By Kim Alderman, Director, AI Innovation Lab, Riskonnect, Inc.
Artificial intelligence is transforming business – and risk management is no exception. Implementing new tech offers plenty of amazing opportunities to enhance risk assessment capabilities and boost efficiency. But AI also comes with a whole web of environmental, social, and governance implications that you need to get ahead of.
Environmental Considerations: The Hidden Costs of Innovation
The environmental impact of AI is nuanced. AI systems are fantastic at helping to optimize resource usage and cut down on waste, but they come with their own environmental baggage. Want a reality check? Training just one large language AI model consumes as much electricity as 25 American households in a year. That doesn’t count the carbon footprint from manufacturing all the necessary hardware or running those massive data centers. Add in the energy required for creating a response, and the cost goes up even more.
For risk managers, this creates a tricky balancing act between the incredible environmental benefits from AI – better resource management, improved efficiency, reduced waste – and the environmental costs. This is especially crucial now, as organizations face mounting pressure to slash carbon emissions and hit sustainability targets.
The takeaway here is to right-size. As compelling the use cases for AI are, there are many times where it is not the right technology for the problem. As the Wall Street Journal once pointed out, always defaulting to the biggest large language model is like using a Lamborghini to deliver a pizza.
Social Impact: The Human Side of the Equation
The social implications of AI represent some of the biggest challenges.
Data privacy and security. Organizations are swimming in data these days, and AI is gulping it down by the terabyte. The challenge? Using all this data responsibly while keeping it secure and private. You need to balance the amazing insights offered by AI against the very real risks of privacy breaches and regulatory headaches.
Workforce impact. AI is shaking up the way work gets done, and not everyone’s going to love it. Sure, AI tools can make teams more productive and open up exciting new roles. But here’s the tough part: Some tasks and jobs will become obsolete. Certain groups will be hit harder than others, especially in roles that are easier to automate. Risk managers need to think carefully about how to handle this shift. It’s not just about implementing new tech. It’s about taking care of your people and making sure you’re responsible with these changes.
Bias and fairness. Here’s an uncomfortable truth: AI systems can make existing biases worse if you’re not careful. These systems learn from historical data, and if that data reflects biases, guess what? The AI will too. This isn’t just about doing the right thing (though that matters); it’s about protecting your organizations from serious reputational and operational risks, especially in sensitive areas like hiring, lending, and customer service.
The takeaway here is to remember that AI is not just about GPUs and neural networks, but how it can work for people. Consider effects on employees, customers, and the broader society, and remember that “with great power comes great responsibility.”
Governance Challenges: Keeping AI in Check
The biggest challenge might be making sure AI systems stay on track and do what they’re supposed to do. Here’s what to focus on:
Getting the structure right. Establish clear lines of responsibility for your AI systems. Who’s watching the inputs and outputs? Who steps in when something goes sideways? As these systems get more complex and autonomous, having clear answers to these questions becomes crucial. Remember that a computer is never going to take accountability for a decision, so you need a structure for oversight of often opaque systems.
Staying on the right side of regulation. The changing regulatory landscape for AI is hard to keep up with. For example, the EU’s AI Act sets new standards that must be adhered to. You’ll need to stay ahead of these changes and make sure your AI implementations don’t land you in hot water.
Getting the board on board. It’s important to help boards and other leaders understand what’s at stake with AI. That means you’ve got to be good at translating technical AI risks into business terms that make sense to business leaders.
The takeaway here is that AI governance is a team sport. Bringing together different departments and stakeholders is critical to full-coverage defense and offense.
Here’s Your Game Plan
- Get serious about AI risk assessment.
- Understand your AI systems’ environmental impact.
- Think through how your AI affects your people.
- Make sure your governance can handle AI-specific challenges.
- Measure what matters.
- Set up clear metrics for tracking AI’s ESG impact.
- Create early-warning systems to catch problems before they can snowball into a crisis.
- Perform regular check-ups on your AI systems.
- Break down those silos.
- Work hand-in-hand with your IT, HR, and sustainability teams.
- Stay connected with outside experts that can see things you might miss.
- Keep those lines of communication open with regulators.
- Keep learning.
- Make sure your risk teams really understand AI and its ESG implications.
- Stay current on regulatory changes.
- Spread the word about AI-related ESG risks across your organization.
Looking Ahead: What’s Around the Corner?
The intersection of AI and ESG isn’t standing still. Here’s what to watch:
Better tools for responsible AI: The good news? New technologies and methods make it easier to manage AI’s ESG impact. Think more energy-efficient training methods for AI models, better bias detection, and smarter governance tools.
More rules: The regulatory landscape rarely stays the same for long, and it’s likely that global AI regulation will continue to get more complex. Stay nimble and ready to adapt as new rules roll out.
Rising expectations: Everyone from investors to customers to employees expects the organization to use AI responsibly. Meeting these expectations while keeping operations running smoothly is going to be key.
Managing AI’s ESG impact will take skill, focus, and constant adjustment. But getting this right is crucial for your organization’s future success. Risk managers are in a unique position to help navigate these challenges while making the most of AI’s incredible potential.
The stakes are high – but so are the opportunities. Those who can effectively balance the risks and rewards of AI while managing ESG considerations will be the ones leading the charge into the future. It won’t be easy, but then again, the most important things rarely are.
For more on managing AI risks, download our ebook, Technology Risk Management: Detection to Protection, and check out Riskonnect’s IT risk management software.
