How Can Leaders Create Value From Generative AI?


Artificial Intelligence (AI) is revolutionizing the way businesses operate, leading to what many call a more profound business transformation. According to GenAI ARC Survey, 74% of EMEA companies say they are either investing in or exploring Generative AI.

As industry leaders look to harness this formidable technology, the challenge lies in creating real value from ‘gen AI’ – a term that symbolizes the latest generation of AI capabilities. But generating such value is not just about adopting the technology; it’s about reshaping the entire organization to leverage generative AI effectively. This means setting new industry standards, redefining responsibilities, and ensuring responsible AI practices are just the beginning.

Essential Capabilities Required to Leverage the Advantages of AI

AI is changing the business game. Those who already have a pre-ready structure will gain more advantages. Others, or new players like startups, need to ensure they have these capabilities to stay ahead of AI.

Data Governance: It involves establishing robust processes for collecting, storing, and managing data to ensure accuracy, security, and compliance.

Ethical AI Framework: Implementing guidelines and protocols to ensure AI systems are developed and deployed ethically, respecting privacy, fairness, transparency, and accountability.

Talent Development: Building a skilled workforce with the knowledge and expertise to develop, implement, and maintain generative AI solutions.

Innovation Culture: Cultivating an organizational culture that fosters creativity, experimentation, and collaboration to drive continuous improvement and innovation in AI applications.

Risk Management: Developing strategies to identify, assess, and mitigate potential risks associated with AI implementation, including cybersecurity threats, biases, and unintended consequences.

Continuous Learning and Adaptation: Establishing mechanisms for ongoing monitoring, evaluation, and adaptation of AI systems to respond to changing business needs, technological advancements, and regulatory requirements.

These listed capabilities in their current companies allow leaders to leverage generative AI’s advantages while avoiding potential pitfalls. This makes it easier to define AI teams’ industry roles to transform our businesses better.

Before Adopting AI Practices, Do Your Analysis Well

Using AI responsibly ensures that AI systems work fairly, clearly, and well. These practices help companies build trust with users and partners. These principles ensure that AI projects match the company’s beliefs and society’s expectations.

By realizing how important following these practices is, leaders can ensure that AI benefits everyone involved. Being open about handling data, making AI decisions clear, and designing things ethically is critical to making generative AI investments pay off in the long run.

Designating AI Organizational Responsibilities

Let’s discuss who should be responsible for keeping AI within these ethical limits. It’s not just one person or team’s job—it’s a team effort. Everyone from the AI team to top managers must work together to ensure AI projects stick to ethical rules.

Responsibility in AI is not just a buzzword; it forms one of the pillars of what we often refer to as responsible AI principles. Adapting to these shifts can sometimes be instinctive. Understanding the critical elements of AI play is crucial to navigating this complex environment. It involves identifying task changes and knowledge requirements, particularly for security teams adapting to the new AI-driven landscape.

Leaders must also focus on the importance of responsible generative AI practices within their organizations, recognize who should carry the baton for AI responsibilities, and comprehend the nuances of accountability in an AI-enabled world.

AI technologies carry a substantial risk of misuse or unintended consequences without responsibility and accountability. The definition of AI organizational responsibilities is the cornerstone of a successful AI strategy.

Responsibilities of Different Roles

Product managers are pivotal in clarifying the purpose of AI solutions, ensuring that they meet customer needs responsibly. They bridge the AI’s technical capabilities and the product’s value proposition, warranting that the technology’s application aligns with ethical guidelines and business objectives.

AI development teams, on the other hand, make overarching decisions on AI design and implementation. They are the architects behind the algorithms that will drive the AI’s decision-making processes.

Compliance teams, including Data Protection Officers (DPO), play a crucial role in overseeing the application of AI within regulatory frameworks. They ensure that AI-related activities align with data protection laws and industry standards. Their deep understanding of these frameworks enables them to act as a safeguard against potential legal and ethical oversteps.

Senior management envisions disrupting and innovating through generative AI while maintaining responsibility for steering their organizations toward responsible usage.

