As a modern CTO, it should probably come as no big surprise that I’m an optimist on the innovative prospects of artificial intelligence (AI). But I’ve been in this career for a long time, and that optimism is tempered with experience. I’ve seen enough emerging technology patterns to know that it always takes a lot more time and resources than people think to evolve innovative technologies beyond their final barriers.

As businesses increasingly turn to artificial intelligence (AI) to enhance innovation and operational efficiency, the need for ethical and safe implementation becomes more crucial than ever. While AI offers immense potential, it also introduces risks related to privacy, bias, and security, prompting organizations to seek robust frameworks to manage these concerns.

While artificial intelligence and big data steal the spotlight, a less glamorous but equally crucial discipline is quietly shaping the future of business: data governance. With European regulators imposing fines of up to 17.29 million pounds for data mismanagement, it’s clear that data governance is not just a compliance checkbox. It’s a strategic investment that can empower your organization with a tangible return on investment.

This article explains what IGA is and the benefits it offers. It also clears up some misconceptions about IGA and offers guidance about what to look for when assessing candidate IGA solutions.

Is your company grappling with an increasing volume and complexity of information? A strong data governance framework is essential to harness the power of data while lessening risks. This strategic framework ensures data is managed effectively, meets quality standards, and supports informed decision-making, quality standards, and supporting informed decisions. As regulatory compliance burdens intensify, data governance has become critical to organizational success.

As noted in the 2024 Gartner Market Guide for API Protection“API security governance is an emerging capability. It allows the administrator of the tool to define and enforce security policies. Unlike posture management, this is a top-down enforcement. It also allows for compliance reports for specific regulations to be generated automatically.” This capability is becoming increasingly important as organizations face a constantly evolving threat landscape.

In the modern workplace, GenAI models have become powerful assets due to their ability to introduce efficiency, up level product innovation, and expedite how teams close the gap on competitors. However, these powerful tools also introduce significant risks related to data security and governance. Companies that aren’t actively figuring out how to govern the GenAI they’ve adopted will inevitably be left vulnerable.

Effective data governance has become a cornerstone of success in today's rapidly evolving life sciences landscape. From ensuring regulatory compliance to enabling secure collaboration, a robust data governance strategy is essential. ‍

Data has become the lifeblood of modern businesses, influencing important business decisions and powering digital transformation initiatives. As more data comes in and new sources appear, it’s important to manage this valuable asset effectively. Here is where a strong data governance system comes into play.