
How to turn crisis response into community trust
Buckle up and bookmark this page for future reference—you never know when you might need it.
Why it's important.
Universities face events that can escalate quickly and without warning—from extreme weather and public health emergencies to campus safety incidents.
Clear, timely communication during these moments is essential to protect the university community and maintain trust.
The idea.
You can't control the crisis, but you can control the communication. And in a crisis, your message is your leadership.
The institutions that thrive are the ones that prepare, unify and speak with purpose—before, during, and after the storm.
Here's how.
University of Miami's plan works because it makes communications a core function of crisis response, not just an afterthought. Success takes:
Unified messaging from a center-led comms model.
Real-time coordination between emergency management and leadership.
Social listening tools to surface sentiment and squash misinformation.
Multichannel outreach, from internal dashboards to emergency texts to FAQ pages.
A people-first mindset that values humility, empathy, and clarity in every message.
An example.
As Hurricane Ian approached Florida in 2022, leaders at the University of Miami didn't scramble; they activated a decisive plan.
The result: Unified action, a faster response, and strengthened trust across the campus—and the community.
Teams across departments used coordinated and pre-approved messaging to ensure clarity.
Schools and colleges paused all non-crisis content and turned readers toward official updates.
AI -supported listening tools flagged emerging misinformation and reader sentiment in real time.
The result: Unified action, a faster response, and strengthened trust across the campus—and the community.
What this means.
Your response to a crisis should be more than a canned statement—it should be the result of collaboration, empathy, and thoughtful decision-making.
Looking ahead.
A disaster-prone world brings more frequent and more complex crises to higher education.
University of Miami's crisis comms case study, built on its 100 years of history, sets a benchmark for industry leaders.
The takeaway.
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CNET
a few seconds ago
- CNET
AI Is Taking Over Your Search Engine. Here's a Look Under the Hood
For decades, the way we find information on the internet changed only in small ways. Doing a traditional Google search today doesn't feel all that different from when, in the 1990s, you would Ask Jeeves. Sure, a lot has changed under the hood, the results are likely far more relevant and the interface has some new features, but you're still typing in keywords and getting a list of websites that might hold the answer. That way of searching, it seems, is starting to go the way of AltaVista, may it rest in peace. In May, Google announced the rollout of its new AI Mode for search, which uses a generative AI model (based on the company's Gemini large language model) to give you conversational answers that feel a lot more like having a chat and less like combing through a set of links. Other companies, like Perplexity and OpenAI, have also deployed search tools based on gen AI. These tools, which merge the functionality of a chatbot and a traditional search engine, are quickly gaining steam. You can't even escape AI by doing just a regular Google search: AI Overviews have been popping up atop those results pages since last year, and about one in five searches are now showing this kind of summary, according to a Pew Research Center report. I'm surprised it's not even more than that. These newfangled search tools feel a lot like your typical chatbot, like ChatGPT, but they do things a little differently. Those differences share a lot of DNA with their search engine ancestors. Here's a look under the hood at how these new tools work, and how you can use them effectively. Everything Announced at Google I/O 2025 Everything Announced at Google I/O 2025 Click to unmute Video Player is loading. Play Video Pause Skip Backward Skip Forward Next playlist item Unmute Current Time 0:13 / Duration 15:40 Loaded : 6.33% 00:13 Stream Type LIVE Seek to live, currently behind live LIVE Remaining Time - 15:27 Share Fullscreen This is a modal window. Beginning of dialog window. Escape will cancel and close the window. Text Color White Black Red Green Blue Yellow Magenta Cyan Opacity Opaque Semi-Transparent Text Background Color Black White Red Green Blue Yellow Magenta Cyan Opacity Opaque Semi-Transparent Transparent Caption Area Background Color Black White Red Green Blue Yellow Magenta Cyan Opacity Transparent Semi-Transparent Opaque Font Size 50% 75% 100% 125% 150% 175% 200% 300% 400% Text Edge Style None Raised Depressed Uniform Drop shadow Font Family Proportional Sans-Serif Monospace Sans-Serif Proportional Serif Monospace Serif Casual Script Small Caps Reset Done Close Modal Dialog End of dialog window. Close Modal Dialog This is a modal window. This modal can be closed by pressing the Escape key or activating the close button. Close Modal Dialog This is a modal window. This modal can be closed by pressing the Escape key or activating the close button. Everything Announced at Google I/O 2025 Search engines vs. AI search: What's the difference? The underlying technology of a search engine is kinda like an old library card catalog. The engine uses bots to crawl the vast expanses of the internet to find, analyze and index the endless number of web pages. Then, when you do a search to ask who played Dr. Angela Hicks on ER, because you're trying to remember what else you've seen her in, it will return pages for things like the cast of ER or the biography of the actor, CCH Pounder. From there, you can click through those pages, whether they're on Wikipedia or IMDB or somewhere else, and learn that you know CCH Pounder from her Emmy-winning guest appearance on an episode of The X-Files. "When customers have a certain question, they can type that question into Google and then Google runs their ranking algorithms to find what content is the best for a particular query," Eugene Levin, president of the marketing and SEO tool company