Artificial intelligence is already part of the daily life of many companies. It has gone from being an emerging technology to an operational tool that directly impacts productivity, decision making and the way we work.
However, in a context where new solutions are appearing every week, the main challenge is not accessing the technology, but understanding where it brings real value and how to apply it judiciously. Many companies have already tried AI tools, but have not always achieved clear results.
The difference is usually not in the tool, but in the use that is made of it.
More tools does not mean more value
One of the most common mistakes is to associate the adoption of artificial intelligence with the incorporation of multiple platforms. In practice, the companies that are achieving results are doing so in a much more focused way.
They start with a concrete use case, apply the technology to a real process – not an experimental one – and measure its impact in terms of time, efficiency or quality. This approach explains why, despite the wide variety of solutions available, value is often concentrated in a few well-used tools.
What type of AI does a company really need
Before choosing a tool, it is important to understand that not all of them respond to the same need. Broadly speaking, artificial intelligence is being applied at three levels within the company.
Firstly, as support for individual productivity, automating day-to-day tasks such as writing e-mails, analyzing documents or preparing proposals. In this area, solutions such as ChatGPT or Gemini stand out.
Secondly, as an integrated part of the processes, being incorporated directly into work tools such as office suites or internal systems. A clear example is Microsoft Copilot.
Finally, as support for analysis and decision making, especially when working with large volumes of information or complex documentation. In this case, tools such as Claude or Perplexity AI are gaining prominence.
The key is to identify where the company is at and move forward progressively, rather than trying to tackle everything at once.
What each tool provides in practice
Beyond their technical capabilities, each solution excels in different contexts.
ChatGPT has established itself as a versatile tool, especially useful for cross-cutting tasks such as writing, information structuring or content generation. Its ease of use makes it a common gateway to artificial intelligence.
Claude excels in environments where depth and consistency are required, such as the analysis of large documents or the development of complex content.
Gemini provides value mainly through its integration into the work environment, allowing tasks to be automated directly in tools such as mail or shared documents.
Microsoft Copilot has a direct impact on productivity when structured processes are in place, especially in tasks such as Excel analysis or report generation.
Perplexity AI is particularly useful in research and analysis contexts, providing answers based on verifiable sources.
In practice, it is not so much a matter of choosing a single tool, but of understanding which one best fits each process.
Cost vs. impact
One of the factors that has driven the adoption of artificial intelligence is its accessibility. Most of these tools have plans around €20 or €30 per month per user, which lowers the barrier to entry.
However, the real cost is not in the subscription, but in its actual use. Many companies incorporate tools that they hardly use, while others achieve clear returns with very specific applications.
The differentiating factor is not price, but the ability to integrate technology into daily work.
Where it is really working
The most common success stories do not respond to large projects, but to very specific applications within the company’s operations.
Artificial intelligence is being used to prepare commercial offers in less time, analyze markets and competitors, generate technical or commercial content, support customer service or automate internal reporting tasks.
In all these cases there is a common pattern: artificial intelligence does not replace the process, but rather accelerates and improves it.
Limitations and risks
Despite their potential, these tools also have limitations that should be taken into account.
They can generate errors or inaccurate information and therefore require monitoring. In addition, data usage and privacy need to be properly managed, especially in enterprise environments. On the other hand, their adoption implies a change in the way of working that is not always immediate.
It is also common to find unrealistic expectations, such as thinking that artificial intelligence can completely automate complex processes without human intervention.
How to start with criteria
For an SME, the most effective approach is often to start simple. Identify a specific time-consuming task, apply a generalist tool and assess its real impact.
From there, more specific solutions can be incorporated according to the needs of each area. The objective is not to adopt artificial intelligence on a massive scale, but to do so progressively and in line with the company’s activity.
A question of approach, not technology
Artificial intelligence is not a solution in itself, but a layer that improves existing processes. The companies that are gaining an advantage are not necessarily those that use the most tools, but those that have been able to integrate them meaningfully into their operations.
In this context, the adoption of AI should not be seen as an isolated technological project, but as a natural evolution within the digitalization process.
At amec’s Acelera Pyme Office, the focus is precisely on accompanying companies in this process: to identify real opportunities and land the technology in their day-to-day work so that it has an impact.
