The February 3 plenary meeting concluded with a conference dedicated to practical uses of artificial intelligence. Following contributions from Delphine Duc-Goninaz, Marketing Director, Jean-Pierre Thieblemont, Sales Director, Pascal Roy, Regional Director, and Mabéo Industries, the workshop-conference outlined ways to improve sales productivity and presented real-world use cases aligned with the on-the-ground realities of Gifec members.
How does AI improve commercial productivity in industry ?
Artificial intelligence improves sales productivity when it takes on time-consuming tasks and frees up time for customer relationships and decision-making. In industrial environments, where sales cycles are long and offerings complex, this impact is first seen in the organization of day-to-day work.
The most time-consuming sales tasks
Industrial sales teams spend a significant share of their time writing meeting reports, rewording technical information, preparing materials, searching for contextual data, and conducting competitive intelligence. These tasks fragment sales time and reduce responsiveness to customers and distributors.
AI can step in upstream of the sales process to qualify prospects, organize available information, and help the sales force prioritize high-potential contacts.
Some applications can also identify prospects similar to existing customers, making prospecting easier for comparable profiles.
Reducing preparation time without automating the sales relationship
AI produces usable summaries, rewrites technical content in language adapted to the audience, and can also prepare working materials based on existing information.
It can also draft sales arguments, anticipate common objections, and suggest wording suited to the industrial context.
The gains do not come from full automation of the sales process, but from reducing the time spent preparing and reporting.
Refocusing teams and creating more consistent sales practices
For sales management, the benefit is twofold. On the one hand, teams refocus on analysis, negotiation, and managing customer relationships. On the other, practices become more consistent, as AI tools implicitly standardize how information is produced, written, and summarized.
This consistency is also seen after the meeting, in the quality of follow-ups, reminders, and documents sent to customers.
Understanding AI to use it better in sales activities
AI is useful when it fits into existing sales practices. Team members need to know when to use it and be aware of its limitations.
What AI can produce in a commercial context
In industrial sales, AI can deliver a summary, rephrase content, prepare a support document, or extract the key points from a large volume of information. It works from existing elements and provides a quickly usable output.
Knowing how to formulate an actionable request
Its effectiveness depends directly on how the request is phrased. An imprecise prompt produces a generic response. A contextualized request (audience, expected technical level, intended use) generates usable content.
In a prospecting approach, AI can also assist with writing sales messages or LinkedIn posts, while respecting the company’s tone and positioning.
Identifying situations where AI adds no value
AI does not replace sales analysis, customer relationships, or negotiation. It does not assess relationship dynamics, arbitrate strategic choices, or assume responsibility for a decision. Knowing these limits prevents inappropriate uses and strengthens trust in the tool.
Integrating AI into practices without changing roles
Ideally, AI prepares or suggests, while leaving teams in control of exchanges and decisions.
In industrial organizations, gradual integration makes adoption easier. Teams keep their professional reference points while benefiting from strong operational support.
Using AI before, during, and after the meeting
During the meeting, AI helps deliver a tailored demonstration, with personalized materials. It facilitates note-taking and the completion of visit reports in CRM tools. Some solutions also make it possible to record and summarize video meetings (Copilot, Read AI, Tactiq).
AI bias and hallucinations: how can we ensure the reliability of commercial content ?
Artificial intelligence generates content from existing data without verifying its accuracy or its consistency with a specific commercial context.
It can therefore produce factual errors or inappropriate wording. These risks are particularly sensitive for uses such as meeting reports, CRM entries, or customer-facing materials.
In an industrial sales context, a meeting summary, sales argument, or technical rephrasing generated by AI must always be reviewed and validated before any external use. This control step is an integral part of using the tool.
To secure these uses, the internal process should define:
- the types of content that can be produced with AI ;
- the validation steps ;
- human accountability in commercial decisions.
Whatever the use case, it is important to remember that AI remains an assistance tool. Its effectiveness depends above all on how it is integrated into the day-to-day work of sales teams.
