Artificial Intelligence – The most powerful technology – News | #cybersecurity | #cyberattack



1. As one of the top technology solution providers globally, where do you see AI in GCC when compared to AI across the globe?

Artificial Intelligence is potentially the most powerful technology businesses have ever had access to. It is already changing the way businesses operate today, from how they communicate with their customers via virtual assistants, to automating key workflows, and even managing network security. The “2021 CEO Study” from IBM’s Institute for Business Value recently revealed that more than half of CEOs surveyed expect AI to deliver tangible business benefits in the next few years.

AI is set to be a transformer for the GCC market. We’re already witnessing that the momentum is shifting in our region, as the need for AI has been accelerated by changing business needs due to the global pandemic. While recent advances in the technology are making AI more accessible than ever, companies in our region are now starting to see the major benefit of AI for their business models, and this has been accelerated by COVID19.

The GCC countries are taking bold steps—through increased investment across sectors and policy awareness and commitment—to prepare and position for dramatic progress using AI. AI investment is clearly on the rise. Recognizing AI’s growing significance in the GCC—for example, the Emirates with the UAE Artificial Intelligence Strategy 2031, and Saudi Arabia with the Vision 2030 plan—place AI capabilities at the center of national economic strategies.

2. One of the most important aspects across all industries is cybersecurity. How do you see AI helping develop robust security systems?

There’s no question that AI is changing the security industry, it plays a significant role in tackling advanced cyber threats through automatic threat detection systems. This results in developing a more efficient system for threat detection and prevention. If the computer is already affected by a cyberattack, these early detections can help spot the potential vulnerability before causing any significant risk to the users.

The development of the role of artificial intelligence in cybersecurity has brought in the need for automation and regulation in keeping the digital infrastructure safe.

Security incidents became more costly and harder to contain due to drastic operational shifts during the pandemic, revealed a recent study commissioned by IBM Security on the cost of data breach on organizations surveyed in Saudi Arabia and the UAE. The financial impact of these security incidents in the Middle East has risen by 6% over the past year and has reached the highest cost in the report’s 8-year history in the region. These data breaches cost companies studied in the region $6.93 million per breach on average, which is higher than the global average of $4.24 million per incident. Of course, this was due to several factors, including remote working and rapid adoption of digitization in the Middle East.

Without AI-Infused security tools, critical industries will continue to struggle adopting their cybersecurity programs to the changing data. AI can bring immense innovation by analyzing vast amounts of data to detect security threats in real-time. AI is trained by consuming billions of data artifacts from both structured and unstructured sources, such as blogs and news stories. Through machine learning (ML) and deep learning (DL) techniques, AI improves its knowledge to “understand” cybersecurity threats and cyber risk. AI gathers insights and uses reasoning to identify the relationships between threats, such as malicious files, suspicious IP addresses or insiders. This analysis takes seconds or minutes, allowing security analysts to respond to threats up to 60 times faster.

3. As organizations recognize the importance of a holistic approach to governed data and AI technology; how important do you think is trustworthy AI to business?

Trustworthy and explainable AI is critical to business. A recent research commissioned by IBM in partnership with Morning Consult, the “Global AI Adoption Index 2021”, revealed that 91% of businesses using AI say their ability to explain how it arrived at a decision is critical. While global businesses are now acutely aware of the importance of having trustworthy AI, more than half of companies cite significant barriers in getting there including lack of skills, inflexible governance tools, biased data and more.

Trust is now clearly top of mind for businesses as they think about their consumers, with a majority of businesses believing that consumers are more likely to choose services of a company that offers transparency and an ethical framework on how its data and AI models are built, managed, and used.

Trustworthy AI has three ethical principles at its core. First, that the purpose of AI is to augment human intelligence. Second, that data and insights belong to their creator, not vendors. And third, that new technology and AI systems must be transparent and explainable. Companies must be clear about who trains their AI systems, what data was used in training and, most importantly, what went into their algorithms’ recommendations.

4. More than 80% of C-suites are planning to implement hybrid cloud for business transformation– According to you, why should it become a top priority for businesses?

Hybrid cloud is IT infrastructure that connects at least one public cloud and at least one private cloud, and provides orchestration, management and application portability between them to create a single, flexible, optimal cloud infrastructure for running a company’s computing workloads. It is designed to help a company achieve its technical and business objectives more effectively and cost-efficiently than public cloud or private cloud alone. In fact, according to one recent study, companies derive up to 2.5x the value from hybrid cloud than from a single-cloud, single-vendor approach.

Companies rarely start from scratch – they have complex and unique workloads and apps. They have messaging, data and transactional systems, all integrated into their operational and security systems. Hybrid cloud is about meeting them where they are at in terms of the IT infrastructure choices they have made and the various places where they will do computing; whether it is in a public cloud, a private cloud, or on premises.

IBM believes that hybrid cloud is swiftly becoming the dominant force driving change in the IT industry. We also believe that vendor lock-in goes against the spirit of true hybrid cloud – which should be open, but also provide the security and control businesses need. Therefore, IBM has been making significant investments to help accelerate innovation by offering a next-generation hybrid cloud platform built on open-source technology, hence capitalize on the massive opportunity that hybrid cloud represents globally —$1.2 trillion, according to IDC.

5. How can innovative technology help businesses in the Middle East and positively impact the bottom line?

The Middle East has become an active innovation center, characterized by leading players – large and small. As the economies of the region seek to diversify away from their historical dependence on oil, and as the energy industry itself adapts to global market shifts, the importance of innovation will increase.

In the Middle East, technology innovation has enabled the development of new products, services and business models that were hardly conceivable just a few years ago. Their pace and scope continue to have an astonishing impact on markets and societies.

