Integrity by design: Building future-proof compliance practices for proactive regulatory readiness
In today’s rapidly evolving regulatory landscape, maintaining integrity is no longer just a legal requirement but a strategic imperative for very large online platforms (VLOPs) and has become good business for any and all data processing enterprises. As organizations expand globally in a data-driven economy, they must prioritize integrity at every level of their operations to build trust, ensure compliance, and secure sustainable growth.
The challenge for global operators is clear: how to remain agile and innovative while adhering to a complex web of global regulations. The answer lies in embracing “integrity by design” — a proactive approach that ensures ethical considerations are woven into the fabric of every decision, product, and process. This is not just about avoiding fines or legal trouble; it’s about building a resilient organization that can thrive in an increasingly regulated and scrutinizing world.
With the EU’s Artificial Intelligence Act on the horizon and the continuous evolution of data privacy laws like Brazil’s General Data Protection Law (LGPD), the infamous General Data Protection Regulation (GDPR), and California’s Consumer Privacy Act (CCPA) and Privacy Rights Act (CPRA), enterprises must recognize that integrity isn’t optional — it’s a business imperative. Those that fail to prioritize integrity risk losing the trust of their users, facing severe regulatory penalties, and ultimately, compromising their long-term viability.
Agile integrity
Adaptability and agility are crucial in a constantly shifting regulatory landscape, where the concepts of integrity, responsibility, and ethics can often be ambiguous for globally operating enterprises. Organizations that can quickly respond to changes in operating regions, offerings, and the rapidly evolving global legislative landscape will gain a competitive advantage in governance, risk, and compliance operations. This can lead to improved posture management, enhanced consumer relationships, and improved social trust.
Agility is a business-critical competency, but it should not compromise core values, consumer commitments, or compliance posture. Integrity ensures that adaptability is rooted in ethical practices.
Integrity has become a dynamic concept in global compliance and can change across business functions, frameworks, and regulations. The GDPR and the CCPA liken integrity to strong information security and data management practices, whereas Sarbanes-Oxley calls for honesty, accuracy, and reliability in financial reporting. The EU AI Act identifies integrity as an ethical responsibility within AI development. The International Organization for Standardization ironically has over a dozen uses for integrity, from anti-bribery management systems to zero-trust segmentation. The Oxford Advanced American Dictionary defines integrity as:
- The quality of being honest and having strong moral principles
- The state of being whole and undivided
The point here is that integrity is the thread that weaves together regulatory compliance, ethical behavior, and trust, ensuring organizations not only meet legal standards but also contribute positively to society.
Consider Meta’s current approach to embedding integrity in the product development process. Historically, Meta addressed challenges such as misinformation and privacy concerns reactively, but soon recognized the need for a more proactive and agile approach. As a result, Meta restructured its development teams to embed specialists focused on safety and security within product teams at the earliest stages of product development and maintained those specialists even after products came to market. Meta’s agility in evolving its development practices while upholding a strong commitment to integrity has resulted in a safer, more trustworthy platform.
The inevitable harmonization of the global regulatory landscape
In the modern global data marketplace, where digital platforms operate seamlessly across borders, the ability to harmonize compliance efforts globally is no longer a future-state nice-to-have. Regulatory trends show that countries are exercising extraterritorial authority to enforce their requirements for enterprises that serve their citizens from anywhere in the world. Countries are increasingly adopting strict, strongly enforced data protection laws, data subject rights, and reporting requirements — many closely aligned with the standards in the GDPR. As new regulations like the Digital Services Act (DSA) and Digital Markets Act (DMA) begin to target VLOPs—and eventually everyone—harmonizing compliance across these diverse regions and regulations not only simplifies operations but also reinforces a unified integrity standard.
The rise of comprehensive data protection laws across US states and operating regions highlights the shortcomings of a fragmented approach to compliance; it is expensive, ineffective, and unsustainable.
Bringing it all together: Unifying compliance operations
Developing a global compliance framework that adopts the highest standards from each jurisdiction as a baseline ensures that compliance efforts are consistent and comprehensive, as well as future-proof and flexible. Implementing an innovative multi-jurisdictional compliance audit practice that examines compliance efforts across all operating regions allows the organization to actually improve its compliance posture by identifying gaps where local practices diverge from global standards, streamlines corrective actions processes, and ensures integrity is maintained globally.
