WHY EXPERIENCED EDITORIAL REVIEW STILL MATTERS AS AI BECOMES MORE COMMON IN CORPORATE COMMUNICATIONS A press release can be grammatically correct and still contain a problem. An incorrect stock ticker may be spelled perfectly. An outdated date may look normal. A paragraph generated with AI may read smoothly while containing an inconsistent name, title or fact. Once distributed, these details matter because corporate information can move quickly across media outlets, financial platforms, search engines, databases and other digital systems. As AI becomes more common in corporate communications, teams have more tools to help draft, revise and refine press releases. But these tools can also introduce new issues, and many existing problems still require context and judgement to identify. To explore what this means for the review process, we spoke with four TMX Newsfile News Leads about the issues they encounter in submitted press releases and what automated tools may miss. Across their responses, a consistent theme emerged: many of the issues that matter most involve accuracy, context, consistency and judgement, not simply spelling or grammar. Editorial Review Goes Beyond Proofreading Traditional proofreading focuses on whether the words on the page are correct. Editorial review looks more broadly at whether the information is accurate, consistent and appropriate for distribution. That can mean checking details such as names, dates and stock tickers, but it can also require judgement about newsworthiness, tone, third-party references and whether the release is structured as a corporate announcement rather than an advertisement, article or blog post. TMX Newsfile's Editorial Guidelines outline standards covering areas such as newsworthiness, writing quality, credible contact information, unauthorized comparisons, excessive keyword use and prohibited content. Many of these issues cannot be identified through a spelling or grammar check alone. A Correct Word Can Still Be the Wrong Information The News Leads identified a range of seemingly small issues that can affect the accuracy or quality of a corporate announcement. These include outdated dates carried over from previous releases, inconsistent company or executive names, outdated or incorrectly formatted stock tickers, broken website links, incorrect contact information and placeholders that were never replaced. An automated checker may see nothing wrong with these details. The words themselves may be spelled correctly and the sentences may be grammatically sound. An experienced reviewer can look at the release as a whole and identify details that appear inconsistent, outdated or inappropriate in context. A Press Release Can Be Grammatically Correct and Still Not Be Distribution Ready AI Has Made Human Review More Important, Not Less As AI becomes more common in corporate communications, it can help teams draft, revise and organize content more efficiently. But TMX Newsfile's News Leads are also seeing new types of mistakes in AI-assisted submissions. News Leads identified unfinished placeholders as a recurring issue. Names, job titles, statistics or quote attributions may be left incomplete when AI does not have the information needed to fill them in. Some signs are more obvious. One of TMX Newsfile's News Leads has encountered releases that still contain conversational text from an AI tool, including instructions such as, “Let me know if you would like me to make any adjustments.” Other issues are harder to spot. The News Leads reported inconsistent names or job titles within the same release, repetitive writing that restates the same core point without adding information, and promotional language that can make a release read more like marketing copy than a corporate announcement. Fluent Writing Is Not the Same as Accurate Disclosure AI can produce polished language very quickly. That does not mean every detail in the resulting document has been verified. Names, numbers, dates, titles, stock tickers, quotations and other factual information should still be checked against the company's source material. A release should also be reviewed as a complete document rather than as a collection of individually well-written paragraphs. This distinction is particularly important in corporate communications. A sentence can sound convincing while still containing an incorrect fact, an inconsistency or information that does not belong in the release. Context Is Difficult to Automate Some of the most important editorial decisions involve context rather than grammar. The value of editorial review goes beyond finding errors. It includes understanding whether the information makes sense in context. A spelling or grammar tool may not determine whether a headline accurately reflects the announcement. It may not recognize that a company is relying on the name of an unrelated third party to attract attention, or know when promotional language has crossed the line into advertising. Tone and intent can be even more difficult to assess. “AI can be very helpful with specific content in a release, but it can have difficulty reading between the lines and understanding tone or intent." TMX Newsfile News Lead This becomes particularly important in the grey areas of corporate communications. A release can contain confident language without being overly promotional. It can mention another organization where that organization is genuinely relevant to the announcement. And it can discuss a disagreement or legal matter without making unsupported or potentially defamatory claims. Those distinctions require judgement about what the release is actually communicating, not simply whether the individual sentences are technically correct. Small Omissions Can Have Larger Consequences Sometimes the most important thing an editor catches is not an error in the release. It is something that appears to be missing. During a preliminary review of a client's full-year financial results release, a senior TMX Newsfile newsroom specialist noticed that standard advisory sections normally included at the end of the company's annual releases were absent. The specialist compared the submission with previous releases from the company and flagged the difference. The client confirmed that the sections had inadvertently been left out of the submitted draft and corrected the release before distribution. The example illustrates an important aspect of experienced editorial review. The question is not always, “What is wrong with this document?” Sometimes it is, “What should be here that isn't?” This can be difficult for an automated proofreading tool to answer because the missing information does not exist in the document for the tool to assess. “Spelling and grammar tools can identify errors, but they don't necessarily understand the story. Experienced editorial review adds context and logic.” TMX Newsfile News Lead This is particularly relevant for recurring corporate announcements such as financial results, financings, acquisitions and exploration updates, where companies may follow established disclosure formats from one announcement to the next. Formatting Is Part of Editorial Quality Editorial review also extends beyond the words themselves. Corporate press releases can contain financial tables, technical data, photographs, charts, captions, hyperlinks and multiple language versions. These elements need to remain clear and functional as a release moves through distribution channels. TMX Newsfile's News Leads encounter issues such as tables submitted as images, low-resolution graphics and visuals assembled from multiple elements in a Word document rather than provided as a finished image. Language and distribution settings add another layer of complexity. A release may be submitted under the wrong language setting, for example, or the selected distribution network may not align with restrictions in the announcement. These details may not change the wording of a release, but they can affect how the information is presented, where it is distributed and how effectively it reaches its intended audience. AI, grammar tools and templates can make preparing press releases faster and more efficient. But efficiency does not replace judgement. The issues identified by TMX Newsfile's News Leads show why experienced editorial review still matters. A polished press release is important, but distribution readiness also requires context, verification and judgement. Sources TMX Newsfile (Editorial Guidelines) Interviews with four TMX Newsfile News Leads, August 2026

The final review of a press release is often the last opportunity to catch a problem before an announcement becomes public. A date copied from an earlier release. A number that changed during the approval process. A quote attributed to the wrong title. A link that no longer works. These details can be easy to overlook when several people have reviewed multiple versions of the same document. For investor relations and communications teams, a final check should go beyond spelling and grammar. It should confirm that there is a clear newsworthy announcement, that the important facts are accurate and consistent, and that the release is ready for distribution. Before submitting your next press release, use this press release checklist to work through five essential checks. 1. Start With the Announcement Before checking individual details, read the release once for the bigger picture. Ask a simple question: Is there a clear, newsworthy development from the company? A press release should communicate an announcement or development rather than read like an advertisement, general article or blog post. The headline and opening should make the purpose of the release clear without requiring readers to search for the news. Check the headline and opening □ Does the headline clearly identify the announcement? □ Is there a clear, newsworthy development from the company? □ Does the opening paragraph explain the most important information? □ Is the company making the announcement clearly identified? □ Does the release provide enough context to understand the development? Check the story as a whole Read the headline, opening paragraph and rest of the release together. They should tell a consistent story. If the headline announces growth but the body describes a decline, or the opening describes a transaction differently from later paragraphs, reconcile the information before distribution. 