Your first AI project: choosing where to create measurable value
Let’s discuss your first AI projectArtificial intelligence creates opportunities to improve operations, develop services, and extend what a team can accomplish. Yet that breadth can make a seemingly simple decision difficult: where to begin. A business may see opportunities in sales, administration, and customer service, while each department suggests a different tool. Without shared criteria, effort can become scattered across initiatives that never become part of everyday work.
The value of a first project extends beyond its immediate outcome. It provides a chance to learn how to integrate the technology, what information it needs, and what organizational changes it requires. Choosing well helps build confidence and provides evidence to guide future decisions. That starts with a recognizable need and a scope the business can implement, evaluate, and maintain.
Start with a business decision
Before choosing a tool, the business needs to understand the situation it wants to improve. “Bringing AI into sales” is a broad ambition; reducing the time spent preparing a quotation is a specific goal that can be measured. It allows the team to identify who performs the task, what information they consult, where delays occur, and how those delays affect both colleagues and customers.
That assessment may also reveal incomplete data, conflicting commercial rules, or steps that serve no useful purpose. Automating the workflow without examining it can carry the same confusion into a new tool. The initial discussion should establish the intended outcome and identify which parts of the process should be simplified before introducing technology.
Compare opportunities by impact and feasibility
A promising opportunity combines a meaningful improvement with conditions that make delivery possible. Consider how often the task occurs, the effort it consumes, and the consequences of mistakes. At the same time, assess the availability of information, connections to other systems, and the team's ability to participate in implementation. An important problem may require preparation that has not yet been completed.
Consider a business weighing two options: classifying incoming inquiries or generating complete sales proposals. The second may promise a greater impact, but it may also depend on current prices, discount rules, and information spread across several systems. The first could offer a more manageable starting point if historical inquiries and clear routing criteria are available. The right choice depends on the context: compare the expected benefit with the work and dependencies involved in achieving it.
Design a pilot that supports a decision
A useful pilot should resemble everyday work closely enough to expose its difficulties. For incoming inquiries, that means including ambiguous messages, incomplete requests, and matters requiring special attention. It also requires clear boundaries for what the tool can handle and when a person must step in. Testing only straightforward examples offers little insight into what will happen when the team begins using the solution.
Before starting, document how the process currently works and agree on what to observe: total resolution time, correct routing, necessary corrections, and supervision effort. The speed of an individual response is not enough to establish improvement. The assessment must account for the complete workflow, operating costs, and the experience of the people receiving and using the output.
The pilot’s success criteria should support a clear decision: expand the scope, adjust the solution, or stop the initiative. Setting them upfront helps prevent a pilot from continuing simply because people are enthusiastic or have already invested time. It also makes it easier to recognize when the learning points toward better data preparation or an integration that needs to be resolved before proceeding.
Build a capability the business can maintain
For an initial implementation to last, someone needs to take responsibility for the process and its development. That includes keeping information current, reviewing exceptions, and supporting the team as tasks change. People who understand the operation need to participate in the project: their observations reveal the differences between a successful demonstration and something useful during an ordinary working day.
How we approach a first AI project at 301
At 301, we combine consulting and development to turn these opportunities into a defined scope. We examine the process, available tools, and implementation conditions, then determine what can be reused and what needs adaptation or custom development. The starting point may be an agent we have already developed, a capability added to an existing system, or a dedicated solution.
A well-chosen first project can free up time, improve an experience, or support a decision. Its strategic contribution also lies in establishing a way of working: shared priorities, evaluation criteria, and a foundation for extending capabilities with purpose. AI adoption can then become a path toward greater competitiveness, with each step informed by what the business has learned.
Business executive with an MBA from IAE Business School and a background that spans over 12 years in the corporate world, entrepreneurship, and business consulting. Founded his own startup and has helped companies across industries align their real needs with effective digital solutions. Specialized in bridging business strategy with technology execution, supporting organizations throughout the entire product development process. Brings a business-first mindset, with a strong focus on impact, alignment, and long-term value.