The core principles of “integrity by design”
Ethical governance frameworks
Ethical governance frameworks are the backbone of organizational integrity. As technology continues to rapidly evolve, these frameworks must remain flexible enough to adapt alongside the shifting legal landscape and respond to the challenges posed by advancing technological capabilities — particularly those involving AI, data processing, and deep analytics. Integrity demands not only a commitment to meeting existing regulatory requirements but also anticipating future challenges.
The EU AI Act’s emphasis on governance structures is intended to force accountability and transparency, signaling a shift in regulatory expectations. Organizations must demonstrate that governance is not just performative but actually safeguards the integrity of platforms, products, and processes. Forming dedicated integrity committees that bring leaders from legal, compliance, operations, people, products, and technology together to embed ethical considerations into every business action is the first step in future-proofing the modern enterprise.
Bias mitigation across all channels
Bias in data processing, including AI systems, poses a significant risk to fairness, regulatory compliance, and integrity at large. The EU AI Act’s focus on bias mitigation and ongoing improvement operations highlights the first wave of the organizational need to regularly audit AI models, data processing outcomes, and applied intelligence to identify and correct perceived and shadow biases that lead to unfair, unethical outcomes. The concept of anti-bias in AI systems has been around for over a decade, with Amazon providing a notable case study in 2014 when their AI résumé screener displayed significant bias against women applicants. Recognizing the bias, Amazon decided to discontinue the use of the tool, even though the system was never actually used to make hiring decisions. The broader discussions within Amazon and the tech industry at large brought the importance of diverse training data in AI systems front and center and established a standard expectation of continuous monitoring and improvement as part of the AI system lifecycle.
To effectively address bias, organizations must invest in developing AI ethics charters that outline commitments to fairness, transparency, and accountability. Rigorous, reliable AI ethics reviews should be conducted to ensure that these principles are upheld, particularly as new data is introduced and models are updated.
Established accountability
In an environment where data warehousing provides opportunities for deep analysis, automated decision-making, and data subject profiling, accountability is crucial. High-risk AI systems require human oversight, clear lines of responsibility, and defined processes at every stage of the data’s lifecycle. Organizations must ensure that when business-critical systems, including AI, fail, a structured response plan is in place to prioritize ethical remediation and data protection contingencies.
Building an accountability competency involves more than just assigning blame when things go wrong. In this context, integrity requires the development of ethical decision-making protocols that guide AI deployment, data use, and intelligence aggregation, ensuring integrity is uphelp amid rapid innovation. These protocols should include expansive, intentionally wide feedback nets where decisions are reviewed and corrective actions are taken in near real time.
Consistently reliable data
The quality of analytics outputs, AI decisioning, and practical intelligence is only as good as the data used to generate them. Ensuring data integrity is therefore a critical aspect of “integrity by design.” High-risk AI systems must be training on high-quality, representative datasets that are free from error and biases.
Organizations, especially VLOPs, should adopt comprehensive data governance practices that include regular data audits, validation processes, and strict access controls to not only protect data from unauthorized access but also ensure it remains accurate, reliable, clean, and usable throughout the AI lifecycle.
Proactive privacy and security operations
As organizations improve in both efficacy and efficiency, it is crucial to recognize the speed at which data protection practices reach obsolescence in an evolving threat landscape. The data-driven economy means that the value of an organization’s data reacts to the perceived security and market availability of that data. Breach events can push the value of high-risk datasets into the hundreds of millions of dollars on the black market and then reduce it to a liability for breached organizations responding to regulatory interruptions and punitive actions. Consumer opinions on breached brands have seen a steady decline as public awareness of both breach events and hostile actor exploitation continue to be part of our cultural zeitgeist. Using Meta as an example, consider the exceptionally forward thinking behind privacy red-teaming and other innovative security practices integrated with governance and compliance operations as a market-trust differentiator.
Modern data privacy regulations have made consent the cornerstone of compliant data processing operations. Organizations must therefore ensure that their consent and preference management operations enable data subjects to make enthusiastic, informed decisions. This includes clearly defining data collection practices, purposes, and protection practices that inform data subjects in appropriate detail on what information is collected, how it’s used, and how it will eventually be destroyed.
