4 prerequisites for IT leaders to navigate today’s era of disruption

Deep understanding of how to monetize data assets

IT leaders aren’t just tech wizards, but savvy data merchants. Imagine yourself as a store owner, but instead of shelves stocked with physical goods, your inventory consists of valuable data, insights, and AI/ML products. To succeed, they need to make their data products appealing by understanding customer needs, ensuring products are current, of a high-quality, and organized. Offering value-added services on top of data, like analysis and consulting, can further enhance the appeal. By adopting this mindset and applying business principles, IT leaders can unlock new revenue streams.

Focus on data governance and ethics

With AI becoming more pervasive, the ethical and responsible use of it is paramount. Leaders must ensure that data governance policies are in place to mitigate risks of bias or discrimination, especially when AI models are trained on biased datasets. Transparency is key in AI, as it builds trust and empowers stakeholders to understand and challenge AI-generated insights. By building a program on the existing foundation of culture, structure, and governance, IT leaders can navigate the complexities of AI while upholding ethical standards and fostering innovation.

Ability to embrace both smarts and heart

IT leaders need to maintain a balance of intellectual (IQ) and emotional (EQ) intelligence to manage an AI-infused workplace. On the IQ side, leaders need to have a vision for the AI-first world in their organizations and know where it can be used to free up employees so they can spend more time on other complex tasks and enhance productivity. But more importantly, EQ and people-centric skills are critical to evangelize positive impacts, keep people engaged, address anxiety around the changing workforce, and help people reskill to focus on new ways of working and thinking. In fact, with advanced analytics producing vast amounts of data beyond comprehension, softer management skills will be more important than deep subject expertise or raw intelligence.