AI sales assistants: what they actually do, and how to evaluate one

The single most useful distinction when buying is between assistants that do administrative work and assistants that offer judgement. Administrative work means summarising, drafting, extracting and noticing absence. Judgement means telling you which deal will close or which lead deserves attention first. The first category is dependable because it operates on the text in front of it. The second depends on your history, and history is where small businesses are thin.

This is not an argument against scoring. It is an argument for treating a score as a way to order a queue rather than as a fact. Used that way, even a mediocre score beats arrival order. Used as a forecast input, it produces confident planning errors.

What happens when it is wrong

Ask directly. Is generated content labelled as generated. Can a user correct it in place. Does the correction change anything, or is it discarded. Is there an audit trail of automated changes. Vendors who have designed for being wrong tend to have thought harder about the rest of the product too, and the answer tells you more than a feature list.

Where does the assistance appear

If the assistant lives in its own tab, usage will decay after the novelty passes. If it appears on the deal record the seller already has open, next to the reply box, it gets used. This is a boring point and it predicts adoption better than capability comparisons do.

What does it need from us

Ask what the assistant depends on: does it need call recordings, does it need messages routed through the platform, does it need a minimum history to be useful. The answers tell you whether you are buying a tool or committing to a change in how your team works, and the second is a much larger decision.

Most teams shortlisting an AI sales assistant end up comparing three kinds of product, and the differences are more about where the assistant lives than about how clever the model is. Sales engagement platforms such as Salesloft and Outreach put the assistant inside an outbound sequencing tool: the AI drafts and personalises cadence steps and summarises replies, and the platform sits on top of a separate CRM that still has to be kept in sync. HubSpot's AI features (sold under the Breeze name) live inside the HubSpot platform, so the assistant sees whatever HubSpot already holds, and the useful capabilities tend to be gated by which hub and tier you are on. HelloGrowthCRM takes the third route: the assistant is part of the CRM itself, so summaries, drafted follow-ups, field extraction and quiet-record flags all act on the same record the rep is working from, with WhatsApp and calls already on that record.

Price the comparison per seat and per month, and include the CRM the assistant depends on. A sales engagement platform is an additional subscription on top of the CRM licence, and platform-bundled AI often requires a higher tier than the one you are on. For reference, HelloGrowthCRM paid plans are ₹899 per user per month plus 18% GST in India (about ₹1,061 all-in) on the Growth plan, which includes the AI features and 2,500 AI credits per user per month rather than selling them as a separate subscription, and there is a free plan to run the two-week test on before paying anything. Competitor pricing changes often, so confirm current figures on the vendor pages before you build the comparison sheet.

Before evaluating anything, spend an hour setting up templates and reminders properly in whatever you already use. That baseline solves a surprising amount of the problem an assistant is sold against, and it gives you something to measure improvement from. If a paid assistant cannot clearly beat a well-configured baseline on your own data in two weeks, the correct answer is not yet rather than never. Revisit in a couple of quarters, because this category is moving quickly and the answer may genuinely change.

Related reading on AI and automation in sales: AI CRM, sales automation, features, lead management software, CRM for small business, and tools.