2. Verify the Facts That Are Easy to Get Wrong A word does not have to be misspelled to be incorrect. Dates, numbers, names and stock tickers can all look perfectly normal on the page while containing the wrong information. Verify these details against the source □ Company name and spelling □ Executive names and current titles □ Announcement date and relevant transaction or event dates □ Stock exchange and ticker symbol □ Financial figures and percentages □ Share counts, financing amounts and transaction values □ Locations, property names and project names □ Contact names, email addresses and phone numbers If a number appears more than once, check every occurrence. Correcting one version of a figure does not automatically correct it everywhere else in the release. THE 60 SECOND FACT CHECK 3. Remove Anything Left From the Drafting Process Some of the easiest mistakes to miss are remnants of earlier drafts. This deserves particular attention when AI or templates have been used to prepare a release. TMX Newsfile's News Leads have encountered placeholders, repeated information and even conversational instructions from AI tools left in submitted releases. Search the final document for: □ Placeholder names such as Jane Doe or John Smith □ XX, TBD, TK or other temporary markers □ Blank dates, statistics or quote attributions □ Internal comments or drafting instructions □ AI prompts or conversational responses □ Duplicate paragraphs or repeated sections □ Information carried over from an earlier release A quick document search for terms such as TBD, XX and placeholder can help uncover remnants that are easy to miss during a normal read. 4. Check the Supporting Elements A release can be accurate on the page and still contain problems with the elements that accompany it. Quotes Confirm that each quotation is attributed to the correct person and that the person's name and title match references elsewhere in the release. If a quote changed during the approval process, make sure the release contains the final approved version. Links Do not assume a hyperlink works because it looks correct. Open it. □ Does the link work? □ Does it lead to the intended page? □ Is the page publicly accessible? Images, Tables and Charts Supporting material also needs to be ready for distribution. □ Are images clear and high quality? □ Do captions correspond with the correct images? □ Are graphics provided as finished files rather than separate elements assembled in a document? □ Are tables provided in an appropriate format? These details can be easy to overlook when a release looks correct in the document used to prepare it. 5. Confirm the Release Is Ready to Go Public Once the detailed review is complete, step away from individual words and look at the release as the document that will actually be distributed. Ask: “Are we comfortable with this exact version becoming public?” Before submitting, confirm: □ You are submitting the correct final version □ Required internal, legal and regulatory approvals are complete □ Quotes are final and correctly attributed □ Supporting files are ready □ The appropriate language and distribution selections have been made □ No comments, placeholders or drafting notes remain One Last Read Read the release once as someone seeing the announcement for the first time. Does anything seem inconsistent? Is anything confusing? Does something appear to be missing? That last question is worth asking. A final review is not only about finding incorrect information. Sometimes the important issue is information that should be there but isn't. Before a press release is distributed, a final review should confirm that the announcement is clear and newsworthy, the facts are accurate, drafting remnants have been removed and the release is ready to move through its intended distribution channels. A few minutes spent checking the final version can prevent a small oversight from becoming part of the public announcement.

Disclosure Intelligence Series How disclosure works in modern capital markets What separates exceptional announcements from the rest? In a companion analysis, TMX Newsfile found little evidence that formatting techniques and keyword strategies alone increase AI visibility. This raises a more important question: if formatting alone doesn't explain AI visibility, what does? This study examines the characteristics associated with the announcements generating the highest levels of AI activity. To answer this question, TMX Newsfile analyzed more than 9.3 million AI interactions across over 21,000 press releases published during the first half of 2026 to identify the characteristics associated with exceptional AI visibility. The findings suggest that exceptional AI visibility is associated less with optimization techniques than with the significance of the information being disclosed. 240× Difference Between Typical and Exceptional AI Activity AI Activity in Press Releases is Highly Concentrated Most press releases generated similar levels of AI activity. However, AI activity was not evenly distributed. A relatively small number of announcements accounted for a disproportionate share of total AI activity. These high-performing announcements significantly outperformed the broader dataset. This pattern suggests that exceptional AI visibility is associated with characteristics found in a relatively small subset of announcements rather than factors common to all press releases. Identifying the characteristics shared by those high-performing announcements was the focus of the analysis. This concentration creates a wide performance gap across the dataset. At the extreme, the highest-performing announcements generated more than 240 times the AI activity of a typical press release, reinforcing how a small number of releases drive overall visibility. Material Corporate Developments Stand Apart One of the most consistent characteristics associated with the highest performing announcements was the communication of significant corporate developments. Across the dataset, exceptional AI activity was consistently associated with announcements involving major commercial agreements, strategic transactions, financing events, legal outcomes, and other developments with broad market significance. Examples from the dataset include Gorilla Technology Group's announcement of a US$2 billion AI infrastructure agreement with Supermicro and Sigma Lithium's announcement regarding a significant increase in investment by A10 Global Fund, accompanied by a detailed explanation of the company's investment thesis and long term growth outlook. Both generated AI activity many times greater than a typical press release, despite communicating very different types of corporate developments. These examples illustrate a broader pattern observed across the dataset rather than isolated cases. Their performance was not associated with unusually high keyword repetition or specialized formatting techniques, but with the significance and market relevance of the information being disclosed. This suggests that AI systems respond most strongly to announcements containing information with broad market relevance rather than routine corporate updates. "Performance varies across industries, but the highest levels of AI activity are ultimately driven by a small number of high-performing releases." Industry Establishes Different Performance Baselines While exceptional announcements generated the highest levels of AI activity, industry also provided an important baseline for comparison. Across the first half of 2026, several sectors consistently generated higher average AI activity per press release than others. These findings build on earlier analysis of a smaller sample over a shorter time period, which showed higher average AI activity in mining and energy press releases. That result reflected the presence of a small number of exceptionally high-performing announcements within the resource sector. In contrast, the larger H1 2026 dataset highlights more consistent average performance across sectors such as technology and biotechnology. These differences likely reflect the types of information commonly disclosed within each industry, as well as varying levels of market attention. Technology, biotechnology, blockchain, mining, energy, and several other sectors consistently generated higher average AI activity than many traditional industries. These findings suggest that industry provides important context when evaluating AI activity. High performing announcements should be evaluated relative to others in their sector rather than against the entire dataset. The chart below highlights the differences in average AI activity across the highest performing industries. Comparing industries alone, however, does not explain all variation in AI activity. The analysis also identified meaningful differences based on issuer type. Public and Private Issuers Display Different Patterns Performance also differed between public and private issuers. Across the H1 2026 dataset, private company press releases generated an average of 244 AI interactions per release, compared with 173 interactions for public companies. This difference does not necessarily indicate that private companies communicate more effectively. One possible explanation is that private companies often issue press releases around major corporate milestones, while public companies also distribute a larger number of routine regulatory announcements, financial filings, governance updates, and other operational disclosures. As a result, the mix of announcements included within each issuer group may contribute to the higher average AI activity observed among private companies. These findings suggest that issuer type also provides important context when evaluating AI activity. A press release should be assessed relative to similar announcements rather than across all companies. What Sets High-Performing Press Releases Apart? The analysis suggests that high-performing announcements share several characteristics. They typically communicate material developments, outperform their industry's typical baseline, and attract substantially greater AI activity than the average press release. What This Means for Issuer Teams Improving AI visibility appears to depend more on communicating meaningful developments than on optimizing formatting or keyword placement. Issuer teams should focus not only on how announcements are distributed, but also on whether they communicate information likely to be recognized as significant within their industry. As AI becomes an increasingly important channel for corporate information, understanding the characteristics associated with exceptional AI visibility can help organizations produce disclosures that resonate with both human and AI audiences. Unlike formatting techniques or keyword repetition, exceptional AI visibility appears to be driven less by optimization tactics than by the significance of the information being disclosed. Across the dataset, announcements communicating material developments consistently generated higher AI activity than routine disclosures. Related Reading Can Press Releases Be Optimized for AI Discovery Through Formatting and Keyword Strategies? Our companion analysis examines whether formatting techniques and keyword strategies influence AI visibility.

