As companies worldwide embrace digital transformation, Generative AI (GenAI) emerges as a key technology, addressing tasks and challenges that humans cannot perform as efficiently. It has been nearly a year since OpenAI released GPT-4 in an effort to keep pace with digital developments. Meanwhile, GenAI has emerged as the most sophisticated modern technology, transforming business operations and taking productivity to the next level.
At the end of 2023, enterprises and tech companies worldwide spent around USD 19 million on GenAI. According to latest studies, this expenditure will reach USD 151 billion by the end of 2027. This includes artificial intelligence programs and software and business services. According to tech leaders, 2024 is the year in which AI will prove its worth in all types of investments.
As smart solutions become more prevalent, it is crucial not to underestimate AI's potential. Integrating Generative AI (GenAI) into products and services can drive significant advancements and achieve greater outcomes for companies. Understanding and leveraging GenAI's capabilities will be key to staying competitive and innovative in the rapidly evolving technological landscape.
Thus, the burgeoning question, “What does GenAI integration mean for business, and what are the key steps to its implementation?” is yet to be answered.
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Re-Building Operations
The only way that GenAI can truly transform businesses is by building an effective system. Based on global data, 96% of businesses are now using GenAI—a number that has tripled over the past 12 months. Over the past three years, due to the increased use of the internet, enterprises now use an average of nearly 10 generative AI applications for various categories and use cases.
Building New Skills: It's necessary to know how to use GenAI responsibly and to identify AI models for each use case. This necessitates upskilling in AI knowledge so workers can achieve far more using new tools.
The UAE is actively implementing skills development initiatives to foster digital competency and inclusivity. Ericsson and Vodafone Oman have partnered to drive digital skills for social impact. Zain KSA, through its WE initiative, focuses on gender diversity and inclusion, empowering women in leadership roles and promoting an equitable work environment. This aligns with Saudi Vision 2030 and the Human Capability Development Program, which aims to invest in human capital. Additionally, Qatar’s National Skilling Program aims to train 50,000 people across various demographics by 2025, equipping them with advanced digital skills to drive innovation.
Data-Driven Decision Making: Generative AI leverages data to improve business decision-making. Therefore, data management should be a priority for every company, including modernizing existing systems and developing new collaborative frameworks.
For example, MYCOM OSI recently announced the beta release of EAA GenAie, a generative AI application enabling data-driven decision making for business executives and operations engineers.
New Services Models: Generative AI offers new potential to create innovative business models and transform various operations in the near future. It can be utilized in education, technical assistance, content creation, analysis, decision-making, research, and editing.
Nokia is leading the way by integrating Generative AI into its security solutions and unveiling MX Workmate to enhance industrial operations. The TDRA has incorporated Generative AI into its 'U Ask' platform, streamlining user interactions. e& UAE is leveraging AWS's Generative AI technology to elevate customer experiences. Meanwhile, stc Group has set a world-first by implementing Nokia’s AI-powered MantaRay SON onto its live network.
Although often associated with business, the applications of Generative AI extend far beyond, enhancing productivity and problem-solving in novel ways. Analysts predict that Generative AI will continue to advance, fostering a new model of interaction between humans and AI machines. Capable of writing, reading, designing, and completing tasks, Generative AI is becoming increasingly interactive with the real world, holding immense promise for the future.
As we approach 2025, Generative AI is revolutionizing innovative solutions across all industries. This evolution will create a new era of solutions, helping companies to address challenges effectively. By allowing users and employees to focus on simpler tasks while AI handles more complex ones, businesses can establish strategies that maximize efficiency and innovation.
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Generative AI Market and Challenges
While industries stand to benefit significantly from Generative AI services, the market is expected to grow substantially between 2024 and 2030, potentially boosting the global economy by trillions of dollars. However, several challenges must be addressed for successful implementation. These challenges include legal concerns, a lack of professional and AI skills, insufficient processing capacity, poor data quality, and issues related to security and privacy.
In the Middle East, several frameworks and initiatives have been developed to ensure the secure and ethical development of Generative AI (GenAI). For instance, the UAE's National AI Strategy emphasizes ethical AI development, ensuring robust data privacy and security measures. The strategy includes a framework for responsible AI usage, highlighting transparency and accountability as key principles.
Saudi Arabia has also been proactive, with the Saudi Data and Artificial Intelligence Authority (SDAIA) implementing policies that focus on data governance, privacy, and security. These policies are part of the Kingdom's Vision 2030, which aims to foster innovation while ensuring the ethical use of AI technologies.
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To successfully implement Generative AI (GenAI), businesses need advanced infrastructure and innovative chip designs. One of the significant challenges is managing poor-quality data, prompting companies to invest in improving their data quality.
Security is another critical aspect, as GenAI applications are vulnerable to cyberattacks. Delving into the influence of GenAI on telco security in an exclusive interview with Telecom Review, Rodrigo Brito, Head of Cybersecurity Portfolio at Nokia, mentioned that Nokia is “using large language models (LLMs), specifically trained on telecommunications and security. We [Nokia] made an augmentation of the training, combining both static knowledge—including additional security knowledge, telecommunications knowledge, security regulations knowledge—and dynamic knowledge, that makes the large language model aware of the context it’s operating on.” Using these LLMs, security engineers can chat with the large language model about a specific security incident, enhancing resolution actions.
Also addressing cybersecurity solutions for GenAI is Vodafone Oman. Stelios Savvides, CTO, Vodafone Oman exclusively mentioned to Telecom Review that, “We [Vodafone Oman] have implemented generative AI (GenAI) in a number of areas within our cyber defense. One of which aims to cleanse data when it sees a threat approaching. We immediately scrub it to prevent it from impacting our services. At the same time, we are also looking at other threats within our office IT, particularly phishing, which is another threat that we all need to be vigilant about.”
Despite these challenges, adopting GenAI promises a smarter, technology-driven future. GenAI can significantly enhance human capabilities by generating new content and driving societal development without replacing human roles. This balance between leveraging AI advancements and maintaining human contributions is essential for societal progress.
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