The importance of governance to data and AI success – an interview with Chafika Chettaoui, AXA

Successful AI has to be built on strong foundations, particularly high-quality data and strong governance and ethics. Simply launching AI projects without these underpinnings risks underperformance and expensive failures. However, governance programs can fail to engage the business, who see them as bureaucratic rather than strategic.

Broadening the understanding of governance is central to scaling data and AI use across the business, making it a key objective for Chief Data Officers (CDOs) and Chief Data & AI Officers (CDAIOs). To share best practice across this and other topics, Huwise’s global Data Voices community has been created to bring together data leaders and provide inspiration to accelerate data strategies.

As part of this, the community has launched the Data Voices Manifesto. This in-depth study looks at the current state of data sharing and provides perspectives from data leaders on how to transform data management by 2030.

In the final interview taken from the manifesto we talked to Chafika Chettaoui, Chief Data & AI Transformation Officer from insurer AXA France. She explained how the global insurer is embedding governance and ethics across the organization. 

Chafika Chettaoui is a leading figure in driving organizational transformation through data and artificial intelligence. Currently Chief Data & AI Transformation Officer at AXA France, she oversees the company’s data & AI strategy and leads a large-scale transformation program that leverages data and AI to enhance technical, operational, and commercial excellence, as well as customer satisfaction, key pillars of the company’s strategic plan.

With a PhD in Mathematics and Computer Science, she began her career in consulting, supporting major companies in banking, insurance, retail, and pharmaceuticals on data governance and data science initiatives.

In 2010, she joined L’Oréal, where she built the data strategy and organization for the Research & Innovation department. She implemented an innovation- and change-management–driven methodology that promoted the adoption of new analytics practices among researchers and evaluators, reducing quality test time-to-market, increasing operational efficiency, and securing decision-making processes.

In 2017, she led the Analytics team at Teradata France, a global leader in analytics solutions, supporting large companies in their digital transformation. In 2018, she founded the Data Office and became Group Chief Data Officer at SUEZ, where she accelerated the use of data and AI to enhance industrial performance, reduce environmental impact, and improve the profitability of public services.

An active contributor to the data ecosystem, Chafika regularly publishes and speaks on topics related to organizational transformation through data and AI, including data governance, and the cultural and organizational change necessary for a successful data & AI strategy, and its resulting business impact.

“The value of the CDO comes from their ability to transform the organization. Data and AI, like digitalization before them, are not merely technological tools but drivers of business and human transformation. The CDO role, as it is often seen today, can sometimes be limited to a purely technical function—responsible for building the foundations needed to address AI challenges. Without a transformation mandate, it becomes “technology for technology’s sake,” which is exactly what has led many organizations to remain stuck at the Proof of Concept stage, without adoption or real impact. I believe that this role must naturally evolve into that of Chief Data & AI Transformation Officer (CDAITO). This position carries a mandate that goes beyond delivery and includes three additional dimensions: strategic vision aligned with business priorities, organizational transformation (operating models and ways of working), and cultural change to support adoption while ensuring strong foundations.

In the coming years, as AI becomes a commodity embedded within business functions, the CDAITO will naturally evolve into the role of Chief Transformation Officer, a job that is sustainable regardless of the technology trend it must address: yesterday digital, today AI, tomorrow…whatever the market brings. This is also what makes the Chief Transformation Officer role both complex and demanding: anticipating change and continuously preparing the organization to adapt, in order to extract maximum value. In other words, the same ingredients, a different recipe.”

“If the term “governance” still generates resistance, it is because it remains associated with a

bureaucratic mindset that discourages operational teams. Instead, focusing on Business Data Ownership changes the perspective by putting responsibility back where value is actually created.

I often use the metaphor of a tidy room: to live and thrive comfortably in a space, it must be organized. This is not an unnecessary burden but essential for providing order to improve efficiency, clarity, and ultimately create sustainable value.

