Disclaimer: This article provides general information and is not legal or technical advice. For official guidelines on the safe and responsible use of AI, please refer to the Australian Government’s Guidance for AI Adoption →
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A Journal of Business Research paper on AI in sales research identifies where AI adds value (lead scoring, CRM, forecasting) and where it stalls—the trust ceiling and the noise floor—plus why "Better Tech" does not equal "Market Share."
Where does AI actually win in the sales cycle?
The paper finds an "Asymmetry of Automation": AI excels at building-adjacent tasks (lead scoring, CRM data entry, predictive forecasting). When it comes to complex, high-stakes relationship management, AI-driven interventions often see a diminishing rate of return—the Trust Ceiling.
What is the "Noise Floor" and why does it matter?
As AI lowers the cost of outreach, the volume of low-quality interactions explodes. Genuine human attention becomes a scarcer and more expensive resource. The Productivity Paradox shifts to the sales floor: efficiency gains in building do not save us if customer acquisition scales harder than code generation.
What should builders take away?
Stop thinking only about how smart your product is. Start caring about how it actually reaches a human who trusts you. Sales is now the primary deployment problem, not a research footnote.
💡Quick note
This issue shifts from "builder's gold rush" to where AI actually stalls: the sales floor. A Journal of Business Research paper maps the trust ceiling and noise floor, plus tools and Crossing the Chasm. Part of the Weekly Deep Dive into AI and ML Advancements & Updates series.
Read this if you are:
Founders & Teams
Better tech does not equal market share. This issue spells out why distribution and trust are now the primary deployment problem—and why your Distribution-to-Build ratio matters more than your stack.
Students & Switchers
A clear picture of where AI wins in sales (lead scoring, CRM, forecasting) and where it hits a wall. Plus practical tactics for your first 100 users, cold outreach, and why "roast my prototype" beats a pitch.
Community Builders
When trust is the scarce resource, community and human connection become the moat. This issue frames why events, workshops, and genuine attention scale differently from AI outreach—and how to position your community.
AI Bits for Techies | Issue #6 | 25 Feb 2026
Your weekly Aussie-flavoured deep dive into what changed in AI/ML, what matters, and what to do next (without living on release-note social media).
This week in one breath: A Journal of Business Research paper maps where AI is winning in sales—lead scoring, CRM, forecasting—and where it hits a wall: the trust ceiling and the noise floor. As technical barriers to building collapse, customer acquisition and human trust become the primary deployment problem. Plus tools and reads for the week.
Journal Paper of the Week
Artificial intelligence in sales research: Identifying emergent themes and looking forward (Journal of Business Research) (DOI)
The Context
Most of the AI discourse has obsessed over the "builder's gold rush." New frameworks, automated coding agents, and instant deployment. But the centre of gravity has moved.
As the technical barriers to product creation collapse, we are hitting a massive friction point: the human element of the transaction. While we can automate the generation of a product, we cannot easily automate the generation of trust. This paper from the Journal of Business Research maps exactly where AI is successfully infiltrating the sales cycle—and, more importantly, where it is stalling. (DOI)
The Method & Results
The researchers conducted a systematic longitudinal analysis of emergent AI themes in professional sales, synthesizing data from high-growth sectors to identify where AI adds value versus where it creates noise. The gaps are wild.
The "Asymmetry of Automation": AI excels at "building-adjacent" sales tasks—lead scoring, CRM data entry, and predictive forecasting.
The Trust Ceiling: When it comes to complex, high-stakes relationship management, AI-driven interventions often see a diminishing rate of return.
The "Noise Floor": As AI lowers the cost of outreach, the volume of low-quality interactions explodes, making genuine human attention a scarcer and more expensive resource.
Why It Matters
This paper is a clean example of why "Better Tech" does not equal "Market Share." In an era where anyone can build a functional MVP over a weekend, the "Productivity Paradox" shifts to the sales floor. The efficiency gains in building do not save us if the cost of customer acquisition scales harder than the speed of code generation.
