5 minute read 16 May 2022
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Five ways MENA companies can improve trust in AI

By Eva-Marie Muller-Stuler

EY MENA Data & AI Consulting Leader

International award winning Data & AI pioneer, evangelizing the adoption of Ethical AI and scalable AI practices.

5 minute read 16 May 2022
Related topics AI Consulting Trust Technology

MENA companies must recognize the benefits of AI in shaping their businesses and keeping up with the world evolving around them. 

In brief
  • Artificial intelligence (AI) and data science offer the opportunity for companies in MENA to generate insights about customers, make process improvements and automate decision-making. But the last few years have shown that it is not easy and that technologies can also come with significant financial, reputational and even legal challenges.
  • Trust in the data and transparency about why an AI model comes to a certain conclusion, is pivotal.
  • The underlying data of AI models should be comprehensive and representative of the targeted demographic. This is a significant challenge in the MENA region, given the diverse and fast-changing nature of its young society. Data that is relevant today will age quickly, and the monitoring and retraining of fully deployed models in the region must reflect this.

Across the MENA region, ambitious governments are encouraging companies to adopt leading-edge technologies to drive economic growth. Among the resources of new techniques is artificial intelligence (AI), in which a large volume of data is used to train an algorithm, which then dynamically “learns” to make better decisions.

AI’s distinct qualities — that it can make some decisions at a scale and speed faster than humans — at times make it fundamentally risky. In recent years, companies have suffered reputational and financial repercussions from deploying unsound AI models.

The snags of the technology constantly multiply in a region that is changing as rapidly as MENA, making recently gathered data quickly irrelevant, or models built for entirely different demographics not transferable. In just one example, the UAE recently switched to a Monday to Friday workweek after long maintaining Friday as a non-working day. That means historical data on traffic and energy consumption patterns, for example, must be adjusted. Yet historical data that is not adjusted for this effect, may still be present in AI models.

To successfully embed AI in decision-making, MENA companies must grow more comfortable with the technology and develop a track record of successful implementations. Five ways companies in the region can increase their trust in AI are:

1. Plan around risk as well as rewards

The potential gains from AI are so attractive that companies often jump at the opportunity to set up the technology, especially if pilot projects suggest that a change can yield significant results. Instead, companies should conduct an inventory of where AI might be used, focusing on potential benefits in areas that align with existing corporate strategies. Reputational risks must be evaluated for each use case, alongside financial and execution risks.
Ideally, this should take place before AI is deployed. Companies already using the technology should audit the risks of current deployments and pause them if necessary.

2. Invest in data

An AI model is only as good as the data that goes into it. There is no point in investing in leading-class data scientists if you do not have meaningful datasets on which they can train models. AI projects consist of multiple parts — from data quality frameworks to machine learning operations (MLOps) and change management. Therefore, the strategy should consider all these factors and not just focus around building a few quick proofs of concepts (POCs). To reflect fast-moving and slow-moving data signals, the ingestion of data must be ongoing, allowing the AI to reflect up-to-date information.

3. Use transparent models

AI may make a different decision today than it did yesterday as it learns and adapts to new inputs. But business decisions, for example, handing out promotions or choosing who to grant loans to, must be explainable, justifiable and auditable. If not, then a company will not be able to quantify the risks and justify the outcomes to customers, employees and regulators. Ultimately, managers still need to be held accountable for the decisions that they make.

For both the models and the underlying data, it is essential that people’s privacy is protected and that the model is robust against unforeseen incidents. The best practice here is to embed solutions in robust cybersecurity frameworks.

4. Audit before deployment — and after

Ideally, before deploying an AI model, it should be peer-reviewed and audited. In the future, we will see more of the role of an AI auditor, who examines and passes a model, or suggests improvements to mitigate risk. Once deployed, an AI must be continuously monitored and re-evaluated. Companies must use the best tools and techniques available to continuously monitor outputs and ensure they continue to deliver against corporate objectives.

5. Hire diverse teams

Even a perfectly designed AI may lead to conclusions that are unacceptable to a company due to ethical values. Models must therefore be subjected to more than simply technical checks and a variety of different disciplines should be involved in designing and evaluating AI applications. A business line leader or designer, for example, might have different insights from a data scientist or a data engineer.

Teams should reflect a diversity of roles and backgrounds, including gender, religion and race. This increases the chance of bias being identified early on and of designing a data collection process that is truly representative.

MENA companies have much to gain from deploying AI more widely, as long as they do so wisely. That means gathering usable data, using transparent models, and building interdisciplinary teams.


MENA companies are halfway there when it comes to successfully embedding AI in decision-making. Improving the current process should be the key focus, especially when it comes to trustworthy data, algorithms and setting up as they play a major role in deciding the fate of an AI model that is programmed to garner accurate results.

About this article

By Eva-Marie Muller-Stuler

EY MENA Data & AI Consulting Leader

International award winning Data & AI pioneer, evangelizing the adoption of Ethical AI and scalable AI practices.

Related topics AI Consulting Trust Technology