Governance is precisely this invisible organization. The semantic shift toward Business Data Ownership is not just a slogan. It highlights the importance of business engagement in improving data quality, since business teams understand their own data and local priorities best.

Like any major transformation, this change requires executive-level sponsorship that is capable of reconciling strategic vision with operational reality, alongside strong centralized orchestration in order to create the controlled governance framework necessary for optimal data usage.”

“At AXA France, the “governed decentralization” model launched nearly three years ago is built on three complementary pillars. The first is organizational. It relies on a Data & AI Office responsible for AI strategy and governance frameworks, with connections to every business unit through Data & AI Leaders who are positioned one level below the executive committee. This creates strong sponsorship and anchors transformation close to business operations while maintaining a shared strategic direction.

The second pillar is technological. Governance is not carried out through documents but through tools,f DataOps and observability capabilities that monitor quality in real time. If quality drifts, AI drifts as well.

Finally, there is culture. Responsibility for data cannot rest solely with an expert team; it must be shared across everyone who produces, uses, or consumes data. This awareness and discipline require long-term support through culture change, training, and change management initiatives.

Together, these three pillars form an inseparable foundation. It is this continuous investment in the fundamentals that enables organizations to move from isolated Proof of Concepts to truly scalable AI deployments, turning AI from a promise into a long-term competitive advantage.”

“We must move beyond the illusion created by impressive demonstrations that never become operationally viable. “AI for AI’s sake” is a pointless and counterproductive race. Scaling AI first requires aligning priorities with the company’s strategic vision and carefully selecting a limited number of use cases that genuinely impact profit & loss, customer satisfaction, and operational efficiency.

Moreover, delivering a solution only provides benefits if users truly adopt it. This means breaking down silos between business and tech teams to create the right solutions by design, while also investing heavily in training and continuous change management.

Finally, there is no long-term AI without responsible AI. Ethics can no longer be treated as a checkbox exercise. Building trust is not secondary. It is central to our business, and it requires us to ensure that AI is designed and used neither incorrectly nor too late.

This search for balance between business, human, ethical, environmental, technological, and societal dimensions is what will differentiate successful organizations in the years ahead.”

“At AXA France, we strongly believe innovation and responsibility must go hand in hand. We have an innovation hub that enables us to adopt a test & learn approach and remain agile when responding to AI evolution. However, we only scale use cases that are validated by a decision-making body operating at executive committee level.

This commitment to responsibility is also reflected internally in how transformation is managed. We quickly established an open and regular social dialogue with employee representative bodies to transparently share our progress, and this has since been formalized through an agreement covering all AXA entities in France.

We apply the same transparency toward customers and the public. We have therefore formalized our commitments in a responsible AI charter shared with other Group entities and publicly available on our corporate website.”

“The priority for the future is to truly deliver on transformation. This means moving beyond announcements and impressive demos that excite the market but risk confusing speed with haste. The challenge is to master the agentic AI wave by focusing on key areas which are capable of deeply transforming the insurance value chain, while maintaining trust.

Trust in data quality and its use, including by agents that go beyond our information systems; trust from employees in tools that transform their daily work and whose adoption is critical to success; trust from business teams, who must be able to deploy AI with greater independence within a controlled framework; and, of course, trust from customers in our responsible use of AI to improve their experience and satisfaction levels.

This transformation is grounded in robust governance and deeply embedded values: we do not pursue AI at any cost; we assess its impact and weigh it against our commitments across business, human, and environmental dimensions, formalized in our company-wide charter.

Ultimately, three imperatives must be combined: measurable operational impact, sustainable human transformation, and non-negotiable ethical responsibility.”

Want to learn more? Read our interviews with:

• Camille Maire of lingerie and fashion retailer ETAM 
• Samia Boujatioui of insurer Coface Group
• Michel Lutz of oil & gas major TotalEnergies 

Alternatively download the full Data Voices Manifesto to find more expert predictions on the future of data.