Artificial Intelligence (AI) is one of the most significant advances in innovation. The extent of its impact is reaffirmed by hundreds of market professionals. The research ‘Before IT, Strategy,’ from 2024, presented by IT Forum Inteligência in June this year, shows that 49% of the 308 respondents consider Artificial Intelligence ‘very important’ for business – a relevance underscored also by the forecasted investment of $200 billion by next year in technology companies, according to the IDC Worldwide Artificial Intelligence Spending Guide.
Belonging to the technology segment, it is common to think that developers are responsible for creating new AI applications, right? Well, I say no. In order for solutions to be developed accurately, the direction should come from those who understand the business pains.
Let me explain. The team leading projects in a particular area has the necessary knowledge to identify where AI can make the greatest impact. They know what the market needs, the demands of customers, and the specific challenges of each segment. Without a clear understanding of how the solution should work, the process cannot flow 100%. Recently, NetApp sponsored the study ‘Scaling AI initiatives responsibly: the critical role of intelligent data infrastructure,’ which showed that 20% of AI projects fail without data infrastructure.
Research with this focus is essential to reinforce the need for the specific business team to dictate how AI solutions should be directed to solve real problems, increase efficiency, and generate tangible value. On the other hand, IT professionals, with their technical expertise, turn these ideas into reality, ensuring that the technology operates effectively.
After clarifying the question of who conceives the solution and who develops it, it is important to highlight the synergy between the two areas. Collaboration between strategy and technology is essential for success in applying the tool. It’s not just about creating the technology, but ensuring that it is implemented safely and efficiently.
Another point that reinforces the need for business leaders to be at the forefront of creating AI solutions is that they are not universal. What is effective in the financial industry may not work for retail or healthcare. Therefore, the business, with sector knowledge, guides the development of these solutions to meet the specific needs of each segment.
Lastly, frequent monitoring by developers and feedback from the business is essential for the continued effectiveness and evolution of the tool. Technological solutions are constantly evolving, and a single tool and version will not deliver effectiveness and expected evolution indefinitely.
When those leading the business understand how AI can be applied in their operations, communication with the development team flows. This way, misunderstandings or communication failures are minimized or even eliminated. Clarity about the needs and objectives of the solution allows the technical team to deliver tools more aligned with specific needs, resulting in more agile projects and higher return on investment.
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