https://mitsloan.mit.edu/ideas-made-to-matter/these-are-most-urgent-ai-risks-according-to-272-experts

These are the most urgent AI risks, according to 272 experts

By
Kristin Burnham

Artificial intelligence presents business leaders with a difficult management problem: The risks are numerous and fast-moving and fall unevenly across organizations, sectors, and stakeholders. Some challenges are well known, like the potential for discrimination and the spread of misinformation, while others are emergent, like AI systems that could accelerate cyberattacks, make weapons development easier, or behave in ways that were never intended.

Dangerous capabilities are broader: While malicious actors might use AI systems to do harm, advances in those systems could also make it easier to perform difficult, dangerous tasks, such as engaging in persuasion and surveillance, creating deepfakes, and even assisting with building chemical or biological weapons. “These are all things that you could previously do but now could do much more easily,” Slattery said.

Competitive dynamics are different: They’re not a single harmful use of AI but a condition that can intensify other risks. When companies or countries believe that AI will confer major economic or strategic advantage, they may have incentives to move quickly, resist constraints, or underinvest in safety. “This is an instrumental risk that creates other risks,” Slattery said.
Where AI risk may hit the hardest, and who is responsible

The study also points to three sectors that the experts indicated are most vulnerable to AI risk over the next five years: information, national security, and finance. Leaders in those sectors should understand that their exposure is not generic, Slattery said. Each sector is vulnerable in different ways because of its specific characteristics.

Information sector: Risks are closely tied to the flow of content and data, including misinformation, disinformation, privacy loss, manipulation, and the erosion of trust in what people see and read.
National security: The biggest concerns include cyberattacks, weapons development, surveillance, and the use of increasingly capable AI systems by hostile actors.
Finance: AI could amplify fraud, cyber risk, market manipulation, privacy breaches, and failures in systems that have broader economic effects.

Across those sectors, AI can make existing risks easier to scale, Slattery said. People who could not previously hack may now be able to do “a range of things related to hacking, while those who can already hack may do things faster or better or more easily,” he said.

The experts said that AI developers and governance actors, such as governments and regulators, have the primary responsibility for addressing AI risks. But AI system users and the stakeholders such systems affect are most vulnerable to those risks. Given that those who are most responsible for addressing risks are not those who are most vulnerable, there are misaligned incentives for taking action.

What leaders should do now

Slattery said the research isn’t intended to predict the future with certainty but to help leaders focus on the AI risks that experts believe are both serious and plausible in the near term. “We’re not saying these things are definitely going to happen,” he said. “We’re saying these are the things that experts think are worth paying attention to now.”

For business leaders, the top risks point to two immediate questions: what increasingly capable AI systems can now do, and whether competitive pressure is pushing organizations to deploy them faster than their governance practices can be updated. The concern is that companies, sectors, and governments may feel pressure to move quickly even when the risks are not fully understood.

That’s what makes the findings especially useful for business leaders, Slattery said, especially considering that many organizations are still treating AI risk as either a compliance issue or distant concern. Leaders should evaluate AI at the business process level, looking at where it could create return on investment, where it could change the broader ecosystem, and whether it could disrupt the products or services their organization provides.

Executives should start by recognizing that AI risk is not business as usual. Slattery cautioned against abandoning what already works but said that leaders should treat AI as a new paradigm that could replace many human tasks, introduce new vulnerabilities, and create “ecosystem-wide, society-wide opportunities and vulnerabilities.”

The response can’t be just a one-time adjustment, either. “It’s continuous and constant from now on because AI is moving so quickly that organizations need to be significantly more attentive and responsive to this technology and the related risks and opportunities than they have been with previous technologies,” Slattery said.

The larger message is that organizations do not need to wait for perfect forecasts or regulations before acting, Slattery said. They can begin by paying closer attention to the most severe and likely harms, and by making AI risk part of the same governance conversations they’re already having around cybersecurity, privacy, safety, and business continuity.

ial Intelligence Lab that studies the economic and technical foundations of progress in computing.

The MIT AI Risk Initiative aims to provide authoritative data and frameworks to help identify, prioritize, and manage the risks from AI. It includes the AI Risk Repository, a continuously updated database of more than 1,600 AI risks organized by cause and risk domain that is used by policymakers, technologists, and organizations to inform AI governance.