AI bots, fake outrage and the new rules of reputation management
You can’t defeat the bots. But you can learn to spot them sooner.
A robot hand with the letter AI and a lady justice statue on the wooden table with law books. 3d illustration.
When Cracker Barrel rolled out a new logo last fall, the backlash appeared instant and overwhelming. Within days, the restaurant chain was working to contain what looked like a full-blown reputational crisis.
But much of the outrage wasn’t real.
According to PeakMetrics, nearly half (44.5%), of X posts in the first 24 hours of the controversy came from automated bot accounts. The high volume of posts caught the eyes of influencers and politicians alike. The anger was largely manufactured. The impact was not.
The rise of AI has turned disinformation into a catalyst, capable of fabricating stories, amplifying outrage and overwhelming response teams before a company can even assess what’s happening.
“AI just continues to dominate…because of the rapid pace of transformation,” said Isabel Guzman, chair of the Global Risk Advisory Council. According to the Global Situation Room’s Reputation Risk Index, AI misuse was the top reputational risk companies faced in the fourth quarter of 2025.
“What makes this risk different is scale,” Guzman said. “It can happen within hours.”
A ‘bot storm’ problem
AI has lowered the barrier for disinformation campaigns to almost zero, said Greg Matusky, founder and CEO of Gregory FCA
“You can unleash a bot storm on a brand before any response can be formulated. And that can be done in moments,” Matusky said.
Unlike misinformation campaigns that required more technical expertise, today’s tools allow almost anyone to fabricate content using deepfakes, synthetic images or coordinated posts. Once released, those falsehoods don’t disappear, even if corrected, making the issue much more difficult to combat, he said.
“They have two impacts,” Matusky said. “One is to damage the reputation of the target. The other is to confuse what the truth really is.”
When false content spreads alongside legitimate information, audiences struggle to determine what to believe, causing even more skepticism to grow.
While it may be impossible to eliminate AI-fueled disinformation and bot activity, there are some things teams can do to spot potential risks early.
Learn to spot bot-driven backlash early
When backlash is mounting, analyze the situation, Guzman said.
“A sudden spike in outrage, especially from unfamiliar accounts or repetitive language, should be treated as a monitoring moment,” she said.
Matusky said it’s often possible to identify bot activity with basic checks. Before you act, ask:
- Do these accounts have consistent posting histories?
- Are they seemingly obsessed with one topic?
- Do posts lack a coherent theme or personal detail?
- Are many accounts repeating nearly identical language?
“If these things align, that’s a good indication it’s a bot,” Matusky said.
This means organizations increasingly need to train teams to verify content, trace where it originated, how it spread and who amplified it, he said. There are also numerous detection tools and software teams can buy, but Matusky warns that just because you detect bots, doesn’t mean you can eliminate them.
“The biggest concern for communicators is that they don’t know what’s coming,” Matusky said. “Identifying bad actors at least lets you respond before the fire spreads out of control.”
Another signal is that bot-driven outrage often concentrates on one platform while barely registering elsewhere, Matusky said. Much of the negative feedback during Cracker Barrel’s rebrand was found on X.
“Spotting this imbalance can help teams decide where, or whether, to respond publicly,” he said.
Flood the zone with credible information
In a disinformation-heavy environment, tracking every falsehood won’t work. The better approach is being visible when audiences actively search for answers, Guzman said.
“Flooding customers with true, valid, fact-based information is increasingly important,” she said.
One way to tell the difference between rumor and real concern is how people search for information online, she said.
False narratives often repeat the same phrasing again and again. Genuine information-seeking shows variation, like questions about how a change affects customers, what it means in practice or where to learn more.
Brands should identify areas most vulnerable to distortion, like policy decisions or recent changes, and prepare clear, plain-language explanations via FAQ’s, blog posts or an informational website.
“When audiences go looking for answers, those resources should be easy to find, easy to understand and clearly sourced,” Guzman said.
Use trusted human voices
During a crisis, who delivers the message is also important, Matusky said.
He pointed to companies, like Tesla, which use real customers to counter online rumors. These are people that have large social followings based on their expertise and knowledge of the brand, he said.
“People already trust them. They already follow them,” Matusky said.
Brands should build long-term relationships with credible voices who understand their company and can explain facts in human terms. These people will often be more persuasive than a brand account trying to counter bad info, Matusky said.
“You have to groom them, give them access and include them early,” Matusky said.
Look ahead
The downside right now is that there’s no single fix for AI-driven disinformation, Matusky said. Bad actors will keep evolving, likely staying one step ahead of detection tools.
Moving forward, companies must have a willingness to learn and adapt to how AI is shaping our information, good and bad, he said.
“You can’t stop people from creating false content anymore,” Matusky said. “What you can do is be ready to counter it, quickly, clearly and with the truth.”
Courtney Blackann is a communications reporter. Connect with her on LinkedIn or email her at [email protected].