AI has immense potential to transform customer experiences and optimize commercial operations. We are all looking for an easy solution to quickly accomplish tasks with a minimum of effort, and AI seems to go in this direction – at least by helping to lighten the load.
A study conducted by Freshworks revealed that IT departments are leading to AI adoption, with 85 % using AI tools each week. However, in the midst of the craze, it is crucial for CIOs to temper expectations and understand that AI is a powerful tool, but not a miracle solution. Although AI can make significant improvements, it requires careful planning and thoughtful integration to achieve full value.
Fully exploit AI thanks to a solid infrastructure
Going from a fixed state of mind to a state of growth allows leaders to see AI not as a universal solution, but as a dynamic tool requiring continuous learning and adaptation. This change helps to avoid crisis management traps and promotes proactive planning and thoughtful execution.
For example, when an AI chatbot deployed, the company’s non -computer scientists probably expect immediate and flawless results. A state of growth changes this approach by starting with a progressive deployment and by collecting feedback to continually refine the chatbot. This state of mind implies set realistic objectives, plan regular updates and anticipate challenges. Considering AI as an iterative tool rather than a rapid remedy, the company guarantees a more strategic and effective deployment, thus supporting continuous improvement.
Ethics and regulations: guarantee a responsible AI.
Each CIO seeks to optimize its budgets – more than ever. The implementation of AI implies a substantial financial commitment, including specialized equipment such as GPUs and skilled talents. A July 2024 survey by Ernst & Young LLP reveals that leaders investing 5 % or more from their budget in AI find an increase in 14 percentage points of employee productivity compared to those who invest less.
Despite its transformer potential, the success of AI depends on a robust infrastructure, rigorous governance and the development of talents. Currently, only 36 % of managers fully invest in data infrastructure, 54 % focus on AI ethics, and 37 % offer full AI training. Inadequate fundamental support can lead to unsuccessful investments.
Costs can reach millions, which can represent a challenge for small businesses. However, with efficient planning and management, AI can be accessible to businesses of all sizes. A Forbes Advisor survey revealed that 90 % of respondents expect the generative AI to have a positive impact on their business within 12 months, and 70 % think that it will rationalize the generation of content. Understanding costs and requirements is essential to effectively exploit AI.
Human and AI: A winning duo to succeed in transformation.
Despite the enthusiasm aroused by large -scale AI initiatives, not all of them reach the expected results. The effective deployment of AI requires reflected integration and realistic expectations. CIOs must set practical objectives and raise awareness of stakeholders on the advantages and limits of AI.
The Gartner’s Data and the analysis summit, Inc. in July 2024 in Sydney revealed that at least 30 % of generative AI projects “will be abandoned after proof of concept by the end of 2025 due to poor data quality, inadequate risk controls, increasing cost or blurred commercial value. This divergence underlines the need for prudent planning and execution to guarantee the success of AI initiatives.
Maintain the balance between innovation and risk management
As technology evolves, several factors must be taken into account. As guards of the organization, it is crucial for CIOs to identify potential risks and put in place appropriate protective measures. It is necessary to collaborate closely with legal experts to fully understand these risks. We are currently in the early stages, and the standards established for AI are still under development. Although we have AI tools, specific applications and standards of use are not yet clearly defined.
AI projects require continuous assessment and adjustment. The implementation of feedback loops and performance measures helps CIOs to follow progress and adapt strategies to align with commercial objectives. According to the State of the CIO 2024 study in Foundry, CIOs are increasingly involved in AI initiatives and provide for increased involvement in cybersecurity (70 %), data confidentiality and compliance (61 %), as well as data analysis (54 %). This underlines the need for a balanced approach combining innovation with rigorous risk management and strategic supervision to ensure that IA investments produce significant and lasting results.
