Council Post: Why Governance Must Evolve From Compliance To Continuous Intelligence
Ramachander Rao Thallada is a Governance, Risk, and Compliance (GRC) Executive for Manulife, a modern North American financial institution.gettyTechnology has advanced by leaps and bounds with the arrival of AI...
Ramachander Rao Thallada is a Governance, Risk, and Compliance (GRC) Executive for Manulife, a modern North American financial institution.
getty
Technology has advanced by leaps and bounds with the arrival of AI through intelligent automation, cloud-native capabilities, predictive analysis, digital twins and autonomous decision-making.
Governance, unfortunately, has lagged behind these developments.
Many organizations still use governance frameworks based on audits, reviews, policies and reporting that look at past compliance efforts. While these methods remain relevant, they were designed for an environment where systems evolved less rapidly.
The increasing discrepancy between technology advancements and governance methods is now a major threat to many organizations. Given the speed of AI transformation, governance can no longer be factored in after technology implementation or incidents. Instead, governance must become a capability that evolves alongside business practices.
To achieve this, technology leaders must move from asking whether their organizations comply with regulations at a particular moment to asking whether systems can continuously maintain accountability, transparency, resilience and responsible decision-making.
The Challenges Of Delayed Governance
In my experience working on enterprise technology programs, most governance processes are still based on manual approvals, audits and evaluations of documents weeks or even months after the changes have been introduced.
During one project, for example, developers deployed application changes several times per week, while the company was collecting information about compliance manually in the end of each release process. By the time the governance team evaluated everything, the technology environment had changed significantly.
In other organizations implementing AI-powered operational platforms, business managers thought that their intelligent systems would help in making fast decisions, but the governance teams did not have real-time insight into the way those decisions were being made or if the operational controls were functioning as planned. This inconsistency led to a growing uncertainty about issues of accountability and operational risk.
What Continuous Governance Entails
The digital transformation projects I've seen succeed over the past few years have treated governance as an ongoing process that is facilitated by monitoring, visibility, automation and enhanced cooperation among business, technology and risk stakeholders.
There are currently several strategies that can support the type of real-time visibility that organizations need to achieve governance that evolves alongside operations.
Technology will play a role. For instance, digital twins can help ensure continuous visibility of operations, decision-making and human intervention, as noted in recent research examining smart manufacturing by mechanical engineer Venkata Naga Kishore Thota.
Likewise, existing frameworks also still have a place in new governance models. DevOps strategies can help ensure that governance, observability and compliance reporting become integral parts of operations rather than separate processes done after deployment, as 2024 research published by business analyst Vimal Teja Manne and DevOps expert Sudhakavya Bodapati Venkata shows.
Beyond technology and specific frameworks, however, this is mainly a leadership challenge. Any future governance efforts cannot be simply evaluated on the basis of whether the audits or compliance tests have been passed or not. Instead, leaders need to take into account how governance helps improve operational efficiency.
Achieving this may include measuring how fast the risks get identified and addressed, the percentage of automated compliance evidence that gets collected during business operations, the transparency of AI-assisted decisions and the effectiveness of controls.
The Future Of Governance
Companies that embed governance in intelligent technologies will have a much better chance of innovating while meeting the needs of regulators, customers, investors and partners.
However, continuous intelligence does not diminish the significance of human judgment.
AI can perform the analysis of vast amounts of operational data and suggest actions incredibly quickly. Nevertheless, ethical considerations, business priorities, the willingness to take risks and corporate responsibility are still human-centered concerns.
Technology will keep moving forward much more quickly than traditional governance structures can keep up. The task of governance, therefore, changes from managing the technology itself to facilitating responsible cooperation of AI and people.
Companies that stick exclusively to periodic reviews for compliance risks are running into trouble as the digital world continues to become more fluid. Companies that can harness continuous intelligence, which uses AI, visibility into operations, human knowledge and built-in governance will find it easier to survive in a changing world.
In the future, being competitive won’t just mean innovating at a faster pace but also being able to continually show why innovation is trustworthy.
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