For builders, the shift is clear. Stop thinking only about how smart your product is. Start caring about how it actually reaches a human who trusts you. Sales is now the primary deployment problem, not a research footnote. (DOI)
Best for: Automating sales engagement and outreach sequences. Outreach uses AI to intelligently suggest next-best actions, optimize follow-ups, and scale personalized communication—making sales workflows more efficient and less manual. https://www.outreach.io/
Gong
Best for: Conversation intelligence and deal analytics. Gong applies AI to sales calls, emails, and meetings to uncover patterns, coach teams, identify risks, and improve close rates—turning sales activities into actionable insights. https://www.gong.io/
Drift
Best for: Conversational lead capture and qualification. Drift's AI chat engages visitors in real time, qualifies them automatically, and routes high-intent prospects to sales reps—helping teams convert traffic into real leads. https://www.drift.com/
Book recommendation (because your brain deserves more than changelogs)
Crossing the Chasm — Geoffrey Moore
Why it matters: Moore's work is the grounding counterweight to this week's paper. It zooms out and maps the psychological landscape of technology adoption. His core argument is blunt: great tech dies in the "Chasm" because founders focus on features while customers focus on trust and social proof.
The gist: Where this week's paper measures the operational infiltration of AI in sales, Moore exposes the deeper, structural human costs of adoption. The "cloud" of AI hype stops looking fluffy very quickly when it hits the hard wall of enterprise sales. Same story. Different layers.
Geeky thought of the week
Great tech dies in the Chasm because founders focus on features while customers focus on trust and social proof.
This week's paper measures where AI infiltrates sales operationally—lead scoring, CRM, the trust ceiling. Moore zooms out and maps the psychological landscape of adoption: the deeper, structural human costs. The "cloud" of AI hype stops looking fluffy very quickly when it hits the hard wall of enterprise sales.
Same story. Different layers.
Housekeeping (so we stay honest)
This is general information, not legal advice. If you ship user-facing AI, be transparent about where AI is used, what it cannot do, and where humans stay in the loop.
Partially. AI can handle lead gen and initial outreach, but high-stakes sales are about risk mitigation and human accountability—things a model cannot yet provide.
Why is "Trust" becoming more expensive?
As AI-generated outreach floods every channel, the signal-to-noise ratio collapses. When "Attention" is scarce, the cost to prove you are a real human with a real solution increases exponentially.
What is the most effective lever for a builder today?
Improving your Distribution-to-Build ratio. If you spend 20 hours building, you should be spending 80 hours figuring out how to get it into a user's workflow.
How do I get my first 100 users for my startup without a marketing budget?
The fastest way to your first 100 users isn't through paid ads; it's through unscalable, manual effort. Stop pitching and start solving micro-problems. Tactics include the "Reddit Shadow-Op" (finding people complaining about a specific problem and offering a scrappy, free tool to fix it), building tiny side-project calculators that funnel traffic to your main app, or cold-DMing ideal prospects and asking them to brutally roast your prototype.
Why is my startup not getting any signups after launch?
You have likely fallen into the "Builder's Trap"—engineering a product in a complete vacuum. Building the tech is no longer the hardest part of a startup; distribution is. It doesn't matter if you've engineered the most advanced agricultural drone for taking soil readings if you haven't stood in a muddy field to ask a farmer about their actual workflow. Features don't sell products; solving painful, real-world problems does.
What is a "Minimum Evolvable Product" and why is it better than an MVP?
A Minimum Evolvable Product (MEP) focuses on survival and adaptation rather than just viability. When you launch, your earliest version only needs to do one thing: survive contact with a tiny group of desperate early adopters. Instead of building a polished final form, an MEP is designed to be scrappy, adapt fast, and evolve strictly based on the harsh, real-world feedback those first users give you.
How do I convince users to switch from an established software competitor?
The biggest friction point for users leaving an incumbent platform is migrating their data. To steal your first 100 users, offer "Concierge Migration." Offer to manually move all their data into your system for them, entirely for free. Yes, it means doing tedious data entry at 2 AM, but doing the unscalable, dirty work that major tech companies refuse to do builds intense, long-term customer loyalty.
What is the best cold outreach template for a new B2B SaaS?
The best cold outreach doesn't look like a sales pitch at all. Instead of asking for a meeting, ask for advice. Send a message to your ideal user on LinkedIn saying: "I'm a founder building a tool for [their industry]. I think it's great, but it might also be total rubbish. Would you be open to roasting it for five minutes?" Humans can't resist giving their opinion, and a high percentage of those who critique your app will end up signing up because they feel a sense of ownership over the solution.
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