GenAI technology, though innovative, is likely to shift back to predictive AI in over half of the situations, with a reduced impact on return on investment. It’s essential to move from the concept phase to production and to focus more on priority use cases to ensure scalability. What role could predictive AI play in this transition?
TL;DR
- Predictive AI proves valuable in the telecom industry.
- Industrial adoption of AI enhances performance and customer experience.
- Reevaluating the ROI of GenAI projects will help guide investments more effectively.
Artificial Intelligence: an asset in the Telecom Industry
Artificial Intelligence (AI) and, more specifically, GenAI are playing an increasingly significant role in the telecom industry. While the application of these new technologies generates enthusiasm, they should be refocused on pragmatic and measurable outcomes.
Predictive AI: less “glamorous” but central to operational challenges
In a sector where operations and processes are already well-optimized, predictive AI often proves more relevant than generative models, even if it’s less attractive. Although it may not carry the same revolutionary appeal, predictive AI delivers solid results in addressing specific challenges like bandwidth optimization, network performance improvement, and fault detection.
From POC to production: a decisive step for AI deployment
To capitalize on the investments already made, many AI projects unfortunately remain stuck in the Proof of Concept (POC) stage. These stalled initiatives require a decisive push to align with companies’ strategic priorities. Moving from POC to production yields tangible results that promote widespread AI adoption within the organization.
Reevaluating the ROI of generative models: a must for efficient GenAI use
Assessing the ROI of GenAI projects is often a double-edged sword. These solutions can be beneficial, but their advantages are often less obvious compared to predictive models. Redirecting use cases toward clearly measurable outcomes can lead to quick financial gains while laying the groundwork for a more strategic use of GenAI.
Towards an industrializable and scalable AI
Telecom companies operate at a complex scale, with millions of subscribers and constantly evolving networks. To harness AI at this level, a robust infrastructure and a focus on industrializable AI solutions are essential. By adopting a pragmatic approach and leveraging predictive AI, telecom companies can quickly see performance and customer satisfaction improvements while preparing for more advanced and strategic use of GenAI.
A return to enlightened pragmatism and embracing the immediate benefits of AI will allow the telecom industry to build stakeholder trust while renewing its infrastructure for bolder and more promising innovation.
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