How AI is slowly changing data governance

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Data governance recently became a vitally important personal and political topic. Security and privacy are at the heart of new regulatory efforts like GDPR in the EU and CCPA in California.

When asked, individuals rank data protections among their top privacy priorities. Companies know the importance of proper data governance, as well. Yet, research suggests their confidence in their own know-how may be overinflated.
The search for better data governance — including data mobility, data accuracy, compliance, cybersecurity and privacy — has led to the application of AI in new processes and a suite of new data handling tools.

Here’s a look at some of them and what they mean for the competitiveness and productivity of the modern enterprise.

1. Brings New Efficiencies to Industry

AI and data governance are a good match for many of the same reasons AI is an emergent trend in every other industry. AI can improve the rate at which:

  • Information is exchanged and verified between departments and partners
  • Process errors are identified, and issues are raised to the appropriate decision-makers
  • "If this, then that" processes are completed
  • Patterns or abnormal events are detected and either capitalized or acted upon
  • Industrial processes are completed with less waste

AI cemented itself as one of the biggest worldwide trends to watch when an eerily humanlike robot won citizenship in Saudi Arabia. Although this article won't touch on the merits of digital personhood, the example illustrates just how consequential AI has already become. AI helps surface and organize the data that companies need in order to optimize their operations and become more competitive.

As far as enterprise efficiency goes, AI has the potential to far outstrip human beings when it comes to identifying problems before they arise and eliminating operational bottlenecks. For example, it will soon be business-as-usual to use AI and smart contracts for delivering notifications and moving processes along.

Partners who want to eliminate friction within a supply chain or another business environment can use AI, blockchain and smart contract technology to do so. Instead of performing manual checks and sending word about completed tasks, AI can monitor business processes between partners, automatically mark portions of a contract fulfilled and signal that the next steps can begin.

2. Aids in the Fight for Tighter Cybersecurity

Data governance and AI are a particularly good fit in the realm of cybersecurity. Criminal elements have ever-more-sophisticated tools at their disposal, including automated cyberattacks such as “credential stuffing” and new techniques to make malware harder to find.
Artificial intelligence is an important ally in keeping organizations’ valuable data safe. It can gather and correlate data from every potential attack vector and throughout the organization’s infrastructure.
Tools like these can spot abnormal patterns and unauthorized network activity much more quickly than a human security team alone. Moreover, after the technology identifies a threat, AI can deliver actionable insights to inform new policies and rules and prevent similar incidents in the future.

3. Allows Chatbots to Become a Data Mobility Tool

Chatbots could save companies in the health care, banking and retail sectors an estimated $11 billion per year by 2023. These savings come from streamlining their customer service departments, as well as from the data mobility that chatbots enable. Chatbots driven by artificial intelligence help data flow to the customer more efficiently. They also help organizations gather data of their own.

Each interaction with customers using chatbots yields information about the client. The technology also gathers and organizes data on common or emerging defects and issues. Each point of data gleaned from a customer-chatbot interaction can help yield further product and service improvements, improve response times and ensure fewer information bottlenecks between organizations and their customers.

In this way, chatbots become a sort of bridge between real-time trends and historical data — one of several important considerations for organizations that want to become data-driven enterprises.

4. Automates Data Discovery, Triage and Organization

As organizations add information to their data lakes and warehouses, they’ll almost inevitably find ways to use that data to trim the fat from their operations, build new campaigns to reach additional markets or improve the productivity of another aspect of their business.

Artificial intelligence is becoming essential for maintaining these databases. As data troves become larger and contain more structured and unstructured information, the parties responsible for data discovery, triage and organizing or repackaging that data will need more help.

That includes professionals like:

  • Data stewards: Those who define data best practices and identify useful data sets
  • Data custodians/engineers: Those who maintain data connections, conduct data and maintain security access
  • Department leaders: Those who act on the gathered data in a business setting

As a data governance and organization tool, AI can be configured in numerous ways to make these processes faster and more effective.

It can perform tasks such as:

  • Identifying the most useful data sets based on user criteria
  • Finding missing values, errors or duplicated content
  • Cleaning up disorganized data sets
  • Repackaging “clean” data into new forms or containers for use elsewhere in the organization or by different parties or apps.

5. Provides a Consistent Approach to Regulatory Compliance

Keeping emerging regulations in mind is a huge part of modern data governance strategies. The EU’s General Data Protection Regulation and the California Consumer Privacy Act have created an inconsistent patchwork of regulatory requirements across the globe. Organizations need a consistent, standardized process for making sure their data infrastructure follows the rules.

Automation can greatly improve the accuracy, regularity and speed with which companies:

  • Discover and flag potentially sensitive data as it arrives
  • Apply encryption automatically to identified high-risk data
  • Properly dispose of non-useful, non-compliant or “expired” data

Under data protection regulations like CCPA and GDPR, customers have a right to see the data collected on them and to request its deletion if they choose. Maintaining personal data on customers, clients and prospects is an important part of doing business. Without automation, however, it will prove increasingly difficult to handle and organize all that data safely and compliantly and make sure it’s accessible, accurate and properly organized for all parties concerned.

AI and Data Governance: A Perfect Match

Artificial intelligence and data governance go hand-in-hand. Handling and analyzing data effectively and safely requires the unbiased, unemotional touch of AI.

Likewise, AI needs access to clean, compliant and actionable data so it can learn and improve. They complement each other perfectly — and thus, organizations of all kinds and sizes have a lot to gain from combining the two.

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