Why AI SDRs Matter – and What They’re Missing

AI SDRs are promised to revolutionise sales, but are they solving core challenges or adding more noise?

AI SDRs are generating a lot of hype lately, with notable players like 11x raising $50 million and Artisan raising $11 million as investors back bold promises of fully automated sales. The pitch is enticing: AI SDRs aim to handle lead sourcing, outreach, and follow-up to book meetings with your ideal customers, automating what was traditionally manual and resource-intensive. But are they genuinely addressing the core challenges faced by sales teams, or just offering another automation layer dressed in AI jargon?

One of the first principles I learned early on is to “be greedy when others are fearful and fearful when others are greedy.” When I see massive funding rounds on such quick timelines, my instinct is to be cautious. Sustainable, profitable businesses aren’t built on hype alone; they emerge from a deep understanding of the problem space and delivering real value to end-users. I think AI SDRs haven't yet cracked the problem-space and I'll explain why.

At their essence, AI SDRs tap into lead databases like Apollo, pull contact information, conduct basic prospect research, and craft a "personalised" message using AI-driven prompts. From there, they generate sequences of emails designed to convert leads into meetings. But when we look under the hood, these tools resemble automation scripts more than intelligent systems—more code than AI. The actual “AI” component handles message creation and limited research, with much of the real sales legwork and strategy still left untouched.

This raises a critical question: Are AI SDRs transformative, or are they merely automating the superficial aspects of outreach without solving the deep-seated challenges of sales itself? A closer look suggests that many AI SDRs fall short of the true potential of AI in sales, highlighting the need for a more thoughtful, human-centred approach.

Problem 1: Overgeneralising Complex Sales Needs

Every organisation is different, and so is every sales cycle. Yet, a fundamental flaw in many AI SDR solutions is their overgeneralisation of sales processes. The typical pitch promises to solve "the problem of templated outreach," claiming that AI-driven personalisation—gathering some research and context to craft a better cold email—outshines human capability. But here’s the catch: even the most perfectly crafted message is meaningless if it’s sent to the wrong person. If the recipient isn’t the ideal customer profile (ICP), the quality of the message won’t make a difference.

Problem 2: Product Quality Concerns

To compensate for their limitations, many AI SDRs resort to brute-force tactics, deploying high volumes of messages to maximise reach across the TAM. While this “spray and pray” approach may yield some leads, it carries a serious cost: it risks brand reputation and long-term prospect relationships by prioritising quantity over quality. This kind of indiscriminate outreach quickly alienates prospects, reduces engagement rates, and exhausts valuable leads, leading to diminishing returns.

The core issue is that most AI SDRs rely on shallow automation, with simple sequencing tools and minimal AI “dusting” that adds little real value to the process. It’s more a facade of intelligence than true innovation. This superficial automation approach not only fails to address the deeper challenges in sales but can actively harm clients’ sales efforts by creating noise without genuine insight or adaptation. Effective sales development requires precision, strategic thinking, and genuine relationship-building—qualities often lacking in these high-volume, low-touch AI solutions.

Problem 3: Wrong Focus Area

Where AI could add real value is not just in automating outreach but in synthesising large volumes of data to fine-tune lead identification. AI's strength should be in spotting patterns, uncovering prospects previously overlooked, and highlighting specific touchpoints unique to each lead—areas a human SDR might miss. This ability to deliver precision rather than simply amplify volume represents the real transformative potential of AI in sales. Instead of repeating SaaS’s mistake of one-size-fits-all solutions, AI SDRs need to prioritise specificity, enabling sales teams to target with purpose and relevance, rather than just frequency.

Problem 4: Premature Product Expansion

Many AI SDR companies are branching out too quickly, rolling out new products like AI cold callers or AI marketers before refining their core offering. This scattershot approach dilutes their focus, as they jump from one feature to the next without fully solving the foundational issues faced by sales teams. Rather than expanding prematurely, these companies would benefit from adopting the principle of "Take a simple, basic idea, and take it very seriously."

