Abdelilah Nejjari, the Managing Director for the Gulf Region at Cisco, says AI helps humans make better decisions and work faster
The acceleration of AI will fundamentally change our world and create new growth drivers for all of us. Generative AI provides access to endless applications; and exceptional use cases are being discovered every day for every sector, from healthcare, and education, to financial services, and many others.
We believe that generative AI is unlocking new opportunities to create value. We are seeing a quick surge in the trend of using this emerging technology for enterprises, for example, marketing and sales-driven companies have quickly added generative AI use cases into their workflows because of the speed and scale AI tools can bring to content production and customer relationship management efforts.
At the same time, AI workloads are surging: IDC expects data from AI-Lifecycle workloads to reach 117 million Terabytes in 2025. With more complexity and distribution comes the need for more powerful and secure networks, and Cisco is at the very centre of it.
Cisco has been using AI and machine learning for a decade now to solve real problems through a pragmatic approach. We are enhancing our products and offers with AI capabilities and driving product differentiation in the areas of collaboration, security, networking, and observability. We also analyze huge amounts of data, identify, and contain threats, or ensure smoother workflows. We bring together new predictive technologies through our broad portfolio of observability, visibility, and intelligence technologies to improve the reliability and performance of networks, the backbones of the digital economy. And we bring everything together by providing a seamless experience throughout the customer journey across our offerings.
Why according to you should companies leverage generative AI?
According to Cisco’s 2023 State of Global Innovation Study, IT professionals rank generative AI as the technology most likely to have a significant impact on their business, with 85% of those saying they’re prepared for its impact.
Generative AI models have been available since 2018, but only now have they become prevalent. Today, with the availability of more computing power, the abundance of data, and with Large Language Models LLMs reaching sufficient parameter counts to handle complex problem sets, generative AI has crossed the threshold of technological and economic viability.
We see numerous key benefits of using generative AI:
- Accelerated automation is one of the top use cases our customers seek: Generative AI can tackle complex problems and automate multiple features that previously required human intervention.
- Generative AI enhances team efficiency: With co-creation capabilities, Generative AI sparks new creative possibilities and inspiration for teams across various functions.
- Deliver Seamless Customer Experiences: Unified prompt interfaces powered by Generative AI offer a more cohesive and seamless experience.
- Unlock New Use Cases: Generative AI models are continuously evolving, achieving greater accuracy, and being curated for multiple use cases. These advancements unlock new growth drivers for both Cisco and our customers. For example, our customers want to optimize their data and create services that support a diverse set of natural language processing tasks, like Bloomberg GPT. This trend is creating a surge in demand for security and observability services specifically for the usage of Generative AI models. Cisco is ready to support and help our customers with these evolving needs.
- Democratize Access to Technology: Generative AI will lower barriers to accessing technology (via interfaces and AI assistants). This is not only making interaction with technology and software much easier and intuitive but is also empowering people with different technology backgrounds to interact with it and perform tasks they otherwise could not.
What are the challenges companies face in terms of adopting and using generative AI and what policies are put in place to overcome them?
In the near future, we predict even more truly transformative AI use cases will emerge. With that, there is an increasing need to identify, manage, and mitigate the unique risks that AI-based technologies may bring.
We recognize that AI has been the answer to solving many real-world challenges, yet we believe it must be accompanied by a moral imperative so its growth will yield a sustainable, positive impact. In building out AI systems, we must ensure that coders remove bias in AI structures and that privacy and security are at the heart of every process.
Cisco employs AI for a wide range of use cases. These include predicting network outages, combing vast troves of data for security threats, and in our collaboration solution Webex, to power features like real-time translation. But Cisco is also a leader in using AI ethically and responsibly, thanks to its policies regarding data privacy and human rights.
Cisco is committed to maintaining a responsible, fair, and reflective approach to the governance, implementation, and use of AI technologies in our solutions. In 2022, we published Cisco’s Responsible AI framework. We believe our customers, stakeholders, and the world at large will be better off if we collectively endeavour to leverage the promise of AI responsibly and ethically.
As such, we are evolving our Responsible AI framework in the context of content generation by AI models to handle new risk variants including but not limited to false content and unanticipated output to enable our teams and customers to adopt AI with the speed and scale needed to maximize value, and the safety and security to mitigate risk and bias.
How can companies use their resources on using generative AI to create competitive advantage?
The global AI market is projected to reach a staggering $15.7 trillion by 2030, underlining the significance of AI adoption in strategic decision-making.
The past decade has seen a massive adoption of machine learning (ML) and artificial intelligence (AI), and an increasing number of organizations have been leveraging such technologies to automate their operations to make their products and services better. Today generative AI has been gaining significant traction.
AI helps humans make better decisions and work faster. For example, data-centric hedge funds already rely on AI to support new trading models. And in a time of acute shortage of talent, HR departments are looking to AI to enhance talent acquisition and retention. We see businesses in the region are increasingly harnessing the power of AI in every sphere — from enhancing the customer experience in retail to providing more accurate medical insights to patients.
To support these trends, AI has been an important element in our products for several years, and lately, we have announced new, market-leading AI technologies across our Collaboration and Security portfolios designed to boost productivity, enhance policy management, and simplify tasks.
What factors do companies need to consider before adopting generative AI such as having a centralized data strategy?
Several factors need to be considered before adopting generative AI. We need to address the skills gap. If we don’t have the manpower to staff, serve, and protect this networked infrastructure, we cannot sustain innovation and propel economic growth. At the same time, large segments of our population will be left behind during this evolution of technology.
It is also our responsibility to be ethical stewards of technology. This means committing our teams to remove bias in AI. If we don’t address bias up front, we will simply automate that bias to the point of no return. Also, security and data privacy should be embedded across the whole process with no compromise. The rapid digital acceleration around the world means that the threat landscape is also growing and so too are our vulnerabilities.