Ultimately, we can easily say that It’s a collective responsibility, with each role providing a crucial perspective on the responsible use of AI. As organizations continue to integrate AI into their day-to-day operations, clearly designated roles and articulated responsibilities become the blueprint for operational excellence, helping to harness AI’s potential while mitigating its risks.

Developing the AI Talent Within

As businesses transform with AI, it is essential to upskill existing talents and clarify the AI-specific skills needed. The AI revolution brings a host of new competencies into the limelight, from data science to AI ethics. Upskilling programs impart these critical skills and promote a culture of continuous learning that can keep pace with rapid technological evolutions.

Investing in staff development and aligning generative AI initiatives with strategic goals helps create an adaptable, knowledgeable workforce committed to digital transformation.

Identifying the essential skills for AI is essential when hiring new talent. This includes technical skills in AI and machine learning and understanding data and AI ethics. Recognizing the need for diverse skills guides recruitment strategies that complement the organization’s strengths.

It’s not just about hiring the right people; retaining them is crucial, too. Creating an environment that values innovation and ownership helps keep employees satisfied and motivated. This aligns with a leadership vision that embraces technology while prioritizing human-centered values.

Successfully adopting AI requires a shift in mindset. Developing AI talent involves more than technical training—it also fosters adaptability and a culture focused on responsible AI deployment. This ensures that generative AI is integrated into the organization’s ethos.

Ensuring Data Quality

Data is the lifeblood of AI systems, and ensuring its quality is quintessential for deriving value from it. High-quality data leads to more accurate AI predictions and decisions, which can drastically improve a wide range of business operations. As leaders push for transformation through AI, they must prioritize data governance and quality assurance protocols.

For gen AI to be truly effective, an organization must focus on structured data and the vast reservoir of unstructured data it possesses. Unstructured data, which include emails, images, and social media posts, often hold untapped insights that can unlock new opportunities for innovation and competitive advantage.

However, realizing the full potential of unstructured data requires sophisticated AI tools capable of processing and analyzing it. This is where investing in the right technology stack and having the talent to utilize it becomes critical. The ability to identify patterns and derive meaning from complex data sets can open new horizons in personalization, customer service, and beyond.

Leaders play a significant role in this data-focused strategy. They must ensure that they create a supportive culture where the importance of data quality is recognized across the organization.

Moreover, focusing on data quality should be complemented by a solid commitment to data privacy and security. With AI systems continuously learning and evolving, safeguards must be in place to ensure data is handled responsibly. This is where organizational policies and procedures must align with the highest standards of data stewardship.

Lastly, leaders should be aware of the power of unstructured data as a strategic asset. When properly harnessed, this underutilized resource has the potential to inform and transform all facets of business operations. Generative AI’s ability to efficiently manage and glean insights from such data will place businesses that commit to its exploration at the forefront of innovation.

Implementing AI in Product Development and Strategy

AI is revolutionizing product development, providing unmatched opportunities for customization, process optimization, and innovation. To thrive in the digital era, organizations must integrate AI into their product strategies from the start. This demands a clear vision and a committed effort to embed AI capabilities into products and services.

Product managers play a pivotal role in this integration. They must understand AI’s potential impacts and applications, aligning them with customer expectations and business goals. Their insight into AI’s possibilities can elevate products from functional to intelligent solutions that meet complex consumer needs.

However, one challenge lies in ensuring that AI enhances a product’s value proposition without compromising user experience. Product managers must ensure that generative AI features are not merely add-ons but integral to the product’s core functionality and purpose.

Strategic AI implementation can redefine competition. Organizations that grasp and utilize AI’s capabilities can lead the market, offering innovative solutions that set new standards. This strategic alignment of AI with intent often reveals new market opportunities.

Integrating AI into product development is an ongoing journey. It requires a willingness to experiment, adapt, and refine AI applications as technology evolves. This process demands technological expertise and a culture of agility and openness to change.

Organizations must cultivate collaboration among product managers, AI developers, and strategists to leverage AI’s potential in product development fully. Facilitating dialogue between these roles ensures that products are technologically advanced and meet market needs and organizational objectives.

Why AI Regulation Matters?