Examples are many – let’s look at the instant payments in the Middle East. COVID-19 has completely transformed the way consumers and businesses in the Middle East think about how they make and process payments that drive day-to-day life and the economy overall. For example, Saudi Payments, a fully owned subsidiary of the Saudi Central Bank (SAMA) announced the launch of the “sarie” instant payments system in collaboration with IBM and Mastercard. This collaboration marks a key milestone for payments innovation in the MEA region and the introduction of “sarie” is in line with Saudi Arabia’s Financial Sector Development Program (FSDP) under Saudi Vision 2030, which targets achieving 70% non-cash transactions by 2030. “

The oil and gas industry in our region is also one of the prominent users of AI-based systems and software. Companies that operate the region already use AI and other innovative technologies, as a part of their operations for better productivity, transparency, and real-time data availability. The companies are continuously trying to digitalize their operations and mining with the help of AI.

Innovators in the Middle East have significant resources that they can leverage. These include large national and industry transformation programs that encompass multiple sectors, such as Saudi Arabia Vision 2030, UAE Vision 2021, and Qatar’s National Vision 2030. Many companies are pursuing new technologies outside of traditional areas of strength. The Middle East is emerging as a melting pot for multinational corporations and leading global academic institutions, and Middle Eastern governments and private institutions have established global partnerships that serve the innovation agenda. There also has been extensive investment in startups, both in the form of venture capital activity and incubation facilities.

6. Is AI like a sure-fire path to success?

While the adoption of AI in businesses is taking off, enterprise deployment of AI is still only a third of the way complete. Nobody said AI was going to be easy. Yet, there are tremendous benefits to be gained for businesses that manage to adopt it successfully.

Barriers to scaling AI for business are related to trust, or skepticism with AI outcomes, quality and complexity of data, and the skill gaps for building and deploying AI.

IBM is committed to lowering those barriers to entry and making AI more accessible to businesses by offering an architecture (AI Ladder) based on client insights that illustrates the four key areas clients must engage to successfully implement AI capabilities: Collect Data, Organize Data, Analyze Data and then Infuse AI.

7. What are the top pitfalls to be kept in mind while embarking into journey to AI?

To ensure successful AI implantations, organizations need to understand how to adopt and implement the technology and realize there will be failures along the way. To turn AI aspirations into outcomes, organizations need to overcome three major AI challenges: data complexity, skills, and trust.

  • Data Complexity: The problem that many enterprises face is that 80% of data is either inaccessible untrusted or unanalyzed. Data is the foundation and fuel for businesses to drive smarter decisions particularly as they embark upon digital transformations. The problem is that while 90% of business leaders list improving the use of data as a top priority, only 15% of them are actually getting what they need from their data. As a result, the majority of businesses have a plan to build a system of insights to become data-driven and have declared the journey to AI as a strategic priority. Data is the lifeblood of AI, and if organizations don’t solve for its complexities, their progress can be slowed by data siloes, incomplete data, and the appropriate approach to governance.
  • Skills: Data is the lifeblood of AI, but you also need skills , such understanding and building deep learning and machine learning models, to bring AI to fruition. The challenge is that AI skills are rare, and therefore in high demand, so there’s a shortage of skilled workers available to hire. This makes it even more important that the technology being built and used is more easily accessible to everyone within the business, regardless of skill level.
  • Trust: For organizations to truly embrace and scale AI across the entire businesses, they need to break open the ‘black box’ of AI and trust the systems. It is critical to ensure AI recommendations or decisions are fully traceable – enabling enterprises to audit the lineage of the models and the associated training data, along with the inputs and outputs for each AI recommendation. As more applications make use of AI, businesses need visibility into the recommendations made by their AI applications.

For AI to thrive, and for businesses to reap its benefits, it is imperative that organizations are able to address these three challenges to ensure they trust their AI systems, have the right skills across their organization, and access to their data, no matter where it resides.

Through IBM’s work with clients all over the world, we have learned that there are three capabilities that will determine the success and scaling of AI in business: Natural Language Processing (NLP), Trust and Explainability, and Automation.

  • NLP: To support people in their daily work, AI must understand the language of business, spanning human language, documents, contextual meaning, etc. With such insights in hand, organizations can improve everything from customer care and transportation, to finance and education.
  • Trust and Explainability: Trust is essential to AI adoption. It allows organizations to understand and explain recommendations and outcomes and manage AI-led decisions in their business (which can be critical for regulatory requirements, among other things)—while maintaining the full ownership and protection of data and insights.
  • Automation: Automating the mundane data collecting and sorting work is critical to facilitating the deployment of AI. Automation and lifecycle management tools, in combination with chip and system-level advances, are essential to scaling AI.

8. To adopt AI, do enterprises need expertise with deep machine learning skills?

Democratized AI introduced improvements in AI tooling, which are lowering the level of expertise required to build AI models. This will make it easier to include subject matter experts in the AI development process. Democratization makes AI available and accessible to the breadth of talent in an enterprise. Business users know the business in and out. Enabling them to build AI-powered applications using visual application development platforms, including those with drag-and-drop functionalities, can close the gap in data science talent. It’s important to note, though, that AI democratization doesn’t replace data scientists. It helps business users collaborate better with data scientists and see them as a partner. Essentially democratization brings the business closer to the technology and the technology closer to the business. It can also free data scientists to do higher value work. Democratized AI will not only speed up AI development, it will also ensure the level of accuracy provided by subject matter experts. Frontline experts can see where new models can provide the most value and where they can create problems or need to be worked around.


Interview by :

Marwan Dardounh

IBM Executive, Data, AI and Automation Technical Sales Leader





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