At fairs, lectures, events, books, congresses, articles and, in fact, in any current business circle, the adoption of Artificial Intelligence (AI) has been widely discussed in the corporate world. Companies and leaders from different sectors are increasingly convinced that AI is essential to maintain their competitiveness and relevance in the market.
However, while many companies recognize the value of AI, few are effectively integrating the possibilities brought by this type of technology in a strategic and transformative way. What we see, in most cases, they are specific pilot projects with low impact, that do not capture the true value that AI can offer.
Companies usually have a practice, in the face of any technological novelty, adopt the "pilot-evaluate-scale-mature" model for project implementation. And with AI many organizations are, in fact, conducting tests and pilots in different departments and types of activity, using the same procedural logic. These experiments, in general, they seek gains in efficiency and productivity in specific areas, freeing up time for employees to focus on higher value activities. Although important, these initiatives are often limited, not significantly impacting the business strategy and, many times, failing to generate value at scale.
The question that arises is: why do these pilots not evolve into broader and more transformative initiatives? The answer lies in the lack of a strategic approach to AI within organizations, that needs to be guided by a clear vision and supported by leadership – often at the board level, inclusive.
How to advance to the strategic use of AI
For AI to be truly revolutionary within companies, it is necessary for executives and leaders to rethink the role of this technology in the context of their businesses. This goes far beyond implementing new software or automating specific tasks; it's a matter of reimagining processes, products and even entire business models from the perspective of AI.
Structuring leadership for AI
One of the main barriers toaa more strategic adoption of AI is the lack of skilled leadership to guide the transformation. Companies that truly advance with AI rely on executives and boards capable of making informed decisions about this technology. Vice presidencies dedicated to data and AI, specialized advisors and governance focused on innovation are some examples of structures that can accelerate the large-scale adoption of AI.
Cultural change and employee training
AI is not just about technology, but also of people. For it to be widely adopted and integrated, it is essential that employees understand how technology can impact their routines and their sector. Continuous training and the promotion of a culture of innovation are essential for employees to feel part of the change and to be able to contribute actively.
Adoption of a robust data strategy
AI relies on data to function effectively. Therefore, it is crucial that companies have a robust and well-structured data strategy. This includes the collection, storage, secure and ethical data processing and analysis. Companies need to be prepared to handle large volumes of data and to explore machine learning and deep learning tools, that allow extracting valuable insights.
Examples of Big Techs
The large technology companies are leading the transformation with AI and serve as a benchmark for the corporate sector. A Meta, for example, uses AI to automate advertising processes, maximizing the reach and effectiveness of campaigns. Another example is Amazon, that applies AI at all points of its operation, from product recommendations to logistics management. These cases illustrate how AI, when used strategically, can transform not only internal processes, but also the customer experience and leverage financial results.
Integration with strategic objectives
To advance beyond the one-off pilots, it is important that AI initiatives are aligned with the company's strategic objectives. AI should be seen as a tool that can help achieve these goals more efficiently and effectively. For example, if a company wants to increase customer satisfaction, you can explore AI to offer real-time personalization or to predict problems before they occur. AI should be integrated into all major constituent projects of organizational strategic planning – and resources must be allocated for their use and enhancement.
To capture the value of AI on a large scale, companies must overcome certain common challenges, such as resistance to change and technical complexity. This process requires the combination of visionary leadership, investments in data infrastructure and a strategic approach that prioritizes long-term results.
Therefore, advancing beyond point pilots with AI requires a shift in mindset and structure within companies, that is not trivial. So that AI is not just a fleeting "chicken flight", it is necessary for leaders to see it as a catalyst for real organizational transformation and to be willing to invest in and completely reimagine their operations.
