Introduction

As organizations navigate an increasingly data-driven world, the conversation around data protection has evolved. The focus is no longer limited to regulatory compliance; it has expanded to responsible data stewardship in a complex digital environment. Personal data now powers intelligent systems that influence decisions, predict outcomes, and automate critical processes ranging from advanced analytics in healthcare to automated decision-making in financial services.

While these innovations offer clear benefits, they also introduce increasingly complex risks. For organizations, the question is not whether to use data, but how to do so securely, transparently, and in alignment with ethical and legal standards in a rapidly evolving digital landscape.

Emerging challenges 

Artificial intelligence is transforming industries by improving efficiency, accuracy, and scalability. In the financial sector, automated decision-making systems support credit assessments, enhance fraud detection, and streamline customer onboarding. These capabilities enable institutions to operate faster and serve broader populations, supporting innovation and financial inclusion.

However, the same systems also create significant challenges regarding data protection and governance. AI models depend on vast volumes of personal and sensitive data, often processed at a speed and scale that outpaces traditional oversight mechanisms. Risks such as algorithmic bias, limited explainability, and unintended data exposure can undermine individual rights, weaken trust, and expose organizations to regulatory and reputational consequences. Without strong governance, AI systems may perpetuate existing inequalities, make decisions that are difficult to explain or contest, and expose sensitive data through poorly secured models or weak operational controls.

Key risks

Among the most pressing risks facing data-driven systems today are:

  • Data privacy and security risks : Data-driven systems often collect and store large amounts of personal or sensitive information. If this data is not properly protected, it can be stolen, leaked, or misused, leading to financial loss, reputational damage, and legal consequences.
  • Data quality and integrity: The accuracy of AI systems depends on the data they are trained on. If the data is incomplete, outdated, or incorrect, the system can produce unreliable predictions or recommendations, leading to poor decisions and operational risks.
  • Ethical and legal risks: Using data irresponsibly or violating privacy laws can create serious ethical and legal issues. Organizations risk fines, lawsuits, and public backlash if they fail to comply with regulations or ethical standards while deploying intelligent systems.

What organizations must do

To address these challenges, organizations must move from reactive compliance to proactive data protection governance. Key actions include:

  • Conducting Data Protection Impact Assessments (DPIAs): DPIAs should be mandatory for high-risk processing activities, particularly when deploying AI-driven systems, automated decision-making, or large-scale IoT solutions. They help identify risks to individuals early and define appropriate mitigation measures before harm occurs.
  • Design privacy into innovation initiatives: New technologies particularly AI-driven and IoT-enabled solutions should be evaluated through a privacy lens at the concept stage. Privacy requirements should influence system architecture, vendor selection, and data governance models.
  • Strengthening organization culture: Privacy by Design cannot succeed without people. Ongoing training, clear accountability structures, and leadership commitment are essential to embed privacy into everyday decision-making.
  • Adopting recognized frameworks and standards: Recognized standards such as the ISO/IEC 27000 series, including ISO/IEC 27001 and ISO/IEC 27701, provide a practical foundation for managing information security and privacy risks. These frameworks enable consistency, accountability, and auditability across complex environments.
  • Engage stakeholders and build public confidence: Working together with regulators, industry peers, and civil society enables shared learning and supports responsible innovation. Open and ongoing dialogue helps organizations align their data practices with changing societal expectations about how data should be used.

Conclusion

Organizations must recognize that trust is their most valuable digital asset. Investing in strong data protection practices is not just a regulatory obligation, but also a critical strategic priority. Leaders must take action to integrate privacy into innovation, govern emerging technologies responsibly, and follow established frameworks that ensure accountability.

At an individual level, awareness is essential. Understanding personal data rights, questioning how data is used, and practicing basic digital hygiene all contribute to a safer digital environment and unlock sustainable digital growth.

As technology continues to evolve, one principle remains constant: responsible data protection is the foundation of sustainable digital transformation. The choices we make today will define whether innovation empowers society or erodes the trust on which it depends.

Data Protection Day 2026 is more than a celebration; it is a call to action. As we mark this day, let us reaffirm our commitment to a future where technology serves humanity without compromising rights.

The article is by the IT Department which handles IT Audits and Consulting across diverse entities in East Africa.

 

References

  1. ISO/IEC 27001;
  2. Organization for Economic Co-operation and Development;
  3. World Economic Forum;
  4. National Institute of Standards and Technology;
  5. European Union;
  6. European Union Agency for Cybersecurity (ENISA); and
  7. World Health Organization.
     

Caveat

This newsletter has been prepared by RSM (Eastern Africa) Consulting Ltd, and the views are those of the firm, independent of its directors, employees and associates. This newsletter is for general guidance, and does not constitute professional advice. Accordingly, RSM (Eastern Africa) Consulting Ltd, its directors, employees, associates and its agents accept no liability for the consequences of anyone acting, or refraining from acting, in reliance on the information contained herein or for any decision based on it. No part of the newsletter may be reproduced or published without prior written consent. RSM (Eastern Africa) Consulting Ltd is a member firm of RSM, a worldwide network of accounting and consulting firms. RSM does not offer professional services in its own name and each member firm of RSM is a legally separate and independent national firm.