This article first appeared in Digital Edge, The Edge Malaysia Weekly on June 10, 2024 - June 16, 2024

The rise of generative artificial intelligence (AI) has had a large impact on businesses worldwide, but one thing that is often overlooked is the effect AI has had on reputation. While the tool has been a boon in streamlining the management process, it can also be abused to create fake images or disinformation that can misrepresent and tarnish a company’s reputation.

“I’m aware that there [have] been many consumer fraud attempts using deepfake generative AI to impersonate government figures and others. In the US recently, in the primary contests for the US presidential election, there were specific instances of Democratic voters receiving deepfake calls from what they thought was President [Joe] Biden asking them not to go out to vote,” says Conall McDevitt, Asia and Europe senior partner at international stakeholder solutions provider Penta Group.

The use of deepfakes — realistic computer-generated copies of a person’s voice and appearance — to spread misinformation and lies is increasingly widespread but new technologies are being developed to combat them as well.

But are the dangers worth the convenience of the technology? The development of AI has brought many benefits in terms of reputation management as well, solving issues and streamlining processes, says McDevitt.

“[AI is able] to understand data that the company has collected or has available to it around its reputation,” he explains. This allows it to provide “more accurate and earlier warnings of potential issues that are floating around the company”.

For companies monitoring their media coverage, for example, website traffic and comments or search optimisation analysis, generative AI can be used to analyse the data to identify trends the companies can pursue to make popular decisions, or potential threats to look out for to avoid losing trust, says McDevitt.

The technology can be used to counter the threats of AI itself. AI tools, like Sentinel, are being developed to detect deepfakes and other AI-generated content that can be misleading or cause reputational harm to companies.

“Every company needs to care about its reputation. It is what’s on the balance sheet, it is called goodwill,” he says.

The best way to solve reputational risks in a company involves dealing with what McDevitt calls the four main stakeholder groups — the employees, investors, customers’ regulators and policymakers. “All of these groups will talk about the business. Oftentimes, they will talk about it in public forums and they will leave a digital trace,” he points out.

McDevitt says these traces can be studied and measured by AI, which can help an organisation analyse the company’s reputation with these stakeholders, having a holistic view instead of three or four separate perspectives. “And that’s the thing a human might struggle to do because of bias and our limitations in terms of ability to consume large amounts of data.”

He stresses the need to track and understand these four stakeholders in managing a company’s reputation in an increasingly digital world.

“Understanding your business is the first step to understanding risk and operational risk. You should have the same level of planning to manage the reputational risk as you do with operational risks,” he says, adding that it is important regardless of company size, from multinational corporations to small and medium enterprises (SMEs).

This is where AI can come in to ease the process of dealing with reputational risks. “If there are any small business owners today thinking about how to even go about mapping out a reputational risk framework, you could start by simply asking ChatGPT or Gemini to make some suggestions,” says McDevitt.

“You can ask ChatGPT to make some suggestions for a crisis management plan … Just tell it generally what your business does. You don’t need to give it the name of your business [or] any proprietary information. Just generally describe your business and it will produce the document for you.”

Drafting frameworks and policies aside, the biggest boon AI brings to reputation management is its ability to synthesise data, to understand data that the company has collected or has available to it surrounding its reputation, which means the AI can accurately detect early warnings of potential issues in the company.

But when it comes to using AI to manage reputational risks, McDevitt sees that businesses, whether small, medium or large, need to understand the opportunities and threats that AI brings.

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