How to Incorporate AI to Your Bespoke Software

Artificial intelligence (AI) is now part of daily business life and no longer viewed as a passing fascination. Companies of all sizes are exploring how to implement AI to improve efficiency within the business, while also making sure they are not late to the AI party.

As a business owner, whether you already use bespoke software or are planning to build one, it is completely natural to ask how AI might fit into the picture. If you are a startup founder, you may feel pressure to include AI somewhere in your product, especially as investors often favour businesses that adopt new technologies confidently. Even so, the real question is not how to add AI but whether it genuinely serves the purpose of the project.

Can AI Get Implemented to All Projects

The simple answer is no. AI is not the right choice for every task. A good example is a basic mathematical calculation. You do not need an AI model for that when traditional code, spreadsheets or calculators are faster, cheaper and dramatically more reliable. This difference becomes clearer when you look at deterministic and probabilistic models.

Deterministic models follow fixed rules. The same input always produces the same output. Most traditional software is built this way because it provides stability, accuracy and clear explanations. It is ideal for billing systems, compliance checks, workflow automation or anything that needs predictable behaviour.

Probabilistic models work differently. They rely on statistics and pattern recognition, which allows a degree of variability in their outputs. Most modern AI models fall into this category. They excel in complex or uncertain environments such as natural language processing, recommendations, forecasting or image generation.

As a result, probabilistic models are not the best fit for tasks that require strict precision. They can still be used in those cases, but a deterministic approach will usually be more reliable and more cost effective.

Should I Use AI in My Software

Technology exists for people. It is an enabler that supports us in solving real-life problems and meeting real needs. We should position AI as an enabler rather than the ultimate goal for our business (unless we are an AI company), and use it only where the use case is genuinely suitable.

Yes, it is a classic reminder, but we never get tired of saying it. The first step is always to define the business problem clearly. Whether you are building a new digital product or enhancing an existing one, you need to understand what issue you are solving and why the solution matters.

Once you know the problem, you can evaluate the technology that fits best. This usually involves discussions with software developers or technology consultants who can help compare different approaches. It is helpful to consider the following points:

• Which model type is correct for the use case and whether the task is better suited to deterministic logic or a probabilistic AI model.

• What the implementation cost will look like. In general, adopting new technologies can be more expensive because of the specialist expertise required. However, depending on the business problem, implementing AI can actually be more cost effective, especially when you choose to integrate an existing API rather than develop a custom model. This is particularly true for SMBs.

• How the solution will be maintained over time, both from a cost perspective and in terms of whether it creates any risk of vendor lock-in. A system that depends heavily on a specific provider can become difficult to evolve later.

Careful evaluation ensures that AI adds value rather than complexity when it is implemented. AI can improve the user experience, automate complex tasks and surface valuable insights. When used without a proper purpose, it can introduce unnecessary complexity, raise costs and complicate maintenance.

Key Take Aways

• AI is powerful but not required for every project or feature.

• Deterministic logic still outperforms AI in many structured, rule based tasks.

• AI should be added when it solves a real business problem efficiently.

• Use case, costs and long term maintenance need to be assessed before implementation.

How DoganTech Helps

At DoganTech we help entrepreneurs and companies make confident technology decisions.

Our Technology Consulting Service is designed to guide you in choosing the right approach for your software and the first thirty minute call is free.

We also build bespoke software solutions and support you through the entire process so you can integrate AI where it makes sense and build your product the right way from the start.