Artificial intelligence has rapidly become the go-to source for information, quietly replacing traditional search engines for many users — and most companies have yet to recognize the shift.

Today, millions of people consult AI tools such as ChatGPT, Claude, and Gemini before using conventional search platforms. Around half of consumers now prefer AI-driven answers over traditional search results, and those responses heavily influence purchasing choices, employment decisions, and brand trust. The impact extends even further: 94% of B2B buyers now rely on AI during purchasing decisions, while more than three-quarters of investors worldwide use AI-powered insights to guide investment strategies.

Despite this growing dependence on AI, many organizations still lack visibility into how their brands are represented in AI-generated responses. Are they appearing in results at all? If they are, is the portrayal accurate, balanced, or potentially damaging?

When existing tools failed to provide clear answers for clients, we decided to create a better solution.

“Communications leaders usually know their media coverage and search rankings, but very few understand how AI platforms currently describe their company,” said Charlie Wilkie. “That’s the visibility gap we designed this tool to solve.”

Introducing the AI Visibility Tracker from 3BL — a platform specifically created to measure and manage brand reputation within AI systems.

Key Features
Unlike many AI tracking tools focused mainly on product visibility, the AI Visibility Tracker concentrates on reputation — helping organizations understand how AI platforms interpret, discuss, and frame their brands.

The platform also delivers more advanced sentiment analysis than traditional tools. Instead of relying solely on positive or negative keywords, it evaluates the broader context of AI-generated discussions, capturing nuanced perceptions even when responses contain both praise and criticism.

“The foundation of public relations has always been that outside perspectives carry more weight than self-promotion,” Wilkie explained. “AI has amplified that reality even further, but many brands are still unprepared for it.”

As AI increasingly becomes the primary source of information for consumers, employees, investors, and business buyers, understanding how your brand appears in AI-generated content is no longer optional — it’s becoming a business necessity.

Click here to sign up to see your AI visibility score.

Artificial intelligence (AI) is rapidly transforming industries worldwide, and for good reason. AI streamlines routine tasks, enhances efficiency, and supports better decision-making.

Its impact extends into the investment sector as well. Advanced AI tools, such as natural language processing (NLP), can assist active managers in achieving better investment results by identifying negative environmental, social, and governance (ESG) news before it gains widespread attention.

The Consequences of Negative ESG News
Events such as oil spills, chemical leaks, child labor scandals, and executive misconduct can significantly harm a company’s reputation, weaken investor confidence, and negatively affect financial performance.

Research suggests that while positive ESG news has led to improved company returns, negative ESG news has had the opposite effect. Companies experiencing negative ESG events tend to underperform their competitors—not just on the day the news emerges but for weeks afterward. Data shows that stocks impacted by negative ESG news see an annualized excess return of -7.3% over a 10-day period (-1.2% for fixed income). Conversely, stocks benefiting from positive ESG news experience an annualized excess return of 6.2% (0.2% for fixed income).

NLP: A Game-Changer for Investors
If asset managers could detect ESG-related issues ahead of their peers, they would gain a competitive edge. However, manually sifting through corporate filings and news articles is an overwhelming and time-consuming process that must be repeated daily.

This is where NLP technology proves invaluable.

NLP, a subset of AI, enables algorithms to interpret, analyze, and generate human language. Since its inception in the 1950s, NLP has advanced from basic pattern recognition—such as responding to "thank you" with "you're welcome"—to more sophisticated deep learning techniques that understand context and sentiment.

Today, NLP technology can efficiently process vast amounts of raw data, identifying key insights with high accuracy.

Leveraging NLP for ESG Alerts
We have developed a cutting-edge NLP tool to complement our fundamental analysis. By incorporating the latest large-language models, this tool efficiently scans thousands of company reports and news articles, pinpointing potentially significant ESG concerns in real time.

Our tool monitors companies globally, analyzing news in multiple languages to detect ESG controversies across various topics, including human rights violations, discrimination, tax scandals, executive compensation, and corruption. Its scalability allows it to track emerging ESG concerns across hundreds of companies simultaneously, issuing timely alerts before negative news impacts the market.

Designed to comprehend financial terminology and ESG-specific nuances, the tool assesses tone and context to determine the sentiment surrounding an ESG issue for a particular company. It extracts key information, generates summaries, and highlights crucial details for analysts, while also linking to original sources for verification.

For instance, our NLP tool identified allegations against a major mining corporation operating in Central America, citing poor treatment of workers and local communities. These concerns led local governments to file lawsuits, ultimately resulting in revoked mining permits and the company abandoning a US$10 billion project. Fortunately, the tool alerted us to these risks well before government actions took place.

The Broader Role of NLP in Investment Analysis
While AI-driven tools are invaluable, they do not replace fundamental analysis. Negative ESG alerts do not necessarily deter us from investing, as the news may pose only a short-term risk or already be reflected in stock valuations.

Our investment teams integrate NLP insights with other relevant data to form a comprehensive analysis. Ultimately, the NLP tool serves as a crucial component within a broader strategy, helping us make informed investment decisions.

Additionally, by automating data collection and analysis, NLP allows our analysts and portfolio managers to focus more on critical thinking and strategic decision-making, ensuring that we continue to act in the best interests of our clients.