Generative AI is rapidly transforming industries, and its potential applications in the media and telecom sectors are vast. 

We spoke with Dr. Mahsa T. Pourazad, Vice President Technical & Educational Activities at IEEE CTSoc, and Data & AI Strategy Manager at Accenture (UK) about the intricacies of this technology, its foundational principles and the transformative impact it can have on businesses.

What is generative AI?

Dr. Mahsa T. Pourazad tells us that in simple terms, “generative AI is a revolutionary class of models capable of creating new content.” 

These models, especially large-language ones, have surpassed previous AI phases in understanding language complexity. Whether it is audio, video, text, or numeric data, generative AI can produce it. Its in-memory operation allows for real-time conversations, a testament to its advanced capabilities. 

Dr. Pourazad also emphasises that “it is crucial to remember that its content generation is based on learned patterns, and it does not possess innate creativity.”

Despite this, AI has played a significant role in numerous industries.

AI in media and telecom

Reflecting on the past, Dr. Pourazad notes that AI has been a part of the media and telecom sectors for a long time. She cites the example that “recommendations on your TV screen are powered by machine learning models that analyse your viewing habits.” 

Initial interactions with service providers often involve natural language processing models. “Some companies even utilised machine learning to convert 2D content into 3D,” she recalls with a hint of nostalgia, emphasising that historically AI-driven tools have been “instrumental” for using data to help drive insightful decisions.  

The revolution of Generative AI

This history of AI applications paves the way for the transformative impact of generative AI, which possesses the groundbreaking ability to comprehend language, context, and intent.

After pre-training on vast data sets, these models can be fine-tuned for various tasks. "Many organisations are now experimenting with off-the-shelf foundation models, leveraging their accessibility and adaptability," Dr. Pourazad notes. 

As generative AI becomes more integrated into business applications, its value will be in customisation. In the telecom and media sectors, its applications span from network optimisation, risk management, and code generation to chatbots, personalised marketing, and content creation.

Before adopting GenAI in a business, however, there are a few important considerations to be made.

Testing, scaling, and responsible practices

Dr. Pourazad advises companies to begin by using specific use cases then to “test them through proofs of concept." 

Scaling technology requires assessing its readiness, the available skillset, and the necessary processes and policies. "Companies must also prioritise responsible AI," she emphasises, which means ensuring transparency, fairness, and compliance.

Another thing to consider is the impact GenAI has on the workforce. 

Augmented roles and human-AI collaboration

Generative AI is changing the face of the workforce, especially when it comes to specific roles. 

Dr. Pourazad predicts that this will continue, "Specific tasks within jobs will be augmented by AI, leading to the creation of new, high-value human tasks." Roles like prompt engineers, AI tech architects, and LLM architects are emerging, which is leading companies to invest in training to help employees adapt "ensuring they harness the potential productivity gains."

Reflections on the AI journey

What AI promises is not just technological prowess but “its potential to uplift and innovate our daily lives.” AI has a responsibility that extends beyond technology, it is about finding ethical solutions that improve society as a whole. Dr. Pourazad underlines that this responsibility, to ensure that generative AI remains a force for positive transformation, prioritises humanity above all else.