  • Protecting Privacy: As the first off our list we have the protection of privacy. The importance of privacy is crucial to every step we take with AI so its security should be ensured. This regulation helps us prevents unauthorized access to personal data as well as ensuring individuals have control over their own information. According to some recent surveys 25% of users are concerned that GenAI
    use will expose them to brand or regulatory risks.
  • Fostering Trust: Trust stands as the one thing we should persevere. With all the possible power struggles we should regulate these laws vigorously.It will help us establish a framework for transparent AI development and deployment while Enhancing user confidence in AI technologies and applications. Therefore it will build trust between businesses, governments, and consumers in AI-driven services. According to surveys, 24% of users are concerned about the accuracy or potential toxicity in the output of GenAI models.
  • Mitigating Bias and Discrimination: In the times we are living now, discrimination is an issue that cannot be tolerated. Each company or businesses are and should have strict ways to apply equality in their companies. These regulations help them implements guidelines to identify and mitigate bias in AI algorithms while promoting diversity and inclusivity in AI development teams and datasets.
  • Ensuring Accountability: Within such powerful innovation, making sure we know how to distribute responsibility and accountability is crucial. With precise regulations assigning responsibility for AI system outcomes to developers, operators, and users while also defining clear guidelines for handling errors, failures, and unintended consequences will be easier.
  • Safeguarding Humanity: While focusing on technology much, we should never forget our values as people. These regulations will help us protects against the misuse of AI for harmful purposes, such as autonomous weapons. Also it will ensure that AI technologies are developed and deployed in alignment with human values.
  • Balancing Power Dynamics: While dealing and innovating AI, we should never let anyone abuse any power. With certain regulations we will prevent monopolistic control over AI technologies and data by a few entities while also promoting fair competition and innovation in the AI industry.

3 Sample Use Cases for Selected Industries


Dubai Electricity and Water Authority (DEWA) Dubai Electricity and Water Authority (DEWA) have been actively embracing Artificial Intelligence (AI) to foster innovation, boost productivity, and elevate service standards. Here are some notable initiatives through which DEWA harnesses AI:

  • Rammas: DEWA’s virtual AI assistant, Rammas, is accessible through various customer support platforms. Whether through DEWA’s smart app, website, social media, Amazon’s Alexa, Google Assistant, robots, or WhatsApp Business, Rammas offers round-the-clock assistance in English and Arabic. Since its launch in the first quarter of 2017, Rammas has addressed over 6.4 million inquiries.
  • Cyber Defense Centre: DEWA’s Cyber Defense Centre employs AI and Big Data to identify potential security threats swiftly and minimize response time to incidents. By leveraging AI, DEWA enhances both customer and employee satisfaction while optimizing system performance.
  • iService: DEWA utilizes AI with its iService innovation to enhance water network efficiency. By analyzing meter diagnostics data, iService detects service interruptions and automatically initiates corrective actions. Additionally, DEWA employs AI for Meter Tampering and Fraud Detection based on smart meter notifications. The Hydronet project further enhances this by remotely monitoring and controlling Dubai’s water network using AI and Deep Learning.

DEWA’s dedication to AI aligns with government strategies and initiatives, including the UAE Artificial Intelligence Strategy 2031 and the Dubai 10X Initiative. The Digital DEWA initiative is revolutionizing the utility concept, leading Dubai into a new digital era. It aims to become the world’s first digital utility employing autonomous systems for renewable energy and storage while also expanding AI and digital services.
For more details, visit DEWA’s official website [here].


Carrefour is rolling out three cutting-edge technological solutions centered around ChatGPT technology: a shopping advisory robot for, descriptive sheets for Carrefour brand products on its website, and assistance for purchasing procedures. These innovations are built upon OpenAI technologies, specifically GPT-4.

Launching on June 8th, Carrefour introduces Hopla, a chatbot powered by ChatGPT integrated into the website. Customers can seamlessly interact with this AI using natural language to aid them in their everyday shopping needs. Positioned on the homepage, users can seek assistance in selecting products for their shopping basket based on their budget, dietary restrictions, or meal inspirations. The robot also offers eco-friendly suggestions for repurposing ingredients and crafting associated recipes and shopping lists. Seamlessly connected to the website’s search engine, Hopla provides customers with curated product lists related to their inquiries, guiding them through the purchasing process.