Semrush, told me. Generally, with a traditional search, you have to click through to other websites to get the answer you're looking for. When I was trying to figure out where I recognized CCH Pounder from, I clicked on at least half a dozen different sites to track it down. That included using Google's video search -- which combs an index of videos across different hosting platforms -- to find clips of her appearance on The X-Files. Google announced AI Mode at its I/O developer conference in May. Google/Screenshot by Joe Maldonado/CNET These multiple searches don't necessarily have to happen. If I just want to know the cast of ER, I can type in "cast of ER" and click on the Wikipedia page at the top. You'll usually find Wikipedia or another relevant, trustworthy site at or near the top of a search result page. That's because a main way today's search algorithms work is by tracking which sites and pages get most links from elsewhere on the web. That model, which "changed the game for search" when Google launched it in the 1990s, was more reliable than indexing systems that relied on things like just how many times a keyword appeared on a page, said Sauvik Das, associate professor at Carnegie Mellon University's Human-Computer Interaction Institute. "There's lots of cookie recipes on the web, but how do you know which ones to show first?" Das said. "Well, if a bunch of other websites are linking to this website for the keywords of 'cookie recipe,' that's pretty difficult to game." AI-powered search engines work a little differently, but operate on the same basic infrastructure. In my quest to see where I recognized CCH Pounder from, I asked Google's AI Mode, literally, "Where do I recognize the actress who plays Dr. Angie Hicks on ER from?" In a conversation that felt far more like chatting with a bot than doing searches, I narrowed it down. The first result gave me a list of shows and movies I hadn't seen, so I asked for a broader list, which featured her guest appearances on other shows. Then I could ask for more details about her X-Files appearance, and that narrowed it down. While the way I interacted with Google was different, the search mechanisms were basically the same. AI Mode just used its Gemini model to develop and process dozens of different web searches to gather the information needed, Robby Stein, vice president of product for Google Search, told me. "A user could've just queried each of those queries themselves." Basically, AI Mode did the same thing I did, just a lot faster. So many searches, so little time The approach here is called "query fan-out." The AI model takes your request and breaks it down into a series of questions, then conducts searches to answer those components of the request. It then takes the information it gathers from all those searches and websites and puts it together in an answer for you. In a heartbeat. Those searches are using the same index that a traditional search would. "They work on the same foundation," Levin said. "What changes is how they pull information from this foundation." This fan-out process allows the AI search to pull in relevant information from sites that might not have appeared on the first page of traditional search results, or to pull a paragraph of good information from a page that has a lot more irrelevant information. Instead of you going down a rabbit hole to find one tiny piece of the answer you want, the AI goes down a wide range of rabbit holes in a few seconds. "They will anticipate, if you're looking for this, what is the next thing you might be interested in?" Levin said. Read more: AI Essentials: 29 Ways You Can Make Gen AI Work for You, According to Our Experts The number of searches the AI model will do depends on the tool you're using and on how complicated your question is. AI Mode that uses Google's Deep Search will spend more time and conduct more searches, Stein said. "Increasingly, if you ask a really hard question, it will use our most powerful models to reply," Stein said. The large language models that power these search engines also have their existing training data to pull from or use to guide their searches. While a lot of the information is coming from the up-to-date content it finds by searching the web, some may come from that training data, which could include reams of information ranging from websites like this one to whole libraries of books. That training data is so extensive that lawsuits over whether AI companies actually had the right to use that information are quickly multiplying. (Disclosure: Ziff Davis, CNET's parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) AI search isn't just a chatbot Not relying on training data is one thing that sets an AI-powered search engine apart from a traditional chatbot, even though the underlying language model might be largely the same. While ChatGPT Search will scour the internet for relevant sites and answers, regular ChatGPT might rely on its own training data to answer your question. "The right answer might be in there," Das said. "It might also hallucinate a likely answer that isn't anywhere in the pre-training data." The AI search uses a concept called retrieval-augmented generation to incorporate what it finds on the internet into its answer. It collects information from a source you point it to (in this case, the search engine index) and tells it to look there instead of making something up if it can't find it in its training data. "You're telling the AI the answer is here, I just want you to find where," Das said. "You get the top 10 Google results, and you're telling the AI the answer is probably in here." Perplexity offers AI-powered search through its app and through a newly announced browser. Stefani Reynolds/Bloomberg via Getty Images Can you really trust AI search results? These AI-powered search tools might be more reliable than just using a chatbot itself, because they're pulling from current, relevant information and giving you links, but you still have to think critically about it. Here are some tips from the experts: Bring your human skepticism Consider how bad people are at telling when you're sarcastic on the internet. Then think about how bad a large language model might be at