Disclosure Intelligence Series How disclosure works in modern capital markets Can press releases be optimized for AI discovery solely through formatting and keyword strategies, as commonly suggested? As AI becomes an increasingly important gateway to corporate information, a growing number of recommendations suggest that formatting techniques and keyword strategies can improve AI visibility, despite limited empirical evidence. While formatting may support readability, this analysis focuses on how content patterns relate to performance. To evaluate these claims, TMX Newsfile analyzed more than 9.3 million AI interactions across over 21,000 press releases distributed during the first half of 2026, examining how announcements actually perform rather than testing specific formatting techniques in isolation. The findings suggest otherwise. There is little evidence that commonly recommended keyword practices and related content patterns are associated with higher AI visibility. Instead, AI activity varied significantly across industries and was concentrated among a relatively small number of announcements that substantially outperformed their sector baselines. Understanding these findings begins with an important distinction between machine readability and AI visibility. In this analysis, “keywords” refer to the meaningful words within a press release after removing common filler words such as “the,” “and,” and “is.” This allows the analysis to focus on the terms that carry the core information in each announcement. “Formatting helps AI understand information, but it does not necessarily make that information more visible.” To understand these patterns, press release performance was evaluated across multiple indicators and assessed relative to others within the same industry, making it possible to distinguish typical performance from statistical outliers. Measuring Performance in Modern Disclosure As AI increasingly influences how corporate information is discovered and interpreted, understanding press release performance within AI systems has become an important part of modern disclosure. Press releases are continuously processed by AI systems, indexed across search engines, financial data platforms, and information aggregators, and referenced over time. This creates measurable differences in how announcements perform after publication. This analysis includes 21,549 press releases, providing a comprehensive view of AI activity across sectors and issuer types. To ensure fair comparisons across industries, each press release was evaluated relative to others within its sector, making it possible to distinguish typical performance from statistical outliers. What Defines an Outlier in Performance A performance outlier is a press release that significantly exceeds or falls below typical levels of activity within its industry. Identifying outliers helps distinguish unusually high- or low-performing announcements from typical performance within each industry. AI Visibility in Press Releases Is Not Driven by Keyword Repetition Alone The analysis found little evidence that commonly recommended keyword repetition and content patterns are associated with higher AI visibility. These findings challenge the growing narrative that press releases can be optimized for AI visibility through keyword repetition alone. To explore this further, the analysis examined whether increasing keyword repetition, a common indicator of keyword stuffing, was associated with higher levels of AI activity. This chart shows how much a single word dominates a press release, helping identify whether excessive repetition is associated with AI activity. The data shows no consistent relationship between repetition of a single word and AI activity. High-performing press releases appear across a wide range of repetition levels, indicating that excessive repetition alone does not improve AI visibility. Taken together, these findings suggest that AI visibility is influenced less by repetition patterns than by the substance and relevance of the information being disclosed. How AI Activity Changes with Content Length This analysis examines how the length of a press release relates to AI activity, using the number of meaningful words after removing common filler words. As content length increases, AI activity initially rises, reaches a peak, and then begins to decline. This suggests that while very short releases may lack sufficient detail, simply adding more content does not continue to improve AI visibility. Instead, the strongest performance occurs within a natural range, where content remains clear, focused, and centered on communicating substantive information rather than unnecessary length. What This Means for Issuer Teams The analysis suggests that AI visibility is driven less by formatting or keyword repetition than by the significance and relevance of the information being disclosed. This does not diminish the importance of structure. Clear headings, logical organization, and well-written disclosures remain essential for machine readability, helping AI systems accurately extract and interpret information. However, the analysis found little evidence that these practices alone are associated with higher AI visibility. For issuer teams, the implication is straightforward: focus first on communicating meaningful information, then present it in a format that is easy for both people and AI systems to understand. This analysis challenges the assumption that repeating keywords or adjusting content patterns alone can improve AI visibility. Instead, the findings suggest that the announcements generating the strongest AI activity are distinguished less by how they are formatted than by the significance and relevance of the information they contain. The results also reinforce an important distinction between machine readability and AI visibility. Clear structure helps AI systems extract and interpret information, but does not necessarily make that information more visible. If formatting and keyword repetition alone do not explain AI visibility, what does? Part 2 of the Disclosure Intelligence Series explores the characteristics that distinguish the highest-performing press releases from their peers

Disclosure Intelligence Series How disclosure works in modern capital markets When a press release is distributed, most issuer teams consider the communication complete. But in reality, this is the point at which another audience begins reading it. Search engines, AI models, financial data platforms, and brokerage systems start processing corporate announcements within seconds of publication. Before many investors read a press release, machines identify companies, extract key facts, categorize events, and begin incorporating this information into search results, financial platforms, and AI-generated responses. According to PwC's Global Investor Survey 2025, 62% of investors now use AI to analyze company filings and earnings call transcripts, while 56% use AI to help develop investment research and investment theses. Only 4% reported that they are not using AI in their investment process. TMX Newsfile's own research shows how quickly this process begins. Our analysis of approximately 220 press releases distributed across TMX Newsfile's global news distribution network found that 75.8% of observed AI processing occurs within the first 24 hours after publication. During this period, AI systems establish an initial understanding of the announcement that may influence how it is summarized and presented across digital platforms. This means disclosure is no longer consumed only by people. It is increasingly processed by machines before many investors encounter it. Disclosure Now Has Two Audiences Every press release now serves two audiences. The first is the people who read the announcement, including investors, analysts, journalists, and regulators. The second is the systems that discover, interpret, categorize, and