You’re probably underestimating the competition

PLUS: Get to really know your prospect in seconds and the rise of shadow agents

From the aibl team

This week I had the chance to dig into a study of 3,000 mid-market firms that exposed a significant blind spot: we are drastically underestimating our competitors’ tech adoption. The researchers found that the vast majority of business leaders believed their competitors were far behind where they actually were, to the tune of nearly 25 percentage points.

When these leaders were shown the hard data proving their rivals were already ahead, it triggered a significant response to invest more, but specifically in established hardware.

If you think you are in or ahead of the pack, the data suggests you may well be very wrong.

However, the study revealed a critical nuance that speaks directly to the current moment with AI. While discovering that competitors were using robotics drove firms to immediately increase their own investment plans by nearly 18%, learning about high AI adoption rates did not spark the same urgency.

The researchers suggest that because AI is still viewed as experimental rather than entrenched like robotics, leaders are hesitant to follow the herd without a clear playbook. We are in a “wait-and-see” trap where businesses acknowledge the tech is growing but are paralysed by the lack of mature use cases compared to physical automation.

For those of us focused on Agentic AI, this is the signal to move from experimentation to integration. The study implies that firms currently treat AI as a novelty rather than a structural necessity, unlike robotics which they view as essential for survival.

We cannot afford to wait until AI feels as “safe” and “mature” as a factory robot. By the time Agentic workflows become the standard “safe” bet, the early adopters who pushed past the experimental phase will have already compounded their advantage. Don’t wait for your competitors to prove it works; the data shows they are likely already doing it, quiet and unseen.

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Playbook of the week

Walk Into Every Sales Call Knowing the Prospect

How to use AI to scan job ads, blog posts and reviews so you know what a prospect really cares about before you ever write to them.

A founder selling a back-office service into clinics and professional firms hit a wall familiar to almost every outbound team. His product handled scheduling, admin, billing and follow-up calls. The value made sense, but the outreach didn’t. His “AI-powered lead gen” tool scraped homepages, dropped the text into a generic prompt and produced polished but vague messages.

He sent thousands and received little in return. Without real context, every prospect looked identical and every “personalised” email disappeared in the noise. He needed the system to understand the lead before he wrote a single line, so he built a way to do precisely that.

How it Worked

He began collecting signals from places where companies reveal their real priorities. Job postings showed where capacity was stretched. Blog updates and product announcements highlighted upcoming initiatives and long-standing frustrations. Case studies indicated who they were trying to impress, and leadership interviews exposed the pressures shaping their decisions. Public reviews added a final layer by showing what customers felt wasn’t working, in their own words.

Read on to learn more.

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NEWS

We’re still collecting real-world wins, misfires and everything in between. If you’ve got a case study that deserves a spotlight, we want to hear it.

Drop a line to John@aiblmedia.com

1. Why Mid-Market Businesses Are Moving Fast But Feeling Stuck, Dec 2A recent roundtable with IT leaders, consultants and investors across North America threw up the same pattern we keep hearing. Plenty of pilots on the go, but the blockers haven’t shifted. No one knows who owns what. Middle managers tread carefully. Governance slows work that ought to move at a steady clip.The early take from a whitepaper based on those sessions points in the same direction. Leaders aren’t hunting for another tool. They want help setting priorities, drawing clear lines and giving their teams the backing to move work out of pilot mode.It aligns with what we’re seeing. The mid-market has the intent and, to varying degrees, the kit. What’s missing is the structured approach to turn one-off wins into regular practice. The firms that pull ahead will be the ones that build that habit, not the ones that bolt on more software.
2. A Simple AI Security Playbook for the Mid-Market, Dec 4Security is often the main brake on AI adoption. Most teams feel the strain: plenty of intent, limited time and headcount, and a sense that even small AI projects raise real exposure. This article argues for a simpler path. Warning, acronyms follow, so feel free to pass along to your IT security lead in 3,2,1…Start with established frameworks like NIST instead of drafting your own guidance. Focus your protection effort on the workflows that matter most. Bring in an MSSP for the specialist work you can’t cover in-house. Keep the basics of governance, data quality and ethical use in place so clients and stakeholders know the work is safe.Taken together, it’s a reminder that AI security doesn’t need to swell into a heavy compliance programme. A few well-chosen guardrails give teams room to move and the confidence to push projects forward.
3. Google Workspace Studio And The Rise Of Shadow Agents, Dec 3What happens when every knowledge worker gets access to agent-like tools? Google is turning Workspace into a place to build automations rather than documents. Workspace Studio lets staff create Gemini 3 powered agents that move across Gmail, Drive and systems like Salesforce without touching code. For mid-market firms this lowers the bar to trying agentic workflows on real work. The risk is familiar though. Without clear ownership and guardrails, it can swap manual busywork for a new sprawl of overlapping automations that no one fully sees or steers.

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PRODUCT SPOTLIGHT OF THE WEEK

We’ve been using Apollo.io for a while and it consistently comes up in mid-market conversations. It’s a broad data and outbound tool that helps teams find companies and contacts, build quick segments and get early outreach moving without taking on a heavy contract. The appeal is speed, coverage and the control it gives operators who want to test a market before committing to something larger.

It also fits the shift toward lighter, modular stacks. Teams are pulling back from all-in databases and building around tools they can adjust as they learn. Apollo often sits in the middle of that because it’s easy to work with and steady on cost.

There’s a 14-day trial, which is long enough to see how it handles your segments and whether it gives you the signal you need to take the work further.

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Quote of the week

“By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.” 

Eliezer Yudkowsky, Founder, MIRI