Demonstrating the multi-million-dollar revenue uplift that AI can bring for public-sector organisations across the Middle East

AI and economic reform

The Middle East is continuing its transition away from oil- and hydrocarbon-led economies and embracing the economic reform needed to create a high-tech future.

The Saudi Government is leading by example when it comes to conceiving digitalisation projects and driving adoption of the latest technologies, mindful of their potential to transform the country’s economy and to attract capital. 

Implementing and accelerating AI adoption

As a public-sector organisation with ambitions to be a technology role model, our client wanted to develop best practice in adopting AI and advocating for its efficiency gains, cost savings and revenue opportunities. First, it needed to fully understand the complex vendor landscape and the areas where AI brings the most value. 

Analysys Mason was asked to recommend key areas of focus for the organisation, and to develop a strategy and roadmap to implement and accelerate adoption of AI.

Prioritising AI use cases with the greatest impact

Analysys Mason conducted comprehensive global research of AI use cases used by enterprises, telecoms companies and related government and public-sector entities. This was done through primary and secondary research, including conversations with public bodies around the world and discussions with leading AI technology experts and vendors. The insights into how the industry is evolving globally, such as AI’s primary use cases, roadblocks and longer-term opportunities, resulted in a benchmark study of more than 50 AI use cases implemented by organisations globally.

This extensive list was then explored with the client teams across the organisation, refined and restructured to ensure specific applicability, and then narrowed down to five prioritised use cases based on potential for efficiency gains, revenue upside, and so forth. It was also important to assess the technical feasibility of shortlisted use cases via discussions with several technology vendors using criteria such as data availability, accuracy and potential impact, before putting recommendations to the client.

We worked with some of the major technology vendors to conduct viability studies into the use cases and gather technical feedback. This included understanding the volume and level of data input required for the specific AI algorithm; the potential form of AI being used (large language models, natural language processing, speech-to-text/text-to-speech); open-source versus bespoke builds; data sovereignty requirements; accuracy and timelines. 

Drawing a roadmap to an AI future

Based on all discussions and inputs, we developed a roadmap of prioritised use cases and a potential pipeline for subsequent implementation. From here, we developed a series of RFPs, in line with the client’s typical structure and approach, to be sent out to vendors. The potential value of the recommended AI use cases lay predominantly in cost savings but also included an application with potential revenue upside of almost USD4 million.