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Adoption

AI training applied to B2B sales.

We teach the team to use AI in concrete sales tasks, with their own cases and criteria to avoid automating the wrong things.

Barcelona · 2026
Adoption

A team that knows when to use AI, how to validate it and how to turn it into a sales routine.

We teach the team to use AI in concrete sales tasks, with their own cases and criteria to avoid automating the wrong things.

Process

How we implement AI in your company.

01Week 1

Diagnosis

We map ICP, data sources, CRM, cadences and bottlenecks. We leave with a prioritized backlog.

02Weeks 2-4

Configuration

We connect tools, data and prompts into auditable workflows. First in sandbox, then with real accounts.

03Weeks 5-8

Activation

We train the team, measure replies, adjust criteria and leave documentation to operate independently.

Tools

A connected AI stack, not a collection of tools.

We work with tools B2B teams can maintain: CRM, enrichment, outbound, automation and reporting with clear ownership for each system.

See details

Enginy AI

AI outbound

Prospecting agent to identify accounts, write first touches and detect sales-ready leads.

Clay

Enrichment

Data, signals and personalization at scale without losing control of sources.

Apollo

B2B data

Account and contact research using ICP, territory, sector and role criteria.

n8n

Automation

Workflows across forms, CRM, enrichment, email and reporting without black boxes.

HubSpot

CRM

Pipeline, properties, scoring and reporting to measure what happens after the first touch.

Instantly

Outreach

Campaigns, domains, warm-up, deliverability and controlled follow-ups.

How we do it

Training that changes daily practice, not the satisfaction score

Most commercial training programmes have the same underlying problem: they're designed to be well-rated at the end of the day, not to change what the team does the following Monday. Techniques are explained in the abstract, role plays run with generic cases, and the team leaves with a sense of having learned something useful. Six weeks later, nothing has changed in practice. The problem isn't the training itself — it's that it wasn't anchored to the team's real context.

What differentiates training that works is that it works with real situations, not simulations. If the problem is that salespeople don't qualify well, we work with the opportunities currently in the CRM, with the deals lost last quarter, with the messages the team sent last week. Learning anchored to the team's concrete reality has a radically different retention and application rate.

Every training programme design starts by diagnosing what's failing in daily practice. Does the team not prospect because they don't know how, or because they have no time and no prioritisation criteria? Do they not close because the sales process is too long, or because the proposal arrives late and unfocused? Do they not adopt AI tools in sales because they don't trust them, or because no one has shown them where to insert them without risk? The diagnosis defines the content. Without diagnosis, training is generic.

We train commercial teams in outbound prospecting strategy, practical use of applied AI in sales, opportunity qualification and objection handling, and narrative and messaging for different sales contexts. Every module is built around situations the team will face this week, with the real clients they work with.

The success indicator isn't the satisfaction score on the post-training survey. It's whether the team does something differently the following Tuesday, and whether that change generates better conversations, better qualification, and measurable results. That's what we track, and that's what we pursue.

Diagnosis

Let's talk about your sales process.

Tell us about your team, market and current tools. We will show where AI can create pipeline and where it would only add noise.

The first call is not a sales pitch. It is a clear diagnosis of what is worth implementing.
ARQ Digital · Barcelona
hello@arq-digital.com
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