isn't about reducing headcount. Instead, it's about elevating your team's capabilities. We're seeing forward-thinking organizations using AI to complement their existing teams, allowing them to tackle previously impossible workloads.

The key here will be in understanding that technology and team consolidation go hand in hand. Companies that simply consolidate their tech stack without reimagining how their teams organize themselves in the wake of AI will miss the bigger opportunity. The winners in 2025 will be those who can successfully merge their human and AI capabilities into cohesive, efficient GTM motions.

{{cta-1}}

Prediction #4: 2025 will be the “Year of the phone.”

While digital channels have dominated our focus in recent years, we predict that 2025 will mark the phone's comeback as the most effective tool in every seller’s arsenal. But don’t worry: this resurgence won’t look anything like the “smile and dial” days.

What will drive this shift? Agentic AI. Think of it this way: AI Agents are able to take over the time-consuming tasks that currently bog down sellers – like sourcing leads, researching accounts, drafting emails, and managing follow-ups. That leaves your human sellers freed up to focus on what technology can't replicate: building authentic connections through conversation. This isn't just more efficient; it's more effective for everyone involved. Prospects get a better buying experience, reps get to focus their time and effort on more meaningful, high-value activities (and the kinds of tasks that they actually enjoy doing), and organizations see better conversion rates.

The timing is perfect for this shift. As email inboxes overflow and LinkedIn messages pile up, a well-timed, personal phone conversation stands out more than ever. So, in 2025, we expect to see leading organizations restructuring their sales motions around this reality, using AI to identify when prospects are most receptive to calls while empowering their reps to focus on what technology can't replicate – building authentic connections through conversation.

Prediction #5: API integrations will become business-critical.

Success with AI won't just be about having the best models: it’ll be about having the best connections. The most effective AI systems in sales will seamlessly integrate with CRMs, sales engagement platforms, intent data providers, and more. They'll pull insights from multiple sources to make informed decisions about when and how to engage prospects and finally deliver on the promise of right person, right time, right message.

This integration will be particularly crucial as AI systems become more sophisticated in their decision-making capabilities. Just as a human sales rep needs access to various data points to make informed decisions, AI Agents need to be able to pull information from multiple sources to make truly informed decisions. They'll need to understand not just what's happening in your CRM, but also engagement signals from your automation platforms, intent data from third-party providers, call dispositions from your dialer, and historical performance data from your sales engagement platform, to create relevant and timely experiences.

We're already seeing this trend emerge, but by 2025, it will be a fundamental requirement for any serious AI sales solution. Companies that can't provide deep, seamless integration across the sales tech stack will struggle to compete.

{{cta-1}}

Prediction #6: GenAI native startups will outmaneuver incumbents in 2025.

The next wave of AI innovation won't come from established software giants adding AI features to their existing products. Instead, it will come from startups that are building with AI at their core. Why? Because today's enterprise software platforms were architected around human workflows and human limitations – not the capabilities of AI Agents. And try as they might, it’s an extremely hard pivot to make.

Think about your typical CRM system. It's essentially a collection of forms and fields that force humans to translate their rich, contextual work into structured database entries. This made sense when software was just a tool for humans to use. But in a world where AI Agents can understand natural communication, automatically extract relevant information, and take autonomous action, these rigid systems become unnecessary intermediate steps.

This architectural mismatch extends to business models too. Traditional software companies are built around selling seats and licenses – essentially charging for access to their tools. But AI is ushering in a fundamental shift toward outcomes-based pricing, where companies pay for actual work completion rather than just workflow enablement. As Jaya Gupta notes in her LinkedIn article “How Systems of Agents will collapse the enterprise stack,” this shift represents a classic innovator's dilemma for incumbents whose revenue models, sales incentives, and GTM strategies are still optimized for the old world of software licensing.

In 2025, the winners in enterprise AI won't be the companies that bolt AI features onto legacy systems. They'll be the ones who rebuild from the ground up with AI-native architectures that collapse traditional software boundaries and deliver measurable business outcomes. For incumbents weighed down by technical debt and outdated business models, this transition will be nearly impossible to navigate. For AI-native startups, it represents one of the largest value creation opportunities in enterprise software history.

Final thoughts

As we look to 2025, we're incredibly optimistic about AI's potential to transform sales. But we're also clear-eyed about the challenges. Success won't come from simply deploying AI tools: it will come from thoughtfully integrating them into your workflows in ways that amplify, rather than replace, human capabilities.

That's the future we're building toward, and we couldn't be more excited about what's ahead. The companies that embrace these changes and thoughtfully integrate AI into their sales processes will find themselves with a significant competitive advantage. Those that don't risk being left behind as the industry evolves.