Additionally, generative AI is utilized to enhance Carrefour brand product descriptions, with over 2000 products already benefiting from this enhancement. This effort, powered by OpenAI technology, aims to provide customers with comprehensive product information, ultimately aspiring to extend this technology across all product description.

Furthermore, Carrefour is integrating generative AI into its internal purchasing procedures, currently under development in collaboration with teams from the non-retail purchasing division. This innovative solution assists in everyday tasks such as drafting tender invitations and analyzing quotations, streamlining internal operations.

“Thanks to our digital and data culture, we have already embarked on the artificial intelligence journey. Generative AI will enrich the customer experience and revolutionize our operational methods. Integrating OpenAI technologies into our operations presents an incredible opportunity for Carrefour. By pioneering generative AI usage, we aim to stay ahead and shape the future of retail.”


AXA, Fraud Risk Management: like any large organization, AXA Sigorta faces the fraud challenge. They employ focused fraud risk program assessments, risk analysis, and advanced analytics to manage fraud risks effectively. By doing so, they ensure that their business operates with confidence.

AI Leadership in a Digital Age

During these digital and AI advancements, leadership takes on a new significance. Leaders must possess not only technological expertise but also the foresight to understand AI’s impact on their businesses and society at large. They must act as agents of change, steering their organizations through the complexities of digital transformation.

These leaders recognize that generative AI adoption isn’t just about embracing new technology—it requires a fundamental shift in how their organizations operate. It involves envisioning a future where AI enhances every aspect of the business, from operations to customer interactions, while staying true to the company’s core values.

To thrive in this digital and AI-driven landscape, leaders must cultivate adaptability, innovation, and ethical awareness within their organizations. These qualities are essential as businesses navigate technological changes and cultural and structural shifts. Leaders must ensure their teams are prepared to embrace these changes effectively.

Leading the Way: Promote AI Practices for Awareness

As AI increasingly integrates into business operations and societal structures, leaders play a key role in promoting ethical AI practices and ensuring technology serves the greater good. Leaders guide their organizations toward responsible, secure, sustainable, and forward-thinking value creation. By setting industry standards, promoting ethical AI practices, and nurturing a skilled workforce ready for the AI revolution, they can ensure their organizations not only succeed but also contribute positively to the broader societal impacts of AI innovation.

Collaborating for a Brighter Future

From reshaping entire industries to addressing pressing global challenges, AI is already tackling some of humanity’s most intricate problems and reshaping the dynamics between humans and technology. Everyone must know what they’re responsible for. As AI changes, so do the teams’ jobs that use it. This includes teams that keep things safe and deal with problems and groups like AI committees and ethics boards, which are becoming more common.

Leaders should prioritize ethical AI. Each individual, company, and region will have their values and standards to guide their approach to ethical AI. The discussion of frameworks, processes, tools, discussion, working groups like CSI, and resources can serve as a foundation for organizations to customize their AI strategies.

Leading the way in responsible AI isn’t just about having good ideas; it’s about making them happen. Leaders must ensure everyone understands generative AI and how it affects the company. It’s not enough to have powerful AI; leaders need to explain how it fits in with the company, what it does, and how they make sure it’s used ethically.

Responsibility with AI goes beyond the rules; it’s about preventing problems and ensuring things work well. This is where AI developers, product managers, rule-followers, and top bosses come in. Each role ensures that AI projects keep improving and are held accountable.

Additionally, we should move faster than we think to lead this movement. Early AI adopters are pivotal in promoting responsible AI use and preparing society for its implications. Their firsthand experiences navigating AI’s ethical challenges will provide invaluable insights for later adopters and those studying or regulating AI.


Maintaining open dialogue among businesses, governments, NGOs, academic researchers, and all interested parties is crucial during this considerable business transformation. By engaging with AI responsibly, we can ensure it fulfills its promise of creating a brighter future for everyone.

Sources: Microsoft, CSA, McKinsey