Reputation in a New Era of AI: Quick-Slides

Using artificial intelligence has become a part of daily operations. From building innovative products, to using them, large language models (LLMs) are sharing more information than ever before about companies themselves — and is impacting reputation accordingly. These 7 quick-slides answer your questions about the challenges and opportunities that AI can bring to your corporate reputation.

Frequently asked Questions

1. What is reputation intelligence?

Reputation intelligence is the ability to understand how stakeholders — investors, employees, customers, regulators, and communities — perceive your company. It goes beyond surface-level opinion by tracking these perceptions over time, giving leaders the clarity to make decisions that turn reputation into a measurable business asset.

2. What is Purposeful AI in business?

Purposeful AI is about applying artificial intelligence with intent, strategy, and direction. It’s not about technology for its own sake — it’s about using AI to deliver insights that build credibility, strengthen trust, and reinforce long-term reputation advantage.

3. Why is data quality critical for AI insights?

AI is only as reliable as the data behind it. Poor-quality or incomplete data can lead to biased or inaccurate insights. High-quality, long-term datasets (especially those rooted in stakeholder perceptions) create more accurate and actionable reputation intelligence.

4. How can leaders reduce reputational risk in the AI era?

Leaders reduce reputational risk by pairing AI-generated insights with human intelligence. Monitoring misinformation, anticipating reputational challenges, and leveraging platforms like RepTrak Compass™ provide a continuous guide to navigate uncertainty and safeguard reputation.