Eighteen months into the real production wave of AI in B2B sales, the gap between hype and what mid-market teams are actually shipping is wider than ever. This is our point-in-time read on what's working, what's overhyped, and what the next 12 months look like — based on the engagements we've run across SaaS, services, and industrial B2B.
B2B sales orgs in 2026 are running on two tracks. Track one: large enterprises (1,000+) buying expensive AI sales suites and watching adoption stall in pilots. Track two: mid-market companies (50-500) building thinner stacks — usually Claude or ChatGPT plus their existing CRM — and getting real workflow change.
Track two is winning. The gap between buying AI and using AI is enormous at enterprise scale, and small at mid-market scale, because mid-market teams cannot afford to buy what they will not use.
Our blunt take: if you are spending more than \$3K/month total on "AI sales tools" at a 30-person company, you are probably overbuying. The actual leverage comes from your team being fluent with a horizontal LLM platform applied to your specific workflows.
Universally adopted, universally valuable. Sales reps run target accounts through a research prompt before every meeting. Saves 20-45 minutes per meeting. Increases meeting quality measurably.
Strong adoption among reps who take notes. Pasting raw call notes into a structured Discovery Synthesizer Project produces a cleaner picture for handoff and follow-up. Major Salesforce productivity win without buying a separate tool.
Highest-leverage workflow we see at mid-market. Time savings of 60-80% per proposal are common; quality holds or improves when good past examples are loaded into the Project.
Reliable when the AE has done their job in discovery. Brittle when discovery is thin — Claude cannot conjure context. Make discovery quality a prerequisite, not an afterthought.
Marketed as replacements for human SDRs. In practice, the output gets prospects to ask "is this a bot?" and your sender reputation drops. Mid-market teams are quietly turning these off. The exception: highly templated, low-stakes nudge sequences — but those barely needed AI in the first place.
Recording calls is useful. The AI-generated "insights" tabs in conversation intelligence tools largely go unread. We still recommend Gong/Chorus/etc. for the recording and search functionality — just discount the AI features.
Generic personalization ("I saw you went to State, go Tigers!") is anti-personalization in 2026. Buyers see through it instantly. Reverting to actual research-based outreach is winning.