Artificial intelligence in companies: where is it worth investing?
Has your company already tried artificial intelligence, but still cannot see where the return is? The challenge is to identify problems that justify changing the way you work.
Artificial intelligence in companies can speed up processes and improve access to information, but it does not create value just by existing. AI consulting should start from the needs of the business, not from the tools.
In which areas can artificial intelligence create value?
The best opportunities arise where there is a frequent problem, available information and an improvement the company can measure. You do not need to transform the whole operation to start.
Customer service and support
When the team repeatedly answers the same questions, AI can help look up information, prepare replies and route requests. The goal is to free people for situations that need individual follow-up.
Delicate complaints and exceptional situations still require human intervention. Automating wrong replies makes the problem worse.
Administrative work and operations
Checking documents, classifying requests, summarizing information and preparing records are activities where AI can reduce repetitive work. With process automation, you reduce manual data transfers.
If a task follows fixed rules, a conventional automation may be cheaper. AI is useful when documents or language need to be interpreted.
Sales and sales follow-up
AI can support meeting preparation, organize contact histories and flag requests that need a reply. It can also make it easier to prepare proposals.
But it does not replace commercial judgement. If contacts are poorly recorded, AI does not solve the source of the losses.
Analysis of information for decisions
Identifying patterns in requests, comparing reasons for cancellation or summarizing customer comments can help a manager see problems that go unnoticed. The value depends on the quality of the data.
Convincing answers can be wrong. Financial decisions require checking.
How to identify opportunities that justify investment?
Start by asking which problem costs the most time, money or opportunities. Then confirm whether AI is suitable.
Identify delays, repeated errors and information that is hard to find. Record the frequency and impact of each problem.
Criterion | Question to answer |
|---|---|
Impact | Does the problem affect costs, revenue, quality or capacity to respond? |
Frequency | Does it happen regularly or is it an exception? |
Information | Is there data and instructions reliable enough? |
Integration | Does the solution need to communicate with the current systems? |
Control | Which decisions require human validation? |
How to calculate the value of an AI project?
Before implementing, record the time, errors and resources involved in the task.
Imagine, in an illustrative example, that a team spends 30 hours a month classifying requests. If a solution cut that work to 10 hours, that is 20 hours freed up per month. At an estimated internal cost of €18 per hour, that corresponds to €360 a month of potentially recovered working capacity.
This is not an automatic saving: the time freed up needs to be put to productive use.
Include licences, integration, training, supervision and maintenance. Constant corrections can cancel the benefit.
Value can also appear in speed of response or service capacity. Measure those indicators.
When is it not worth using artificial intelligence?
Sometimes it is enough to simplify processes or use features that are already available.
We advise against starting with AI when:
- The process changes constantly: there are not yet minimum rules that allow results to be assessed.
- The data is not reliable: the information is incomplete, duplicated or out of date.
- The workload is low: the cost of implementation exceeds the likely benefit.
- The risk of error is high: the company cannot ensure the necessary review.
- The team will not use the solution: there is no availability to change routines and define responsibilities.
Preparing people also counts. The European Commission clarifies that companies that provide or use AI systems must take measures to support the AI literacy of their staff, taking into account the context of use. It is not enough to install a tool and assume everyone knows how to assess its results.
Where should an SME start?
Start with a limited, relevant and measurable pilot project.
Define an owner, an objective and how errors are handled. Compare performance with the previous situation, including supervision.
If the results are consistent, consider expanding. If not, stop or rework the project. A specialized partner helps choose the right pilot and measure it, which can save time lost to trial and error.
Before hiring an AI solution or partner, ask four questions:
- Which data will it use and where is it stored?
- Who validates errors and incorrect answers?
- How is the return measured, and with which indicators?
- What happens to the data and the work done if you change supplier?
If the answer to any of them is vague, it is worth clearing it up before going ahead.
According to the OECD, AI adoption by SMEs depends on conditions such as skills, data, infrastructure and financing. This reinforces the importance of adjusting the project to each company's real maturity, instead of replicating solutions designed for very different organizations.
Frequently asked questions
What are the most useful artificial intelligence applications for an SME?
It depends on the company's processes and problems. Customer service, organizing information, administrative tasks and sales support are areas to assess, but the priority should come from the expected impact and the feasibility.
Is it necessary to develop custom software to use AI?
No. Many needs can be met with existing tools or features already included in the company's systems. Custom development makes more sense when there are rules, integrations or requirements that those options do not solve.
How to tell whether an AI investment is paying off?
Compare indicators before and after implementation, including time spent, errors, service quality and operating costs. Also consider training, maintenance and human supervision, so as not to confuse apparent speed with real return.
Should an SME start with an AI agent?
Not necessarily. An AI agent, able to carry out actions within defined limits, may suit certain processes, but a simple automation or a tool that supports the team may solve the initial problem better.
Can Norde help identify where to invest in artificial intelligence?
Yes. We analyse the company's processes, tools and priorities to identify opportunities with measurable value. For many SMEs, our consulting makes it possible to structure a suitable implementation; if an existing solution or a simpler improvement is enough, we will tell you frankly.
How can Norde help your company?
AI justifies investment when it solves a relevant problem. Start by identifying lost time or opportunities.
At Norde, we assess processes and tools before recommending a solution, which for many SMEs means a well-chosen AI implementation.
If you want to identify concrete opportunities in your business, talk to us: we reply within 24 hours and the conversation is without obligation. We work without lock-in contracts and everything we build stays on your side. The Norde team brings more than 11 years of experience in digital.
Want to find out where artificial intelligence can create value in your business?
We analyse your processes and identify the opportunities that justify investment.