summarize that information before many of those readers encounter it. This does not change the purpose of a press release. It changes how information should be organized. The goal is to organize information so both audiences begin with the same understanding. As a result, the structure of a press release has become increasingly important. Information that is clearly organized is easier for both people and machines to interpret. Machine Readable Disclosure is Becoming Standard Machine readable disclosure is information that software can identify, interpret, and process without relying solely on human interpretation. For many public companies, this concept already exists within regulatory reporting. Financial statements filed through EDGAR use Inline XBRL to identify financial concepts through standardized tags, allowing software to recognize information such as revenue, net income, assets, liabilities, and earnings per share. The importance of structured disclosure continues to grow The U.S. Securities and Exchange Commission's latest report under the Financial Data Transparency Act states that 43 of 55 core SEC disclosure forms now require some machine readable data. The report also cites research showing that structured data can improve large language model performance while reducing error rates compared with unstructured documents. Press releases work differently Unlike financial statements filed using Inline XBRL, press releases generally do not contain standardized financial tags. Instead, AI systems rely on document structure, headings, metadata, consistent terminology, and clearly presented relationships between facts to interpret an announcement. Figure 1: Machine Readability in Regulatory Filings and Press Releases Why Press Release Structure Matters Unlike human readers, AI systems depend on clear document organization to identify companies, executives, financial metrics, dates, and material events. They also compare information across press releases, regulatory filings, company websites, earnings transcripts, and previous disclosures. When important information is difficult to identify or inconsistent across sources, the risk of misinterpretation increases. The objective is to organize information so it can be interpreted consistently across both audiences. Figure 2. How AI Interprets a Press Release How to Structure Press Releases for Machine Readability Understanding how to structure press releases for machine readability has become increasingly important as AI systems begin processing disclosures immediately after publication. Machine readable disclosure is not about writing for machines instead of people. It is about organizing information so both audiences identify the same facts and interpret the announcement as intended. The following principles can improve how press releases are processed by AI systems while making disclosures clearer for investors, analysts, journalists, and regulators. Lead With the Material Announcement The opening paragraph should communicate the material announcement immediately. State what happened before explaining why it matters. Whether announcing financial results, a financing, an acquisition, a regulatory milestone, or a leadership appointment, state the material event first, followed by the most important supporting details. If the announcement relates to financial performance, identify the reporting period and the primary financial metrics early in the release. If it relates to a transaction, clearly identify the parties involved and the nature of the transaction before providing additional background. A reader should understand the purpose of the announcement after reading the opening paragraph. Organize Information Into Clear Sections Group related information into logical sections with descriptive headings. Separate financial results, operational updates, transaction details, management commentary, and forward looking information wherever possible. Each section should communicate a single topic before moving to the next. This structure allows readers to locate information more quickly while helping AI systems distinguish one topic from another. Clear organization reduces ambiguity without changing the underlying message. Use Consistent Terminology Consistency helps preserve meaning across every disclosure. Use the same terminology throughout the press release when referring to financial metrics, business units, subsidiaries, products, projects, and executive titles. For example, avoid referring to the same financial measure as revenue, sales, and top line performance within a single announcement. Most readers can usually interpret these variations. AI systems are more reliable when the same concepts are described consistently. Separate Facts From Commentary Present factual information before interpretation. Financial results, operational updates, transaction details, and other material information should be clearly distinguished from management commentary explaining why those results are significant. This helps readers separate objective disclosure from management's perspective while making it easier for AI systems to identify the underlying facts. Clear separation improves readability without reducing context. Maintain Consistency Across All Corporate Disclosures A press release is rarely the only document describing a material event. The same announcement may also appear in regulatory filings, investor presentations, financial statements, earnings materials, and information published on the company's website. Company names, executive titles, reporting periods, financial metrics, transaction values, dates, and other key information should remain consistent wherever they appear. This does not require identical wording. But, it requires every disclosure to communicate the same underlying facts clearly and consistently. Strong disclosure has always depended on accuracy, completeness, and regulatory compliance. As AI becomes a standard part of investment research, consistency across disclosures also plays an increasingly important role in how that information is interpreted. Machine Readability Checklist for Press Releases: ✔ Lead with the material announcement ✔ Organize information into clear sections ✔ Use consistent terminology throughout ✔ Separate facts from commentary ✔ Keep information consistent across press releases, regulatory filings, and investor communications What This Means for Disclosure Strategy Machine readable information is becoming an increasingly important part of corporate communications. AI systems are now embedded throughout the investment process, helping investors discover, compare, summarize, and evaluate corporate information. At the same time, regulators continue expanding the use of structured, machine-readable reporting, recognizing its value in making disclosure data more accessible and easier to use. For issuer teams, this does not require writing differently. It requires organizing information more deliberately. TMX Newsfile's research found that 75.8% of observed AI processing occurs within the first 24 hours after a press release is published. During that period, announcements are interpreted, categorized, and connected with other public information. Clear organization helps ensure that process begins with accurate, well structured disclosure. For decades, disclosure quality has been measured by accuracy, completeness, and regulatory compliance. Those principles remain unchanged. Today, structure is becoming another measure of disclosure quality. Press releases have always been written to inform the market. Today, they also influence how corporate information is interpreted across an increasingly AI driven investment ecosystem. The most effective press releases will continue to communicate clearly to people while presenting information in a way that AI systems can accurately interpret. Structure does not change the message. It helps preserve its meaning.

