According to DIligent’s GC Risk Index, organisations are feeling more confident tackling the AI governance challenges of today. In fact, when Diligent asked legal teams what key areas of risk they felt needed attention right now, a mere 8% answered technological disruption, showing that blind spots are already happening.
As Dottie Schindlinger, the Executive Director at Diligent Institute, notes, “This calm was a little surprising to me, given the current frenzy to integrate AI and see results as soon as possible.”
When technology is unprecedented, it makes things difficult for all governance professionals, including company secretaries, compliance officers, risk managers, advisors, and leadership. Why? Because these professionals are on the frontline of AI governance challenges, they must ensure that AI is implemented successfully while keeping ethics and compliance in check.
How to Overcome AI Governance Challenges
If this sounds familiar, we’re here to help. Looking at the AI governance challenges of today, Diligent hosted a recent podcast episode with Beena Ammanath, the Global Head of the Deloitte AI Institute and an expert on navigating tech disruption. Taking the knowledge from two of her books in this area, she gave some salient advice – and we’ve summarised it right here, in 3 realistic tips for overcoming AI governance challenges.
1. Overcoming workplace disruption
Most governance and legal professionals follow an established career path, including education, followed by a lot of time making and checking endless documents.
But now AI has automated the whole process, transforming the team’s workload and profession’s overall pipeline and career trajectory. It leaves these team members understandably worried, especially when they hear promises that AI will take away the boring parts of their work and make their jobs easier. For example, a company secretary may find themselves contending with AI meeting minutes makers or AI board pack builders, leaving them wondering if AI may eclipse their important role altogether. But this doesn’t have to be the case.
“Leaders have a responsibility to go beyond the clichés,” Ammanath said. “What happens to the workday when organisations make the job easier? If AI is going to create new jobs, what are those roles?”
Building on Ammanath’s point, governance professionals, like company secretaries, who are worried about AI may find themselves needing to assist leadership with navigating this disruption by becoming strategic advisors. AI doing the mundane tasks means that these professionals will be free to embody such a role with more ease.
2. Finding the ideal division of labour
Then there’s the matter of the human/machine relationship. “How can leaders thrive and succeed in this era of AI where humans and machines are working so closely together?” Ammanath asked. “To work in the best possible way, where can we get the maximum benefit with the minimum side effects?”
We’ve all seen cautionary tales about students outsourcing the entirety of their coursework to ChatGPT. This should go without saying but: Don’t do that in your organisation.
In the podcast, Dottie and her cohost, Meghan Day, referenced studies of what people’s brain waves look like when they use AI at different levels. The heaviest AI use showed the lowest brain function, almost like people were asleep. More optimal EKG activity happened when AI users started a task with their brains and then added ChatGPT.
“Personally, I’ve been most successful embracing AI in my job in areas where I already know what good looks like,” Day said. “And AI is able to speed my work along.”
AI also promises big potential for board members. You can train different agents to have different personalities and perspectives so they can frame problems in new ways for you, for example. But you’ll still need to oversee them and evaluate their output with your own human expertise to ensure accuracy and nuance.
3. Make continuous education a cultural norm
Navigating AI’s risks and rewards requires knowledge of AI itself – at every level of governance.
This doesn’t mean dropping everything to become an AI expert (although those nine-figure job offers make it tempting). It means having a basic understanding of core AI principles, like machine learning, deep learning and computer vision, and what these principles look like in action.
“It’s important to focus the time and energy to not only learn about AI, but start using AI tools in your job,” Ammanath said.
Looking for the full podcast? Listen to the full conversation on the Corporate Director Podcast: AI leadership strategies for a changing world.
