Co-founder and CEO at 10 Senses
Currently, artificial intelligence (AI) is revolutionizing industries and the way they operate. The technology is advancing at such a dynamic pace that without investing in innovative AI solutions, businesses put themselves into a losing position.
As a result, we can observe a significant rise in the usage of AI applications developed in-house or by using the services of AI experts.
Nevertheless, introducing AI applications into an organization is one thing, but companies must also pay close attention to how these apps are programmed. The way AI is programmed significantly impacts its performance, usability, and scalability.
Once you read this article, you will know:
- what is AI programming
- what are the benefits of good AI programming.
What is AI programming
AI programming refers to the process of creating systems that analyze data, learn from patterns, and make decisions. It combines traditional coding with machine learning (ML) and deep learning techniques to build efficient AI applications.
Apart from just writing code, AI developers need to focus here on making AI accessible, transparent, and user-friendly. It can be achieved by, for example, using low-code and no-code tools, which allow even non-technical users to contribute to AI app development.
What are the benefits of good AI programming
Well-structured and effectively implemented AI programming brings numerous advantages to businesses, including:
- stronger collaboration between AI developers and domain experts,
- greater development efficiency,
- enhanced transparency and accountability,
- improved user experience.
Stronger collaboration between AI developers and domain experts
In fact, bridging the gap between AI developers and domain experts is one of the biggest challenges in AI implementation. Numerous AI projects suffer from a lack of alignment between technical teams and industry specialists, which can result in low-quality outcomes.
Therefore, to mitigate this issue, AI programming should include:
- creating structured frameworks to enable domain experts to convey their needs,
- implementing user-friendly programming environments that enable interactions with AI models for non-technical users,
- ensuring smooth knowledge transfer between AI developers and domain experts.
With such an approach, AI applications can be more effective and better serve their intended purpose.
Greater development efficiency
Traditionally, developing AI models required specialized knowledge in ML and software engineering. However, modern AI programming is more about streamlining workflows by using low-code and no-code platforms and, as a result, making AI more accessible to domain experts.
These systems are becoming increasingly popular, empowering subject-matter experts to:
- train AI models without extensive programming knowledge,
- fine-tune AI behavior using real-world insights,
- develop AI-driven functionalities without relying on software developers.
This democratization of AI app development ensures that solutions are more aligned with industry needs while also easing the workload of AI developers.
These days AI engineers often face tight deadlines and high demands. By involving non-technical business users in the development process, developers can shift their focus from simply delivering AI projects to enhancing and refining AI algorithms for better performance.
Enhanced transparency and accountability
Truth be told, well-structured AI programming ensures that AI applications are transparent, explainable, and auditable. Such a feature is more important than ever in light of the AI Act and ongoing discussions about AI responsibility.
To achieve this, AI programming should include:
- clear logging and reporting mechanisms for compliance and security,
- interpretable AI outputs to build trust among users and regulators,
- built-in explainability features to make the AI decision-making process transparent.
Improved user experience
Finally, the way AI is programmed also impacts the user experience. Only a well-structured development approach allows teams to:
- design AI systems that respond intuitively to user inputs,
- ensure seamless interactions,
- continuously refine AI behaviors to align with real-world user expectations.
As a result, user-friendly AI programming allows businesses to create applications that are not only powerful but also enjoyable to use.
Summing up, the importance of AI application programming goes far beyond writing code. It shapes how AI is integrated, understood, and used across industries and businesses.
By bridging the communication gap between AI developers and domain experts, increasing AI development speed and efficiency, enhancing transparency, or improving user experience, proper AI programming is crucial for unlocking the full potential of AI applications.
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