For many public issuers, expanding into new markets means more to manage. As disclosure extends across Canada and the United States, even core tasks like distributing and posting press releases can involve additional steps, systems, and coordination. For DLP Resources Inc., a publicly traded mineral exploration company, the focus has been on keeping the distribution and cross-border posting of its news simple. “They seamlessly post our news on the OTC Markets site. I don’t even have to think about it.” — Robin Sudo, Office Manager / Corporate Secretary, DLP Resources Inc. About DLP Resources DLP Resources Inc. is a publicly traded mineral exploration company operating in Peru and Southeastern British Columbia, Canada. The company is listed on the TSX Venture Exchange (DLP), the OTCQB (DLPRF), and the Frankfurt Stock Exchange (J8C), managing disclosure obligations across multiple jurisdictions. Consistent Disclosure From the Start DLP Resources has worked with TMX Newsfile since the company’s inception in 2019. From the beginning, the goal was to establish a process that was reliable, easy to manage, and consistent as the company grew. As Office Manager and Corporate Secretary, Robin Sudo is responsible for ensuring disclosure is handled correctly across jurisdictions, including maintaining visibility on U.S. OTC Markets. “What stood out most was how accessible our representative was, how easy they were to work with, and how clearly everything was explained.” — Robin Sudo, Office Manager / Corporate Secretary, DLP Resources Inc. The Challenge: Managing Cross-Border Posting & OTC Reporting In many organizations, cross-border disclosure introduces additional steps. Press releases and regulatory postings, including OTC reporting, are often handled through separate systems, requiring manual coordination to ensure information is distributed correctly across jurisdictions. For DLP Resources, the challenge was not complexity. It was time. “If I had to do the filing on the U.S. OTC site myself, it would be time-consuming. Not difficult, but time-consuming.” — Robin Sudo, Office Manager / Corporate Secretary, DLP Resources Inc. Even when the process is manageable, it still takes time away from more important work. The Solution: A Single, Coordinated Workflow TMX Newsfile simplifies this process by handling distribution and cross-border posting within a single workflow. For DLP Resources, this means: Press releases are distributed and filed through one process Posting to OTC Markets is handled automatically No additional systems or manual coordination are required By removing the need for separate steps, the process becomes both faster and more reliable. Why It Works: Support That Removes the Burden For DLP Resources, the value of the process is not just in how it works, but in how little attention it requires. From onboarding onward, the experience has been defined by accessibility, clear communication, and a straightforward process. “I have great confidence in the approval and release process. The representatives are friendly, helpful, and knowledgeable, and this gives me a sense of security.” — Robin Sudo, Office Manager / Corporate Secretary, DLP Resources Inc. This level of support ensures that disclosure is handled correctly without requiring constant oversight. It also makes the process easy to manage with confidence. The Result: Confidence Without Extra Work Today, disclosure at DLP Resources is handled with minimal administrative effort. Key outcomes include: Reduced time spent managing cross-border posting Greater confidence that disclosures are handled correctly Consistent execution across distribution and regulatory visibility Ongoing support from a responsive and knowledgeable team For a role centered on accuracy and responsibility, this provides a meaningful advantage. A Practical Approach to Cross-Border Disclosure In modern markets, maintaining visibility across both Canadian and U.S. markets does not need to introduce additional complexity. For DLP Resources, cross-border disclosure is handled through a single, consistent workflow that works the same way every time. As a result, press releases are distributed and posted across jurisdictions through a single workflow, without additional coordination or manual effort.

Disclosure Intelligence Series How disclosure works in modern capital markets When a press release is distributed, most issuer teams treat the process as complete. In reality, this marks the point at which AI systems begin processing, interpreting, and positioning the announcement for the market. To better understand how press releases are processed in modern markets, TMX Newsfile analyzed AI crawler activity across a 72-hour window following press release distribution. The study tracked approximately 220 releases distributed across TMX Newsfile’s global distribution network during a peak news cycle. This allowed us to observe how quickly press releases are processed, how widely they are distributed, and which AI systems are interpreting them. The findings point to a structural shift in how information is consumed. Disclosure is no longer only consumed by people. It is also processed by AI systems. This study answers three operational questions for issuer teams: How quickly are press releases processed by AI systems? How do AI systems use news releases once they are captured? Which AI-driven platforms process press releases first? The results show that AI ingestion is immediate, global, and highly concentrated within the first 24 hours of release. AI Processing Speed and the 24-Hour Visibility Window Speed is one defining factor in how press releases are interpreted in modern markets. Once a press release is distributed, AI systems begin processing it almost immediately, establishing an initial understanding of the announcement that can influence how it is surfaced, summarized, and referenced. To quantify this timing, we analyzed AI crawler activity over a 72-hour period following the distribution of approximately 120 press releases across TMX Newsfile’s global distribution network. The results show a highly concentrated window of activity within the first 24 hours. Figure 1: AI crawler activity over a 72-hour post-release window A three-day view of AI crawler activity shows that 75.8% of all observed AI activity occurs within the first 24 hours after publication. The data also reveals a rapid decline in activity after the initial visibility window. The majority of activity occurs on Day 1 Activity declines significantly after the initial window By Day 3, AI visibility is materially reduced This defines a clear AI visibility window, where the first 24 hours are driven by active AI processing, interpretation, and positioning of press releases in the market. How AI Systems Process Press Releases AI systems process press releases for two fundamentally different purposes. Some systems retrieve press release information in real time to answer user questions, while others continuously ingest press releases to train future AI models and improve long-term understanding of companies, sectors, and market events. To better understand this behavior, TMX Newsfile analyzed the balance between grounding activity and training activity during the first 72 hours after a press release is issued. Figure 2: Grounding vs. training AI activity over a 72-hour window The results show a clear distinction between real-time AI retrieval and longer-term model training. On Day 1: 92.7% of AI activity is training based, where large-scale crawlers collect press release data to build and improve future AI models 7.3% is grounding based, where systems retrieve information in response to user questions Grounding activity declines rapidly after the initial visibility window, falling by approximately 92% from 571 hits on Thursday to just 45 by Saturday. Training activity also declines over time, but remains substantially higher than grounding activity, decreasing from 7,293 hits on Thursday to 808 by Saturday. This reveals an important shift in how press releases are processed by AI systems. Both grounding and training activity decline after Day 1, but training activity remains substantially higher throughout the 72-hour window. As a result, the first 24 hours play a critical role in shaping how AI systems understand and retain a press release. Which AI Platforms Process Press Releases First? Figure 3: AI platform activity during the first 24 hours AI processing activity on Day 1 comes from a globally distributed mix of platforms, including systems linked to: ByteDance / Doubao (China) OpenAI (United States) Meta (United States) Amazon (United States) Baidu / Ernie Bot (China) While this chart reflects the most active AI platforms observed during the study window, major platforms such as Google, Microsoft, Anthropic, and X also actively process press release content across TMX Newsfile’s network. The results show that press releases are rapidly processed across major AI ecosystems in both North America and Asia within hours of publication. This suggests that corporate announcements are no longer confined to traditional investor audiences or domestic distribution channels. Instead, press releases are increasingly being interpreted, categorized, and retained by globally distributed AI systems almost immediately after release. What This Means for Disclosure Strategy AI systems begin processing press releases immediately after publication, with the highest concentration of activity occurring within the first 24 hours. As a result, visibility is no longer determined solely by where a press release is distributed. It is also shaped by how AI systems interpret and categorize information during the first hours after release. Timing AI activity is most concentrated immediately after publication, making the first release window critical for visibility. Structure Information must be clearly organized to support both human interpretation and machine processing. Consistency When press releases, filings, and supporting information are managed separately, inconsistencies can emerge during the period when AI systems are actively processing and categorizing information. In modern markets, the first 24 hours after a press release is published play a major role in shaping AI visibility. For issuer teams, this increases the importance of clarity, consistency, and execution at the moment of release, when AI systems across multiple global platforms are actively processing and categorizing information. Once released, a press release becomes part of a broader AI-driven ecosystem that interprets, categorizes, and stores information across digital platforms.

