DISRUPTIVE TECH

According to global and regional research by McKinsey, it has estimated that the application of Generative AI to 63 use cases could generate global annual economic value between $ 2.6 trillion and $ 4.4 trillion, adding 15 to 40 % to the value previously estimated from other AI technologies, such as machine learning, advanced analytics, and deep learning.

In Gulf Cooperation Council, GCC countries, the same Generative AI use cases could generate between $ 21 billion and $ 35 billion a year, on top of the $ 150 billion that other AI technologies could deliver. To put that into perspective, Generative AI could be worth 1.7 to 2.8 % of annual non-oil GDP in the GCC economies today.

According to a recent Middle East survey by global consulting firm, BCG, Generative AI applied to technology functions can broadly impact up to 65 % of IT spending and deliver potential gross savings of up to 10 % of the IT spend. This would be across IT infrastructure and operations, service desks, and digital workplace tools being the most relevant areas for deployment in the short term.

And while AI and Generative AI have enormous potential to generate gains and benefits, it does not offer any low hanging fruit for enterprises at scale. The challenges are quite diverse and impact multiple areas. These include identification of business objectives and business value, job roles and skills required, managing data repositories and data compliance, scalable and high performing IT infrastructure, IT costs and modernisation, and commitment of the top management. forming the foundation for automation and digitising best practices. Historically IT and data management were never built to run end to end but to perform excellently within fixed boundaries and walls. Unfortunately, AI and Generative AI do not work in this fashion.

Early feedback from teams that begin their AI journeys point to the challenges of data management across multiple operational silos, different IT tools and platforms, and varying or even unidentified business owners.

According to a survey by HFS Research and Syniti, 85 % of respondents realise that data is a cornerstone of business success. However, only a third are satisfied with their enterprise data quality and realise that more than 40 % of their organisational data is unusable. So while the good news is that enterprise leaders are serious about data, the downside is that enterprises are struggling to make progress.

Today, enterprises are drowning in data debt. More than 40 % of organisational data is bad and unusable, which creates an opportunity cost of 25 % to 35 % across organisational goals. There is poor alignment between data quality and business outcomes. The result is that enterprises are failing to scale their data strategies. Only one in four respondents have fully implemented an active company-wide data management strategy.

According to Gartner, every year poor data quality costs organisations an average of $ 12.9 million. Apart from the immediate impact on revenue, over the longterm, poor-quality data increases the complexity of data ecosystems and leads to poor decision making. Data quality is directly linked to the quality of decision making, say Gartner analysts.

Today, data quality is the competitive advantage that business and IT decision makers need to focus on continuously.

Data transformation

Hilel Baroud, CEO, PROVEN Consult

Data management

By default, and mostly due to legacy information technology architectures, different business functions of an enterprise are owners of their own data. These data repositories have usually been siloed and have worked well for those specific business functions.

The challenge arises when business processes connect, sharing a data thread that runs across the enterprise,

Raw data arrives in multiple formats, from various sources, and in large volumes, which can make it challenging to extract insights directly. This is where data transformation becomes essential.

Data transformation is the process of converting, cleaning, and structuring data into formats that are not only compatible with business systems but also optimised for analysis. By partnering with specialised players, and implementing effective data transformation

www. intelligentcio. com INTELLIGENTCIO MIDDLE EAST 73