Transparency and explainability
Transparency is key to building trust in all capacities. High-risk AI systems, high-risk data collection and processing, and high-risk environment safeguarding require not only detailed documentation practices but also the ability to explain those practices in a way that is understandable to users, data customers, and regulators. This is particularly critical for VLOPs, ecommerce platforms, and gatekeeping services where AI-driven decisions can affect the lives of individual data subjects.
Transparency must extend beyond regulatory compliance by including clear communication with users, stakeholders, partners, and customers about how data is used, processed, and protected. Organizations should implement transparency dashboards that provide real-time data on processing operations, AI activities, and improvement plans that enable data customers and regulators alike to understand data processing outcomes, AI decisions, and the activities that result in desired and undesired outcomes.
Becoming future-proof: Proactive regulatory readiness
As we look toward the regulatory horizon, one truth becomes abundantly clear: the organizations that will thrive are those that don’t merely react to regulatory changes but actively anticipate and prepare for them, with integrity at their core. For VLOPs, and other heavily regulated organizations, this means adopting proactive measures that not only align with current regulatory requirements but also position these orgs to lead in a future where ethical governance is nonnegotiable.
The future of regulatory compliance is one where governance frameworks are more than structural necessities — they serve as the ethical compass of an organization. Regulators are increasingly scrutinizing the governance structures of VLOPs, demanding that they not only exist but also actively ensure accountability, transparency, and ethical decision-making at every level.
The rise of comprehensive data protection laws put fragmented governance practices at risk. Harmonization allows organizations to create a corporate culture of compliance that upholds integrity regardless of geographical location.
As data-driven organizations face increasingly sophisticated digital threats, the need for robust risk management and incident response strategies is paramount. Regulatory trends are moving toward requiring organizations to demonstrate not only their ability to manage risks but also their capacity to respond to incidents in a way that prioritizes transparency and rapid, ethical remediation.
Ensuring integrity-driven compliance
To truly future-proof your organization and lead with integrity, it’s crucial to take proactive measures that go beyond simply reacting to regulatory changes. Here are three foundational steps to starting the “integrity by design” journey:
- Establish cross-functional integrity committees
- Form dedicated committees that bring together leaders from legal, compliance, operations, product development, human resource management, and technology teams. These committees will be responsible for embedding ethical considerations into every business decision.
- Assign committee members with clear roles and responsibilities.
- Hold regular meetings to review major initiatives, ensuring they align with the organization’s integrity principles.
- Implement decision-making protocols that require ethical review for all high-impact projects, particularly those involving AI and data handling.
2. Conduct annual multi-jurisdictional compliance audits
- Implement a comprehensive audit schedule that examines your compliance efforts across all regions where your organization operates. The focus should be on identifying discrepancies between local practices and global standards, ensuring that your organization upholds a unified integrity-driven approach.
- Develop an audit framework that adapts to the specific requirements of each jurisdiction.
- Engage third-party auditors to provide an objective assessment of your compliance posture.
- Use audit findings to drive corrective actions that close gaps, harmonize practices, and enhance global compliance.
3. Develop a dynamic compliance playbook
- Create a living document that outlines your organization’s compliance strategies, ethical guidelines, and operational procedures. This playbook should be updated regularly to reflect evolving regulations and emerging best practices.
- Include sections on data governance, AI ethics, incident response, and stakeholder communication.
- Set up a review cycle to ensure the playbook remains relevant and aligned with new regulatory developments.
- Distribute the playbook organization-wide and conduct training sessions to ensure all employees are familiar with its contents and their roles.
To thrive in an increasingly regulated world, organizations must embed integrity into their core strategies. By adopting “integrity by design” methodologies, organizations can proactively address regulatory challenges, build trust with consumers, and secure long-term compliance posture management. As data-driven organizations continue to expand their reach and influence, the need for integrity at the core of their operations has become increasingly apparent. Today’s consumers are more informed and discerning than ever before, and they expect the platforms they use to operate with the highest ethical standards. Meanwhile, regulators across the globe are tightening their grip, demanding that data controllers not only comply with local laws but also lead by example in areas like data protection, AI ethics, and content moderation.
Bryan Kissel is a senior principal and global expert on data responsibility and privacy at Slalom.
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