The Kingdom of Saudi Arabia is all set to embrace the emerging technologies to adapt to the post pandemic economic landscape. Envisioning Saudi Arabia as a global hub for AI and Data, the National Strategy for Data and AI is a landmark upon which enterprises in the region will unveil the potential of AI and Data Analytics to attain the Kingdom's transformation into a leading AI and data-driven economy. Middle East Enterprise AI and Analytics Summit 2023 attempts to bring Saudi Arabia closer to its vision by curating a world class platform for tech-leaders in the region to connect, communicate and collaborate under the theme "Accelerating Innovation in Enterprises with Applied AI and Analytics Strategies". Governments and enterprises realize the significance of AI and Data Analytics in their digital transformation journey to make their operations smoother, faster and more efficient leading to huge investments in cutting-edge technologies. But there still exist challenges in terms of real time implementation, scalability, infrastructural and organizational cultural changes at the enterprise level.

Artificial Intelligence (AI) is built on data. Yet, many organizations are still finding it hard to implement AI properly to make the most out of their data. There are concerns that the AI is not able to comprehend the data the way they want it to, especially with more businesses having their data stored across the multi-cloud and even on-premise. When it comes to data analytics, SAS has been a household vendor in the industry for years. The data analytics leader continues to pioneer new innovations when it comes to providing businesses with the insights they need in the best way possible.

This blog post was written by Dr. Maryam S. Jaffer, Director Data and Statistics, Emirates Health Services; Dr. Bashar Balish, Senior Director, Cerner; and Michel Ghorayeb, UAE Managing Director, SAS. The future of health care has never been more exciting. Artificial intelligence (AI) and data analytics have captured center stage for any business planning on surviving and thriving. Given the pace of technological development, AI is transforming the future on an unprecedented scale. And that includes the future of health care.

Organizations must increase visibility, monitoring, and leverage AIOps and data analytics to mitigate "The Watermelon Effect" In the business world, "The Watermelon Effect" is a concept that describes when things appear to be positive and working properly (green) on the surface, but with a closer, deeper look, the outcomes and value expectations are underachieving (red). For example – work may be getting done on time and meeting deadlines, but the quality of the work delivered may be low. It is not difficult to imagine examples of key performance indicators (KPIs) falling short when investigated at a more granular level. This lack of transparency and comprehensive visibility can create tension between technology teams and the business, creating barriers to alignment between the two groups. The Watermelon Effect typically results in a lack of trust and raises credibility concerns.

After years of resisting "pretend football," I finally joined a neighborhood fantasy football league. I'm a very casual football fan and probably couldn't name 10 active players without several minutes of thought, but in the interest of participating in some neighborly fun and learning a bit more about the game, I created my first team. I frankly still don't fully understand fantasy football scoring and all the nuances, but for the unfamiliar, you select a virtual team from a pool of available players during a draft process, and each player's activities on the field that week contribute to your overall team score. For example, if my defense blocks a touchdown, I might get 10 points, while if a running back on my team rushes for a few yards in a different game, I get a fraction of a point. Theoretically, this creates interest in more teams by giving the fan more players to follow, but at this point, it's mainly creating confusion as my extremely limited "football brain" attempts to follow a half dozen simultaneous games.

Airlines and airports are now embracing new technologies and turning to artificial intelligence (AI) to support their customer service. Technology is drastically changing the way businesses connect with their customers, and the world of aviation is part of the change too. Data and the way it is used is transforming airlines from pre-flight to post-flight operations, including ticket purchase, seat selection, luggage, boarding and ground transportation. The data required is captured along the various components of a passenger's journey, allowing organisations to take informed steps towards operational efficiency and improved customer experience. Airlines and airports are now embracing new technologies and turning to artificial intelligence (AI) to support their customer service.

The economic value of data for companies is challenging to conceptualize and measure directly. Many executives have the wrong perception of data monetization. To them, the only way to derive economic value from data is to sell it to other companies. As a result, they overlook the immense untapped value that it represents. Companies can monetize by improving customer experiences, reducing costs, finding new customers, and so much more from the data that is produced directly or indirectly using big data analytics and AI.

With the upcoming NFL draft, the stakes are high for the league's billion-dollar franchises. Few events represent greater opportunities than the annual talent assessment undertaken by professional football teams. In a highly competitive league with fixed salary caps, the selection of new talent can make or break football operations. If you make the right choices, your team's fortunes can sky-rocket while personnel mistakes consign your team to below-average performance. In this type of situation, it is little surprise that teams are deploying the latest technologies as part of their skills assessments, talent recruitment, and evaluation of injury proneness.

Gartner has forecast that AI and data science-equipped VC or private equity (PE) investors will become commonplace in the next 4-5 years, given the recent advances in data analytics and AI models. "Successful investors are purported to have a good gut feel-- the ability to make sound financial decisions from mostly qualitative information alongside the quantitative data provided by the technology company," Patrick Stakenas, senior research director at Gartner said in a statement. Stakenas said this inability to quantify inner voice grown from personal experience is decreasingly playing a role in investment decision making. AI models can help investors by determining the viability, strategy and potential outcome of an investment in an early-stage startup, based on past investments, revenue growth, market penetration, consumer sentiment and their industry experience. "AI tools will be used to determine how likely a leadership team is to succeed based on employment history, field expertise and previous business success," added Stakenas.

Indian Railways collaborated with the Indian School of Business (ISB), Hyderabad, to establish a Centre of Excellence in Artificial Intelligence and Data Analytics for South Central Railways. The CoE is aimed at serving the railways' needs of AI by analysing all the data gathered, for providing better services to both passenger and freight customers. Gajanan Mallya, General Manager of SCR, handed over LoA of Milind Sohoni, deputy dean, ISB, Hyderabad, in the virtual presence of Vinok Kumar Yadav, CEO and Chairman, Railway Board. Speaking on the occasion, Mallya said, "With the growing importance of Data Analytics and Artificial Intelligence, it is the right time for establishing a Centre of Excellence in this area and ISB is a right partner for this project. These new technologies have become vital tools to make the organisations more effective."