Every week, a new tool comes along that promises to change the way we work.
Try it—it works—and after a month, an icon remains on your desktop. That’s what happens when you start with technology.
The question that makes all the difference is a different one: What tasks, today, take up your employees’ time without adding value?
From there, artificial intelligence becomes a project with a start date, a scope, and a person in charge.
And it also answers the question that many entrepreneurs silently ask themselves: What will happen to my employees?
In the projects we manage, our goal is to assign each person tasks that add the most value.
Here’s how we do it.
Every day, the market offers new artificial intelligence tools, and each one performs a specific task well.
The challenge for an SME lies elsewhere: figuring out which processes to tackle first, what data to use, and who is responsible for them.
When this choice is missing, isolated experiments emerge that remain on the computers of those who tried them, with information scattered across too many platforms and team members unsure of their roles.
When there is a choice, AI becomes a corporate initiative: a measurable goal, clear data policies, trained staff, and a result that can be extended to other departments.
We work with entrepreneurs who want to implement artificial intelligence with a medium-term vision, while respecting their employees, customers, and the local community.
Every project follows the four phases of the FARO method: first, we determine where AI adds value; then, we build it; and finally, we measure its impact.
We start with a map of repetitive processes and available data.
First, select a pilot project with a measurable goal; establish rules regarding data and accountability; then build the solution, train the staff, and measure the time saved.
Following the initial results, AI is being expanded to other departments.
Six services that cover the entire process, from the initial assessment to trained personnel. If you haven’t yet decided whether and where to implement AI, the starting point is AI consulting for businesses.
When AI handles repetitive tasks, people can return to work that requires experience, interpersonal skills, and judgment.
Where the organization allows it, that time can also translate into more reasonable hours and more time for family.
That’s how we measure the success of a project.
It’s best to choose a partner that focuses on processes before tools, clearly states how it handles data, measures results using agreed-upon metrics, trains staff, and leaves control of data and content in the company’s hands.
Before signing, ask for specific examples, a timeline for the first results, and who will oversee the project after launch.
The price is determined based on the project, following the assessment. The factors that determine it are as follows:
Public incentives for business digitization are made available periodically: it’s worth checking which ones are currently available before launching your project.
The method remains the same; what changes are the questions we ask the entrepreneur, the tools we decide to use, and the timing of the decision. These are the four areas where we have the greatest depth of expertise.
Based on an assessment: a map of repetitive processes, available data, and internal expertise.
The result is an initial use case with a measurable goal, chosen because it delivers visible results quickly and involves people who are willing to experiment.
Tasks that are repetitive, frequent, and based on information that is already available: standard responses to customers, preparing documents and quotes, searching internal documents, and summarizing meetings and reports.
These are processes where the results are easy to measure and the risk remains low.
The goal of the projects we manage is to shift people toward higher-value tasks: customer relations, quality control, and decision-making.
AI handles the repetitive tasks, and people guide its work. That’s why training is part of the project from the very beginning.
Based on the number of processes involved, the quality of the data, integrations with existing systems, the level of customization, and the people who need to be trained.
The price is determined after the assessment, once these factors are clear.
With metrics agreed upon before starting: hours saved, response times, errors avoided, and quality as perceived by customers.
The starting point is identified, and then comparisons are made at regular intervals. The time given back to people is one of the most telling indicators.
These decisions are made at the outset, during the governance phase: which data can be shared with the models, which data remains within the company, which plans and vendors to work with, and who has access to what. The rules are put in writing and shared with the team.
It depends on the use case you choose. A well-defined initial project—involving a repetitive process with organized data—shows measurable results as early as the first few weeks of use.
Projects that involve multiple departments require a phased roadmap.
AI consulting helps determine whether, where, and with what priorities to implement artificial intelligence. AI services carry out the decisions made: governance, automation, agents, software, and training.
Many companies start with consulting and move on to services.
During our first meeting, we’ll review your processes together and identify where artificial intelligence can free up more time for people.
Factory Communication supports companies and small and medium-sized businesses throughout Italy with an ethical and measurable approach.