Disclosure Intelligence Series How disclosure works in modern capital markets A May 2026 TMX Newsfile analysis found that mining and energy press releases generated higher levels of AI activity per release than Technology & Innovation announcements. The study analyzed AI crawler activity across approximately 220 press releases distributed through TMX Newsfile’s network over a 72-hour period. Results showed that AI systems are actively processing mining and energy press releases at scale. AI Activity by Industry Figure 1: Energy & Resources generated the highest level of AI activity per press release in the study sample. To better understand how AI activity varies across industries, TMX Newsfile analyzed average AI interactions per release across multiple sectors. The results show: Energy & Resources: 77.2 AI interactions per release (73 releases) Technology & Innovation: 66.8 AI interactions per release (13 releases) Financial Services: 19.3 AI interactions per release (91 releases) While Financial Services generated the largest number of releases in the sample, Energy & Resources recorded the highest level of AI activity per individual announcement. Structured Disclosure and AI Activity Mining and energy press releases often contain highly structured, quantitative information, including: Technical drill results Production figures Measurable outputs Standardized project milestones These characteristics may help explain the higher levels of AI activity observed in the study. Structured information is generally easier for AI systems to categorize, interpret, and retain across large datasets. Resource sector announcements generated the highest levels of AI activity observed in the study. AI Activity Extends Beyond Public Markets The study also showed that AI activity extends beyond publicly listed issuers. Within the same dataset: Public company releases averaged 69.0 AI interactions per release Private company releases averaged 27.6 AI interactions per release The findings suggest that AI systems actively process corporate announcements regardless of listing status. Even without an exchange listing, private companies raising capital or building market visibility are already part of the broader AI information ecosystem. Implications for Mining and Energy Companies For mining and energy issuers, press releases now reach multiple audiences simultaneously: Investors Analysts Media AI systems AI systems increasingly process, categorize, and retain press release information shortly after publication, shaping how information is later surfaced across digital platforms. Because resource sector disclosure is often highly technical and data-rich, structure and clarity become increasingly important. Consistent terminology, organized formatting, and clearly presented information help support accurate interpretation across both human and AI audiences. The audience for corporate disclosure continues to expand. It now includes AI systems that process, categorize, and retain information across broader digital ecosystems. For mining and energy companies, effective disclosure is no longer only about communicating information to the market. It is also about how clearly that information can be interpreted across digital systems after distribution.

According to a PwC report, 72% of business leaders termed AI as a “business advantage.” Artificial Intelligence is advancing rapidly, and professionals in investor relations are quickly adopting AI prompts for IR and technologies to improve their strategies. To fully leverage this tech in your field, crafting precise AI prompts is crucial for targeted and successful outcomes. In the constantly evolving AI landscape, IR professionals must excel at creating precise AI prompts for effective financial reporting, investor engagement and crisis management. This article offers AI prompts to help IR professionals enhance outcomes and address communication needs more effectively. Utilize the prompts below to assist with tasks and gain valuable insights. They do not require the input of sensitive or confidential corporate information. AI Prompts for Investor Relations AI prompts for financial reporting & investor engagement AI prompts for strategic investor relations management AI prompts for compliance & crisis management AI prompts for targeted messaging and IR initiatives AI prompts for IR training & development AI Prompts for Investor Relations As an investor relations professional, you can use AI in many different ways. For example, AI can enhance your financial reporting precision, improve investor engagement or ensure expert compliance in communications. Just last month, Disney’s CEO Bob Iger expressed openness to using AI-driven avatars for earnings calls, while Box CEO Aaron Levie demonstrated AI’s swift aggregation and analysis of earnings information. Matt Joanou, Forbes AI Prompts for Financial Reporting and Investor Engagement Financial reporting is vital for any business. To enhance it and engage investors effectively, we’ve gathered AI prompts that enhance key aspects such as summarizing performance, crafting engaging communications, and addressing inquiries. These prompts aim to improve transparency and strengthen investor relations. 1. Summarize key points from [company’s] last quarter financial performance. 2. Summarize [company’s] major achievements and future outlook from its latest earnings report. 3. Create potential questions investors might ask about [company’s] recent quarterly performance and draft concise, informative responses. 4. Create a script for addressing FAQs in [company’s] earnings call. 5. Create an engaging introduction for [company’s] annual report. 6. What are the key industry benchmarks of the [industry type] industry? 7. Draft an engaging email for [company website address’s] quarterly investor newsletter, incorporating any details about [company] for relevance. 8. Generate a list of topics for [company website address’s] next investor webinar. 9. Develop investor personas for tailored communication strategies for [company website address’s] [key business]. 10. Draft an agenda for [company website address’s] annual shareholder meeting to reflect the current issues, strategic priorities, and operational focus of [company website address]. 11. Generate a summary of shareholder feedback for [company]. AI Prompts for Strategic IR Development and Feedback Analysis Did you know that 75% of investors use digital sources to make investment decisions? Social media for investor relations or any form of monitoring, listening and analysis across different channels will provide you with more tools to enhance your IR strategy. If you are looking for effective investor relations strategies then the following AI prompts can help. 12. Explain financial hedging methods for [company] [(company stock exchange: company stock ticker)] against [industry] price volatility, including current specific instruments and stock exchange examples. 13. Suggest the most specific, actionable and innovative IR strategies for a [industry] startup. 14. Plan a communication timeline for a major merger announcement. 15. Identify current market trends for strategic IR planning in the [industry description] industry. 16. Compile key takeaways from recent investor surveys for [company] [(company stock exchange: company stock ticker)]. 17. Generate a report format for quarterly investor feedback for [company] [(company stock exchange: company stock ticker)]. 18. Analyze investor communication trends for improved strategies for [company] [(company stock exchange: company stock ticker)]. 19. Analyze recent news articles and social media trends about [company’s] industry to identify investor sentiments and concerns. 20. Summarize public financial and operational data of [company’s] key competitors to highlight [company’s] competitive advantages. 21. Suggest innovative strategies for [company’s] investor engagement in the current market scenario, based on publicly available industry trends. 22. Create detailed investor personas to tailor [company website address’s] communication and investor materials effectively. AI Prompts for Compliance and Crisis Management in IR AI can help you navigate regulatory changes, update ESG initiatives and develop crisis responses or lessons for dealing with investors in a crisis. This ensures transparency and effective investor communication in many varied scenarios. 23. Identify upcoming regulatory changes in the [industry description] industry and outline a corporate communication strategy incorporating these changes. 24. Compose an update on ESG initiatives. 25. Report on emerging regulatory trends in the [industry type] industry. 26. Create a stock market fluctuation response plan for [company] [(company stock exchange: company stock ticker)], focusing on actions specific to the [industry description] industry. 27. Script a sensitive communication to investors about a management change [company] [(company stock exchange: company stock ticker)]. 28. Create scenarios and responses for hypothetical market crises to [company] [company stock exchange: company stock ticker]. 