Where does AI deliver measurable results in sales first, in mid-sized companies?
First where your sales team repeats the same work every day: answering product and pricing questions, preparing meetings and quotes, searching for knowledge inside the company. These tasks come up often, are easy to measure and quick to change. Do not pick the most exciting AI topic. Pick the three levers with the best balance of value, effort and risk.
Why sales is a good place to start
In sales, three things that matter for getting started with AI sit close together: a lot of recurring work, a direct link to revenue and results you can see. Whether a customer gets the right answer today or in three days is noticed by everyone in the company. That is exactly why sales works better than an abstract pilot that nobody feels in daily work.
The three typical first levers
1. Answering questions from inside and field sales
Which variant fits this customer, what does the accessory cost, how does the complaint process work? An AI assistant that knows your product knowledge, your prices and your processes answers these questions by chat, voice or phone. That takes load off experienced colleagues and helps new ones get up to speed. More on the personal AI sales assistant
2. Preparing meetings and quotes
What is the company working on right now, who is at the table, which questions should you expect? AI summarises the information, suggests a conversation guide and creates a first draft of the quote. Deciding and signing stays with people.
3. Follow-up and CRM upkeep
Summarising meeting notes, recording next steps, keeping the CRM up to date: this is the work that most often gets left behind in sales. AI turns it into a draft within minutes, the salesperson checks it and approves.
Where it usually gets stuck in practice
The pattern I hear most often in conversations with managing directors: licences for Copilot, ChatGPT or Claude were rolled out, together with guidelines and a basic training. No goals and no priorities were set. Access is open, along the lines of: off you go, be more efficient.
That leads to usage, not results. Rolled out is not led. A tool on individual desks is the first step, a project is the second. Only when AI runs as a fixed part of a process and someone is accountable for the result does it count for the business. That is why AI is not an IT ticket. It's a business decision.
How to find your first three levers: the Shortlist Rule
No AI project without a shortlist: collect 10 to 20 ideas, sort them by effort, value and risk, pick three.
- Collect: ask your sales team where work repeats every week and where customers wait longest.
- Sort: rate every idea against three questions. How much value does it bring? How much effort does it take? What is the risk, for example with customer data?
- Pick: take the three ideas with the best balance. Not twenty at once, and not the one that impresses most.
- Assign ownership: each of the three levers gets one person who is accountable for the result, not a department.
How to measure whether it works
Before you start, define one metric per lever and write down today's value. For example:
- Time until a customer enquiry gets the right answer
- Preparation time per customer meeting
- Share of conversations fully recorded in the CRM
Compare after a few weeks. What cannot be measured does not go on the shortlist.
Frequently asked questions
Do we need a big AI strategy first?
To get started you need a clear decision on which three levers come first and who owns them. The strategy becomes more robust when it builds on first real results.
Who should own the introduction of AI in sales?
The managing director or the head of sales, not IT. IT takes care of operations and security. Which tasks a model takes on and which result counts is a leadership decision.
What about data protection and customer data?
Customer data only belongs in systems with a suitable data processing agreement, ideally processed in the EU. Clarify this with your data protection officer before you start. This is guidance, not legal advice.
How quickly do results show?
That depends on the lever. Well-chosen first levers connect to existing processes and therefore show in weeks rather than quarters. The precondition is that you have defined beforehand what you measure.
More answers
- How do you choose your first AI use cases?
- Why do AI pilots get stuck, and how does AI get into daily business?
- Where does AI pay off in marketing for mid-sized companies, and where not?
About the authorSelina Gaertner, AI for Leadership, Sales and Marketing. TÜV Rheinland certified AI Strategy Consultant, more than ten years in sales and marketing in medical technology, co-author of the Amazon bestseller “Fokus Mensch”.
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