The real value lies in mastering one specific area—whether it’s outreach automation, lead qualification, or messaging personalisation—before diversifying. By focusing deeply on solving a single aspect of the sales process, AI SDRs could bring genuine innovation and quality to market, rather than spreading themselves thin across features that feel half-baked and ultimately fail to deliver on their promises.

Problem 5: Wrong Brand Positioning

AI SDRs are currently positioning themselves to appeal to highly tech-enabled companies—organisations that already use sophisticated tools and automation for their sales processes. But this approach neglects a massive segment of the market: traditional, non-tech-enabled industries where AI-driven sales development could make a real impact. Industries like manufacturing, maritime, financial services, and advisory have substantial sales needs, but they often rely on personal, human-centred outreach and relationship building. These sectors aren’t clamouring for automation that bypasses the human touch, especially not from AI avatars.

The brand positioning of many AI SDRs only exacerbates this disconnect. An AI avatar as the “face” of a sales process may appeal to tech-savvy sectors, but it misses the mark for industries still anchored in personal rapport and trust. For example, I recently spoke with a Slovenian pallet manufacturer with contract values exceeding $1 million, a company unfamiliar with most digital sales tools. They’re wary even of entrusting outreach to another human, let alone a fully automated AI avatar. The result? AI SDRs often fail to address the real pain points of industries where they could provide the most transformative value by targeting only those already tech-enabled.

AI SDRs need to rethink their approach, adjusting their branding to appeal to organisations that prioritise human relationships in sales. Rather than pushing avatars, AI SDRs should position themselves as tools that augment human-led outreach, providing value by blending AI’s efficiency with a human’s relational expertise.

A Better Way Forward: Service-as-a-Software (SaaS 2.0)

As I’ve spoken about before on LinkedIn, the future is shifting towards “Service-as-a-Software” (SaaS 2.0) rather than traditional Software-as-a-Service. Unlike SaaS, which often piles on more tools, Service-as-a-Software outsources the outcome entirely, allowing companies to sidestep technology complexity. This model isn’t about offering more tools—it’s about delivering outcomes, a direction that the original SaaS should have embraced. While the software market is large, the service market (i.e. labour market) is manitudes larger, presenting massive opportunities for disruption.

Where traditional agencies are constrained by human capital bottlenecks in tasks like research and data synthesis, an AI-driven workforce can automate these processes, freeing humans to focus on what they excel at—using intuition and fostering relationships.

Consider this example: a traditional setup might require one employee to serve every five clients to maintain a high-touch experience. However, an AI-empowered agency could enable one employee to manage over 5 times the clients, significantly reducing operational costs while enhancing scalability and personalisation. With the advent of Service-as-a-Software, companies no longer need to manage complex tech stacks; instead, they can seamlessly outsource the entire service, shifting focus solely to outcomes.

Our take: While every business needs a salesperson, not every business needs a sales tool.

Service-as-a-Software provides a scalable, high-touch solution, marrying AI-driven efficiency with human expertise—achieving cost-efficiency without sacrificing depth or relational impact. This is the new standard, empowering businesses to scale, grow, and prioritise outcomes in ways traditional SaaS or agencies simply cannot. While a SaaS model could scale to even more clients per support employee, it often sacrifices the relationship-driven service that many clients still value.

The future of business isn’t just software or service. It’s a fusion of both.

"AI eats software, now salaries + services"

To disrupt the labour market, you need to actually provide a labour service with real people in the foreground.

The AI-agency model, therefore, represents a scalable, high-touch solution—one that balances cost-efficiency with the depth of personalised support. It brings the best of both worlds, leveraging AI to extend the agency’s capacity for managing more clients at lower costs, without losing the relational aspects critical to successful, long-term client partnerships. This is the new standard, empowering agencies to deliver growth, scale, and personalisation where it was once impossible.