29. Develop a concise ESG strategy overview for investor briefings, focusing on major sustainability achievements, social initiatives, and governance practices for [company]. 30. Create detailed investor personas to tailor [company’s] communication and investor materials effectively. 31. Provide guidelines for crafting risk disclosures in [company’s] financial reports, reflecting current market conditions and regulatory requirements. AI Prompts for Targeted Messaging and IR Initiatives Connecting with investors and shareholders is at the top of the list of priorities for many. In fact, AI can help you tailor messaging to specific audiences. Automating some of these tasks will free up time to focus on your full list of priorities. Plus, don’t forget to improve your investor relations website. 32. Develop a personalized message to long-term investors of [company] [(company stock exchange: company stock ticker)]. 33. Suggest enhancements for our investor relations website content to improve investor engagement and information accessibility: [insert investor relations website address]. 34. Create an investor update on the following R&D progress: [insert previous corporate stock exchange compliance announcement]. 35. Segment [company’s] investors for customized messaging. 36. Plan an IR campaign with timelines and important details for a new sustainability project. 37. Outline a year-end message for [company] highlighting company milestones over the last year. 38. Predict the impact of [company’s] IR campaigns on investor perception. 39. Draft a structured agenda for [company’s] annual shareholder meeting that includes major business updates, shareholder voting items, and Q&A sessions. AI Prompts for IR Training and Development Implementing training and development in your IR department will pay dividends. Ensure that your whole team progresses and can collaborate to share skills with one another. Stay up-to-date with the latest technologies and cultivate a culture of continuous learning. 40. Suggest topics for an IR team training session. 41. Draft an IR best practices guide for new team members. 42. Develop a curriculum on emerging IR technologies. AI is transforming investor relations, offering new efficiencies in financial reporting and engagement. Embrace these AI prompts to stay ahead in this evolving field. Let’s innovate together and shape the future of investor relations.

Just ahead of COP28, reports of an intriguing trend emerged: over 80% of investors now prioritize ESG factors, highlighting the need for clearer sustainability reporting. At the forefront of this shift is Artificial Intelligence (AI), revolutionizing AI tools for ESG reporting and making it more transparent and efficient. AI is benefiting both investors and companies by helping to collect, analyze and report ESG data. The new ESG landscape after COP28 How AI Transforms ESG Reporting Top 8 AI Tools for ESG Reporting in 2024 Case studies: AI's real impact on ESG Benefits of AI in ESG Reporting Challenges in AI for ESG Reporting Post-COP28 AI Investment Trends The new ESG landscape after COP28 Post-COP28, the ESG landscape is undergoing a significant shift, with a renewed focus on achieving the crucial 1.5°C global warming temperature limit. This heightened environmental goal is compelling businesses to adopt more stringent measures in line with these objectives. In response to this change, the demand for transparent and accurate ESG reporting will surge. Investors are seeking clear evidence of how companies are contributing to these new global climate goals, especially in reducing their carbon footprint and enhancing social governance. Artificial Intelligence (AI) has emerged as a key player in addressing these reporting needs. For instance, AI can process complex data efficiently. Also, it can provide companies with the tools to report more accurately on key ESG metrics, including carbon emissions and energy efficiency, aligning with the 1.5°C target. How AI Transforms ESG Reporting AI is transforming ESG reporting by improving data accuracy and streamlining analysis. In addition, it is offering predictive insights, natural language processing (NLP) and the identification of key performance indicators. Facilitating regulatory compliance is another area where AI can be of assistance. For example, AI can simplify new compliance rules, such as the new Form N-PX rules for 13F filers. These AI features that transform ESG reporting advance sustainable decision-making and strategic focus. Top 8 AI Tools for ESG Reporting in 2024 Arabesque S-Ray - applies AI to assess sustainability performance and translate ESG metrics into scores. Truvalue Labs - uses AI to generate real-time ESG data by analyzing a wide range of sources. Boosted AI - integrates ESG data into its machine learning platform to produce boosted insights for investment decision-making processes. Clarity AI - leverages AI to deliver detailed ESG insights for companies and investment portfolios. Accern - harnesses AI to extract and interpret information from various sources and streamlines complex data workflows. Owl Analytics - applies AI to offer advanced ESG data and analytics, focusing on sustainable and socially responsible investing. Datamaran - utilizes AI for automated risk management, helping in identifying and monitoring ESG risks. RepRisk - provides ESG risk data and business intelligence through its AI-powered tool. Case studies: AI's real impact on ESG Artificial Intelligence is not just a buzzword in the world of ESG reporting - it's a game-changer. This is seen in the success stories of companies integrating AI into their sustainability initiatives. Success Story - Freeport-McMoRan Take the example of Freeport-McMoRan, a leading international mining company, which has used AI to make their mining operations smarter and safer. They developed a tool with WWT, which helped them use big data to make better decisions and improve how they work. This tool showed how AI can really help a business work better and care for the environment and people. Success Story - Accenture Another example is international business management consulting company Accenture, which tackles ESG data challenges with a strategy focused on standardized reporting. They use AI for data processing and leverage alternative data sources. Their approach aims to make ESG data more accurate and useful for better decision-making in sustainability. Analysis of Results: Accenture's approach to ESG reporting involves making data more reliable and actionable, which is crucial for sustainable practices. Similarly, Freeport-McMoRan's AI use in mining likely leads to more responsible and efficient operations, aligning with ESG goals. Both cases show how AI can transform ESG reporting, helping companies to be more environmentally and socially responsible. Benefits of AI in ESG Reporting Artificial Intelligence (AI) in ESG reporting stands out for its accuracy and timeliness. It minimizes errors in data analysis and delivers insights much faster than traditional methods. This advancement in AI-driven ESG reporting greatly benefits companies and investors. Companies can more easily comply with complex regulations (compliance), while investors get a transparent view of ESG practices, leading to smarter investment decisions. Challenges in AI for ESG Reporting Using AI for ESG reporting faces two main challenges. First, different companies report varied data, leading to inconsistent ESG measurements. Additionally, the absence of standardized frameworks makes it hard to compare data across companies. Second, privacy and ethics are key concerns. Ensuring data privacy and preventing bias in AI algorithms are crucial for accurate and fair ESG reporting. Post-COP28 AI Investment Trends Looking ahead, there's a focus on getting ready for more advanced AI technologies and adapting to stricter regulations. At the same time, there's an opportunity to leverage new AI-driven trends in ESG, especially following the developments from COP28. Big Climate Funds: A huge $30 billion fund for climate projects shows a push towards big investments in fighting climate change​​. Smart ESG Reporting: More use of AI for better and quicker ESG reports, helps companies and investors make eco-friendly choices​​ Clean Energy Growth: Agreements to greatly increase renewable energy, signals a move towards investing in green energy sources​​. Investing in Farming for the Climate: The AIM for Climate initiative's focus on sustainable agriculture points to more money going into eco-friendly farming methods​​. Cutting Methane in Energy: Oil and gas companies' commitments to lower methane emissions reflects a shift towards cleaner energy practices​​. Climate-Friendly Food Production: A focus on investing in sustainable food systems will improve how food is grown and supplied and promote more climate-resilience​​. AI's role in ESG reporting is more crucial than ever, especially following COP28. It's about enhancing accuracy, efficiency, and making informed decisions for a sustainable future. As we move forward, let's embrace these AI advancements to elevate our environmental and social responsibilities.

