In a world dominated by Machine Learning and AI, data privacy must catch up

Today, data privacy is a space that’s long on rules, but short on tools. First-generation approaches followed a ‘paint by numbers’ approach: checklists, organizational readiness, quick identification of privacy gaps and compliance risks. They were static, what-you-should-do approaches — necessary, but incremental. Every company that adopted them soon realized how much work remains to operationalize their privacy initiatives in a cost-effective, policy-driven manner.

As companies cry out for tools to conquer the complexities that come with privacy and to eliminate spiraling compliance costs, new mindsets and methods for data privacy and governance are responding to the call. These innovations hold the promise of making privacy programmatic and scalable.

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The longer companies wait to employ automation for data privacy, the greater the risk for reputational damage, and erosion in profit margins due to ever-increasing complexity. Complexity in the constant flickering of the regulatory regime; technical challenges inherent in recognizing and resolving digital identities; and by the proliferation of systems that need to honor consumers’ privacy instructions. A manual, burdensome approach to compliance limits companies to one of two options: dismiss privacy requirements and use personal data to grow, or comply and stagnate. .

There’s a better way.

Business leaders are embracing automation in data privacy, and committed to the systemic pursuit of compliance and growth — recognizing the risks of non-compliance, and the opportunities that come from cultivating privacy and greater trust with stakeholders, and the strategic imperative to participate fully in the data AI revolution.

Automating Compliance Significantly Reduces Costs in the Sprawling Environment of Global Data Regulations and Data Systems

 The European General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) are the two significant regulations shaping the regulatory environment, but there are more than 80 different data privacy laws that impact businesses every day.

Data and privacy compliance are already difficult to operationalize through manual approaches for one set of regulations like the GDPR; it is nearly impossible to do so with the global entanglement of different standards, and the multiplicity of systems across which privacy must be respected. As a result, the costs for companies for implementing and orchestrating privacy are spiraling.

The fastest way to address and significantly reduce these costs is through end-to-end automation via robust data management and control — most importantly, in automating the actual privacy task i.e. the data deletion in a data subject rights request, or the updating of consent across systems where personal data resides. In most instances, consent management vendors are approaching the challenge by only automating the workflow, which does not solve this problem because it just results in pushing emails around instead of a sustained solution. By automating both the privacy task and the associated workflow, with the necessary approvals and checks and balances, the labor required to address compliance is removed, freeing up a team’s time to focus on other essential, more productive tasks.

A key challenge in end-to-end automation is to solve for a communication, or “Tower of Babel” problem — as most service providers don’t reliably ‘speak privacy.’ This means that a privacy translation layer is vital to the communication and enforcement of privacy instructions across systems

‘Deploy-Once, Comply-Everywhere’ Responsive Data Infrastructure is Key to Future Proofing Against a Dynamic Regulatory Framework

Just as we have failed to develop coherent, unified regulations regarding climate change, migration, trade, and many other dynamic, cross-border phenomena, it is unlikely privacy regulations will converge into a unified, global standard. Instead of betting on a single global standard, a more pragmatic path is to create responsive infrastructure that assembles the building blocks of modern privacy, and connects them to a system of record for permits, at a granular data level — to insulate businesses from the slings and arrows of a constantly flickering global privacy regime.

The building blocks of modern privacy applied to granular data sets provide the flexibility and adaptability to respond to new and shifting global regulations:

• Individuals about whom you hold data — who is it about
• Categories or attributes of the data — what is it
• Uses, or purposes of data processing — how can you use it
• Legal basis for processing, by jurisdiction — why you can use it based on where the individual is located

The system of record for permits then communicates with all the data systems that are required to respect those signals, both internal and external e.g., website infrastructure, and vendor systems.

As the regulatory climate continues to fragment, we cannot afford to maintain ad-hoc compliance programs as each regulation and its interpretation evolve. Playing whac-a-mole is not a viable or durable strategy for data privacy.

It’s critical that compliance tools provide the flexibility to respond to new and changing regulations, the granularity to build tailored privacy programs across multiple regions, and the connectivity to data systems that ensures policy stances are realized and enacted, rather than lying inert in a document or privacy policy somewhere

By adopting ‘Deploy-Once, Comply-Everywhere’ responsive infrastructure , organizations can comply today, and maximize efficiencies with a system that updates with a few simple tweaks rather than chasing each new or changing regulation with engineering resources.

Automated Privacy Orchestration

To realize true privacy — not just the Hollywood façade of privacy, businesses must ensure that this customer’s privacy commitments in this jurisdiction are honored not just in this one company’s system, but in every system with which its systems interact. If a business collects personal data, it has the responsibility to ensure that its customer’s data dignity is respected not just within their four walls, but in the data systems of their service providers and partners as well.

Automated enforcement of consent in downstream systems is an opportunity to improve trust with customers. It’s aligned with the broad planetary tilt towards data rights and data dignity which is increasingly making its way into consumer buying decisions.

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Centrally controlled, policy-managed processing across data systems governing the collection, storage, access, and use of data across the organization has the added benefit of getting the right data to the right teams seamlessly Business leaders can sleep soundly with the confidence that access, permissions, and privileges for data are correct, enforced, and auditable. Data is utilized based on access policy, responsible sourcing of data (with consent), for and defined data purposes.

As data privacy laws continue to grow and change; and as technology continues to advance with new systems to control, new protocols to observe, and new technical flanks to close — the role of flexible and programmatic privacy solutions will continue to rise. The solution to this complexity is simple, automation. Not only does creating an automated and responsive regulatory response allow a company to take the most efficient posture towards data collection and compliance in real-time, but also cultivates trust with customers, by ensuring their privacy choices are respected across every interaction and jurisdiction.