Why AI Struggles to Turn Major IT Projects into Concrete Gains
Despite enthusiasm for artificial intelligence, major IT projects, especially in infrastructure and operations, struggle to show tangible benefits. This gap highlights technical and organizational challenges to overcome.
For several years, artificial intelligence (AI) has established itself as a major driver of transformation in the IT sector. Initiatives are multiplying, whether to optimize business processes, improve customer experience, or automate certain tasks. However, while AI applications in functional areas are often highlighted, major IT projects—particularly those related to infrastructure and operations (I&O)—still face difficulties demonstrating significant gains.
Major IT Projects: A Challenging Field for AI
Major IT projects cover essential areas such as infrastructure management, monitoring, security, configuration management, and operations automation. These initiatives are often complex and critical to the smooth running of businesses. Yet, the integration of AI into these projects has not yet generated widespread expected benefits, whether in terms of cost reduction, performance optimization, or better incident management.
Several factors explain this delay:
Complexity of IT environments: Current infrastructures are often heterogeneous and aging, complicating the collection of reliable data and the implementation of effective algorithms.
Lack of maturity of AI tools: Existing solutions are not always suited to the specificities of IT operations and still require significant adjustments and customization.
Organizational barriers: Adopting AI within I&O teams demands skill evolution and strengthened collaboration between IT professionals and data scientists.
Data governance issues: The quality, availability, and security of IT data are essential prerequisites for leveraging AI but are often insufficiently controlled.
Promising but Still Limited Use Cases
Despite these obstacles, several use cases demonstrate AI’s potential in major IT projects:
Predictive maintenance: AI can anticipate hardware or software failures by analyzing logs and metrics, thus limiting service interruptions.
Intelligent automation: Automation platforms integrating AI can detect and automatically correct certain incidents, reducing resolution times.
Resource optimization: By analyzing loads and usage, AI helps better size infrastructures and optimize energy costs.
Strengthening cybersecurity: AI algorithms can identify abnormal behaviors and potential threats in real time, improving team responsiveness.
However, these benefits often remain limited to pilot projects or specific cases, without yet generalizing across all IT infrastructures.
Towards Better Integration of AI in Major IT Projects
To enable AI to deliver tangible gains in major IT projects, several avenues should be explored:
Enhance data quality: Implement rigorous governance around IT data, with adapted processes for collection, cleaning, and securing.
Adapt AI tools: Develop solutions specific to infrastructure and operations challenges, integrating the business knowledge of IT teams.
Train teams: Support the upskilling of IT professionals on AI technologies, fostering effective collaboration with data scientists.
Encourage change management: Raise organizational awareness of AI’s benefits and limits to facilitate its gradual and controlled adoption.
Promote experimentation: Launch pilot projects aimed at quickly demonstrating concrete gains, then extend solutions on a larger scale.
Conclusion
Artificial intelligence offers undeniable potential to transform major IT projects, particularly in infrastructure and operations. Yet, gains remain to be realized on a large scale due to technical, organizational, and cultural challenges. A pragmatic approach focused on data quality, tool adaptation, and team support will be essential for AI to become a true driver of IT optimization.