it. That's how Google's AI Overviews came up with the idea to put glue on pizza -- by pulling information from a humorous Reddit post and repeating it as if it were real culinary advice. "The AI doesn't know what is authentic and what is humorous," Das said. "It's going to treat all that information the same." Remember to use your own judgement and look for the sources of the information. They might not be as accurate as the LLM thinks, and you don't want to make important life decisions based on somebody's joke on an internet forum that a robot thought was real. AI can still make stuff up Even though they're supposed to be pulling from search results, these tools can still make things up in the absence of good information. That's how AI Overviews started creating fake definitions for nonsensical sayings. The retrieval-augmented generation might reduce the risk of outright hallucinations but doesn't eliminate it, according to Das. Remember that an LLM doesn't have a sense of what the right answer to a question is. "It's just predicting what is the next English word that would come after this previous stream of other English words or other language words," Das said. "It doesn't really have a concept of truthiness in that sense." Check your sources Traditional search engines are very hands-off. They will give you a list of websites that appear relevant to your search and let you decide whether you want to trust them. Because an AI search is consolidating and rewriting that information itself, it may not be obvious when it's using an untrustworthy source. "Those systems are not going to be entirely error-free, but I think the challenge is that over time you will lose an ability to catch them," Levin said. "They will be very convincing and you will not know how to really go and verify, or you will think you don't need to go and verify." But you can check every source. But that's exactly the kind of work you were probably hoping to avoid using this new system that's designed to save you time and effort. "The problem is if you're going to do this analysis for every query you perform in ChatGPT, what is the purpose of ChatGPT?" Levin said.


Entrepreneur
a few seconds ago
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Forbes
a minute ago
- Forbes
A Conversation With Verizon Business Chief Product + Marketing Officer Iris Meijer On Synching The Product + Marketing Functions To Innovate The Customer Experiences Of Tomorrow
The marketing function is undergoing many changes in today's environment. Firstly, marketers must demand a seat at the table in ways never done before, as they are required to not just market, but ultimately act as change agents driving a company's perpetual transformation. To do this, CMOs must reimagine what it means to be truly customer-centric, while working to reinvent customer understanding. Additionally, they also must remove product development out of individual siloes and embrace it as a critical component of the marketing organization. Verizon Business Chief Product + Marketing Officer Iris Meijer On Synching The Product + Marketing ... More Functions To Innovate The Customer Experiences Of Tomorrow As a result of these significant sea changes, I wanted to speak to someone at the forefront of all of these trends, who understands the value of brand, along with an ability to use technology with specific intentionality to create customer experiences that delight and engage. Iris Meijer is Chief Product and Marketing Officer of Verizon Business. She is an industry veteran who has previously held senior roles at leading organizations such as Vodafone and Nokia. Following is a recap of our conversation: Howard: There are so many changes taking place in marketing today. One which you shared when we last spoke that I found particularly interesting was your feeling that marketing must be in the driver's seat for transformation efforts to truly be successful. Can you explain this further? Meijer: Marketing plays a critical role in driving successful transformation efforts because it possesses an unparalleled understanding of customer needs and market dynamics. As CMOs, our role is evolving to be strategic partners on the commercial realities of the business, going hand-in-hand with brand building. By being in the driver's seat, we ensure that all transformation initiatives are customer-centric, designing every journey, optimization, or new solution to delight our customers and address their evolving needs, which ultimately leads to higher customer satisfaction and loyalty. Our deep dive into data, technology, and advanced AI models allows us to go beyond surface-level insights, creating foresight into changing customer expectations. We are increasingly deploying AI and new technology tools to predict future customer behavior. For example, in Verizon Business, we're leveraging GenAI to improve customer experience and employee experience, increasing efficiency and sales velocity through data orchestration that tracks the customer lifecycle as well as through content generation, analytics, business operations, employee productivity, and coaching. This is crucial for anticipating needs and offering tailored solutions. The impact of this marketing-led approach extends beyond customer satisfaction. By driving these transformations, we see tangible business benefits such as reduced churn, increased revenue through more relevant offerings, attached solutions, and significant cost reductions due to optimized operations. This commitment to measurable improvement solidifies marketing's strategic importance in overall business transformation. Howard: Tell me about why you recently united product and marketing at Verizon Business? Meijer: In 2024, we strategically united product and marketing at Verizon Business to achieve a more cohesive and synergistic approach to serving our customers, focusing on the commercial performance of our portfolio and ultimately driving profitable growth. This decision was rooted in the recognition that a unified Product & Marketing organization can more effectively develop and deliver successful products to our customers. It creates more opportunities for innovating new commercially successful products