Are you looking for great sustainability press release examples? Ones that can give you inspiration and ideas for your own sustainability press releases? Well, the Barbie brand's sustainability news releases will give you the inspiration that you need. We've curated the following sustainability press release examples just for you. Why You Should Send Out ESG News The numbers are backing up why you should be concerned with sustainability and sending out more ESG news. For example, according to PwC’s Asset and Wealth Management Revolution 2022 report, global ESG-focused institutional investment is expected to soar 84% to US$33.9 trillion in 2026. Furthermore, PwC states that Canadian organizations are talking about ESG more seriously but unprepared for upcoming mandatory reporting requirements. In addition to this, the SEC is pushing for more ESG reporting. As sustainability reporting requirements are expected to rise, now is a good time to hone in on perfecting your sustainability press releases. Environmental Sustainability Press Release Example Mattel's environmental press release announces its first fashion doll line made from recycled ocean-bound plastic. Not only is the company committed to the environment, but it wants you to know about it. The Future of Pink is Green campaign is displayed front and centre in the press release with a high quality graphic of three environmentally-friendly Barbie dolls. View complete environmental press release example This environmental campaign also features the Dr. Jane Goodall Barbie. Along with this, Barbie has a roots & shoots partnership with the Dr. Jane Goodall Institute, promoting conservation and animal welfare. Mattel is committed to protecting the planet through a series of eco-friendly initiatives. Furthermore, it has a goal of creating 100% recycled, recyclable or bio-based plastic materials in both products and packaging by 2030. Diversity & Inclusion Press Release Samples Out of all the sustainability and ESG areas, Barbie sends out the most press releases about its diversity and inclusion efforts. The following press release introduces the first doll with Down syndrome. View complete media release example Research shows that 35% of an employee’s emotional investment in their work and 20% of their desire to stay within their existing company depends on how included they feel in their workplace. Companies that embrace D&I develop products and company operations based on these principles. The following press release highlights Barbie's focus on gender diversity. As well, the press release explains about an important collaboration with MTV and provides a personal touch with a quote from Lisa McKnight, SVP and Global Head of Barbie & Dolls, Mattel. View complete press release sample Philanthropy Press Release Samples Barbie sends out press releases announcing collaborations with various charitable organizations such as Save the Children and Habitat for Humanity International. For instance, the following press release announces how Barbie helps to build homes during The Barbie Dreamhouse 60th anniversary. View complete news release example Moreover, special edition dolls support various charitable causes and the company promotes STEM (Science, Technology, Engineering, and Mathematics) education and careers for girls. Another initiative known as the Barbie Dream Gap Project is committed to helping girls reach their full potential. In the following press release, Barbie pledges to donate a doll to the children of the first responders of COVID-19. This happens every time an eligible career doll is sold. This press release clearly communicates Barbie's charitable efforts that directly tie into important events. View complete sample press release Barbie's sustainability press releases clearly convey the corporate ESG messages. This is achieved with clear and descriptive messaging, powerful graphics, great headlines and effective sustainability campaigns. Feature Image by Freepik

For global mining companies, disclosure does not happen in a single market or a single time zone. It is continuous, time-sensitive, and often coordinated across continents. Adyton Resources is a TSX Venture-listed exploration company operating in Papua New Guinea, with its team based in Australia. In this environment, disclosure is not just about generating information. It is about executing it with precise timing and coordination across time zones. “The ability to file 24/7 with immediate support is helpful, as our staff are in Australia.” — Chirag Patel, CFO, Adyton Resources Corporation Global Disclosure from Australia Operating across jurisdictions introduces more than regulatory requirements. It introduces operational complexity. Adyton’s team operates primarily out of Australia while maintaining Canadian listing obligations and communicating with a global investor base. This creates a constant need to coordinate: time zones regulatory systems and disclosure timelines In this environment, delays are not just inconvenient. They can introduce risk. About Adyton Resources Adyton Resources is a Canadian public company focused on the development of gold and copper resources in Papua New Guinea. Its projects are located within the Pacific Rim of Fire, one of the world’s most resource-rich mineral belts. The company holds existing resources of over 2.1 million ounces of gold and operates in geological settings that are open, scalable, and prospective for further discovery. As a TSX Venture-listed issuer, Adyton manages ongoing disclosure obligations while engaging investors across multiple markets. The Challenge Before working with TMX Newsfile, cost and efficiency were key considerations in Adyton’s disclosure process. Traditional distribution services introduced: higher fees limited flexibility in pricing and execution As the company evaluated alternatives, the goal was to find a more efficient and cost-effective approach to distribution. The Solution: Coordinated Disclosure Execution TMX Newsfile provides a more direct and cost-effective way to manage press release distribution and regulatory filings. The focus is on simplifying how disclosure is executed. Submissions are easy to complete, and support is available when needed, regardless of time zone. TMX Newsfile also supports distribution beyond North America, including Australasia, helping extend Adyton’s investor reach. “Everyone I've worked with at Newsfile is knowledgeable, gets the job done for us, and is well-informed. Solutions are straightforward, and the onboarding itself was very easy.” — Chirag Patel, CFO, Adyton Resources Corporation Why It Works In cross-border environments, consistency and responsiveness matter more than process complexity. By simplifying how press release distribution and regulatory filings are managed, Adyton is able to execute disclosure more efficiently across time zones. This reduces delays and supports more consistent and reliable delivery of information to the market. The Result Today, disclosure is executed with greater consistency and confidence. Key outcomes include: Faster and more predictable disclosure timelines Reduced friction across distribution and filings Greater confidence in disclosure, supported by editorial feedback from the newsroom Improved coordination across time zones 24/7 support across time zones Distribution support extending into Australasia For a company operating across continents, these improvements make disclosure more reliable and easier to manage. A Practical Advantage in Mining Markets In mining, where announcements can materially impact valuation, timing and clarity are critical. Results are often interpreted immediately by the market and this makes coordination across disclosure channels essential. For Adyton Resources, simplifying press release distribution and regulatory filings improves the stability and reliability of its disclosure process. In global markets, effective disclosure is not just about meeting requirements. It is about executing with precision.