The Paradox: Cluttered Inboxes and Diminishing Returns

The rise of AI tools has unleashed a flood of content, automation, and accessibility, saturating every digital space with endless streams of information. These tools promise efficiency and scale, but in doing so, they create a paradox: as content becomes abundant, meaningful connections become scarce. AI-driven interactions, once novel, now overflow in our inboxes, notifications, and feeds, making it harder to discern what truly matters. The industry may, ironically, be worsening the very problem it set out to solve.

In this era of media saturation, our finite attention becomes the most valuable asset. People are naturally starting to seek authenticity amid the noise. This abundance prompts a shift from quantity to quality, as individuals crave genuine connection, thoughtful engagement, and clarity. The real opportunity isn’t in automating for sheer output—it’s in using AI to cultivate deeper, more meaningful interactions. Those who embrace this shift, harnessing technology for value over volume, will lead the way in a cluttered digital landscape.

The commoditisation risk with AI SDRs is real—over-reliance on scripts leads to robotic, repetitive interactions, stripping away authenticity. As more companies adopt similar AI-driven processes, differentiation fades, and brands risk blending into a sea of sameness. To stand out, AI should enhance, not replace, the human touch, blending efficiency with personalised nuance to avoid falling into a commoditised rut.

I believe we’re coming full circle: in-person relationships will regain importance. COVID led to a distancing of people and services, yet in an era of overwhelming abundance, people search for authenticity.

With infinite channels, reach, and repetition at everyone’s fingertips, true value no longer lies in creating more but in creating with purpose. This saturation era will usher in a return to relationships, to messages that matter, and to trust built over time. The real opportunity is with those who view AI not as a means to increase volume but as a means to elevate value—those who use it to enhance connections rather than automate them.

Why This Matters: The Role of Technology as an Uplifting Force

At its core, technology exists to uplift society, to make life better, faster, and more affordable. It’s a function of exchange—a way for humanity to trade knowledge for progress in one of the few truly positive-sum games.

Technology, at its core, is the transformation of knowledge and imagination into tools, processes, and systems that amplify human capabilities and remove limitations. It’s humanity’s way of overcoming constraints—physical, cognitive, and social—by creating solutions that extend what we can achieve alone. Beyond practicality, technology reflects our values and aspirations; it’s a multiplier that frees us from repetitive tasks, allowing time for creativity, learning, and exploration. The direction technology takes mirrors our priorities, embodying both our potential and our responsibility. At its best, technology reshapes human experience by creating new possibilities and expanding what it means to live and work meaningfully.

Of course, technology can bring unintended consequences, such as social media’s role in promoting addictive behaviours. And there are real ethical concerns—job displacement, for example, is a reality. Companies may claim to “empower” employees, but with targets like revenue per employee in mind, increased efficiencies often mean fewer jobs. Sales, a field built on human connection, risks losing its relational edge as AI handles more interactions. Over time, replacing human roles with AI could result in a salesforce less attuned to the psychological nuances essential to meaningful client relationships.

This is why it falls on conscientious technologists to steer innovation with intention, thinking beyond hype and short-term gains. We may not foresee every impact, but the difference between a quick fix and a long-term solution is usually clear. It’s our job to drive technology forward with a mindful approach—one that prioritises lasting benefit and genuine human progress.

What shall we do?

Now while I understand this blog post pay offend a lot of people building in this space - don't take it as that. This is just my perspective on the industry itself - I may be wrong, and I'm willing to be wrong. But thinking from first principles something just doesn't add up for me.

So, what does that mean for what we’re doing at Throxy? For us, it’s about keeping things as straightforward as possible:

• Setting the right values from the outset—knowing what we’re doing and why.

• Embracing long-term thinking.

• Collaborating closely with customers to solve their real problems, step by step.

• Aligning our brand with our customers' needs and aspirations.

• Deeply understanding the problem space to create solutions that genuinely work for them, not just products that work for us.