and experiences that can truly transform our customers' businesses, whether they are small business owners, global enterprise customers or public sector customers, by delivering on each segment's distinct needs. This strategic alignment means that the feedback loop between customer insights from our marketing science teams and the continued listening by our frontline employees is immediately brought together and actioned for the ongoing development of our product portfolio. By having product and marketing teams work side-by-side, we ensure that new solutions are not only technically sound but also directly address identified customer needs and market gaps. This means products are conceived with a clear understanding of the customer problem they solve and how their value will be effectively communicated from the outset. This integration is key to accelerating our current success and aligns with our focus on customer segments to truly connect and build individual customer relationships. This organization has allowed us to ensure product delivery translates to a marketable asset to the final goal of revenue realization. Howard: Winning customer experiences and customer-centricity are key themes that drive your marketing organization. Can you share more on how you operationalize this thinking as well talk a bit about the new CX Index you recently launched? Meijer: Customer-centricity isn't just a buzzword for us; it's the fundamental principle that guides every decision and initiative within our marketing organization. We operationalize this thinking by focusing on several critical areas that directly impact the customer journey. For example, we've heavily invested in initiatives like bill simplification, recognizing that a clear and understandable invoice is a cornerstone of a positive customer experience. Our new Bill Inquiry Tool is a prime example. It's an easy-to-use chatbot that answers customers' 2,000 most-asked questions about their bills. We've just rolled it out to our service reps, who are pressure-testing it for us, and are planning to release it directly to customers in the coming months via our digital portal. Once live, the tool will allow our customers to get their questions answered immediately. This is part of our commitment to creating new moments of delight in the customer experience. To rigorously measure our progress and identify areas for further improvement, we recently launched a new Customer eXperience Index (CXI). This robust AI-powered index is integrated directly into our operational tools, providing a real-time, holistic view of customer satisfaction across various touchpoints. We no longer rely just on survey data. Instead, we now have the ability to empirically score every customer through a network, product, sales, service and value lens to ensure we are meeting and exceeding our customer promise. And in cases where we are not, we proactively take action on behalf of the customer to remedy the issue, sometimes even before the customer is aware. The impact has been significant. The CXI has already shown improved outcomes for our wireless accounts, directly contributing to a lower churn rate and a notable increase in revenue. Our overarching goal with these initiatives, driven by the insights from the CXI, is to maintain our coveted #1 NPS ranking for 2025, solidifying our position as a leader in customer experience and demonstrating how we translate customer insights into commercial opportunities. Howard: I have been talking about achieving 1:1 commercial intimacy, or personalization at scale for years, and my POV has always been centered on sharpening customer understanding, particularly through the lens of emotion. What are your thoughts? Meijer: I wholeheartedly agree that achieving 1:1 commercial intimacy and personalization at scale is not just an aspiration but a critical imperative for modern marketing. Your emphasis on sharpening customer understanding, especially through the lens of emotion, resonates deeply with our philosophy at Verizon Business. True personalization goes beyond simply knowing demographics; it's about understanding the nuances of a customer's needs, their pain points, their aspirations, and the emotional drivers behind their decisions. This is why we focus on customer segments to really connect and build customer relationships that are individual – in SMBs, we refer to it as a "segment of one" due to the need for personalization. To achieve this, we are committed to continuously investing in advanced data analytics and artificial intelligence. Generative AI, for example, has the potential to increase the scale and speed of our marketing content personalization like no other recent technology development. Gartner predicts that by 2025, 30% of outbound marketing messages from large enterprises will be synthetically generated. We have rich insights into our customers' real-time behavior and intent, and AI helps us translate that into dynamic content at scale, augmenting sales with AI as part of our Verizon Velocity Selling strategy. On your point about the lens of emotion, we are leveraging advanced AI and generative AI to gain a deeper, more empathetic understanding of our customers' journeys. Through the use of "conversational intelligence," we actively analyze interactions across all our communication channels—including phone calls, chat, and email—to score customer sentiment and track our commitments in real-time. This AI-driven insight allows us to provide more sensitive and personalized service. For example, our technology can identify signals of customer frustration, enabling our specialized teams to proactively engage and provide a higher level of care. By focusing on the sentiment around each interaction, we aim to move beyond transactional support to build stronger, more positive brand relationships. Ultimately, our ability to deliver winning customer experiences is inextricably linked to this level of personalization. When we truly understand our customers—both rationally and emotionally—we can anticipate their needs, offer proactive solutions, and provide a seamless, intuitive experience across all touchpoints, ensuring that our customers feel heard, understood, and valued.