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How Telcos Can Optimize Voice Data Networks for AI - 46 CEO feature article in The Fast Mode

The telecommunications industry is undergoing a rapid evolution, with Artificial Intelligence (AI) leading the way in driving digital transformation. Network optimization, a crucial part of enhancing network performance and efficiency, has emerged as a significant area where AI is revolutionizing the landscape.

The use of AI in voice connectivity is greatly underrepresented in the IoT space, especially as voice clones and deepfakes continue to create security and identity issues in the industry. AI is unlocking new possibilities, but not without risk, which is why network administrators need to take careful precautions before introducing AI into their systems.

The power of AI

AI uses sophisticated algorithms to analyze data and uncover patterns, empowering telecoms to predict network anomalies before they occur. This integration of AI enables service providers to proactively address issues before they have a detrimental impact on customers.

They can even help networks self-optimize with real time updates and consistent machine learning. Telcos are leveraging AI to take historical data and use it to predict future data, allowing providers to effectively identify emerging business needs and scale faster than ever before.

While AI can be an essential tool for businesses looking to streamline their workflows and receive data on their offerings, it can also increase risk if not implemented correctly.

AI now has the power to mimic voice nuances and create “voice clones”, causing serious concerns for two-factor authentication and making spam calls even more difficult to detect. Telecom providers in particular have a responsibility to protect their customers from these threats, and learning how to optimize voice networks for the use of AI is essential.

Telecom providers in particular have a responsibility to protect their customers from these threats, and learning how to optimize voice networks for the use of AI is essential.

Optimizing voice data networks

Network optimization in voice data networks is an essential part of improving network performance by reducing downtime, enhancing network security and reliability and increasing network scalability.

The benefits of optimization are endless, and it is made even more important when AI is introduced to network systems.

AI can only report back what it is fed, meaning the information given to the AI must remain up to date and accurate to ensure the best results. Otherwise, it can run rampant and cause security issues, costly mistakes or system shutdowns.

To accommodate the workloads of AI, telcos need to ensure that they have a high-speed, lossless, scalable and low-latency network. This way, AI enhancements will lead to improved networks rather than causing more work to be done and more issues to solve, which is exactly what will happen if AI is implemented into unprepared legacy networks.

One of the greatest challenges for telcos is aging legacy networks that need to be updated at an alarming rate. Copper networks were the gold standard in the early 2000s, but not anymore. Since then, copper cables have been retired and the FCC deemed copper Plain Old Telephone Service (POTS) and TDM Voice obsolete.

However, copper is still deeply entrenched in the country with more than 40 million copper lines in the U.S. as of 2021.

For those who cannot afford an entire overhaul of their legacy systems, AI has the power to expand functionality and improve security, two consistent challenges providers deal with on legacy networks. However, this cannot happen without first optimizing the network for the use of AI.

Supplement, not replace

Customer service automation can augment traditional business roles and is being used by companies across the world to free up employee time and streamline internal processes.

For example, AI chatbots can be used to answer customer queries, provide personalized recommendations and direct them to the right information. This eliminates the need for a human counterpart unless a query is elevated and cannot be solved with the use of AI.

While a human may still be needed for quality control and complex issues, AI technology gives time back to the employee to focus on more important issues that would otherwise be spent sorting through hundreds of messages and customer calls.

AI should be used to supplement human work, not replace it.

But, just because AI can replace some human tasks, does not mean it should. As mass layoffs and 5G woes continue to plague the telecommunications industry, many employees fear losing their job to AI-driven strategies. However, AI should be used to supplement human work, not replace it.

When AI is used responsibly, it will get people on the phone with the right human faster and easier, not replace the talent needed to ensure no threats are created.

Human intervention in AI is a necessary aspect of optimization that will ensure the ethical and correct use of the technology, creating faster and less expensive networks, and bringing more jobs into the market.

AI can be a job creator, not destroyer, but humans need to remain in control and be responsible for the tools that we create.

Trevor Francis
CEO, 46 Labs
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