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As readers look to curl up with a proverbial good book this winterand put their holiday bookstore gift cards to worktheyll be faced with an obvious question: What should they pick up next? People find it much harder than you think, because there’s so much choice out there, says Rachel Van Riel, founder and owner of the book recommendation website Whichbook. Where do you start? Whichbook employs human readers to classify books along dimensions like moods, levels of violence and sexual content, attributes of the main characters, and length. Its a process Van Riel says artificial intelligence cant yet replicate, though its still quite mathematical in nature, with new hires guided in tuning their scores to the sites standard. Then, Whichbook users can indicate their own current preferences with a set of sliders to find a set of books that match. Operating for free since 2003, at times thanks to funding from libraries, its designed to be a low-pressure way to discover interesting books. I think when it’s more playful, people take more risks, and that’s where they end up finding something that maybe suits them better, Van Riel says. It’s also very nonjudgmentalwhatever you like, lots of sex, no sex at all, your choice. Whichbook shies away from recommending big bestsellerssince, as Van Riel says, people are generally already aware of thembut it can suggest books similar to current literary hits, or help people find books from particular parts of the world via an interactive map. Its one of a growing number of websites, apps, and online communities helping people find something to read through various mixtures of algorithms and human insights. Readers can take cues from influencers, like the loose community of literary-themed TikTok creators commonly called BookTok, or ask for personal recommendations on any of several subreddits set up for the purpose, like r/suggestmeabook or r/booksuggestions. Or they can take to book-based social networks, like Amazons Goodreads, The Storygraph, or Fable (recently acquired by Scribd ebook unit Everand), sharing suggestions and reviews with friends or friendly strangers. Each of those social sites also offers some automated recommendation features, as do many online bookstores, though the nuances of what makes a book a good read at a particular time can make the problem especially tricky. We began just from the idea that there isnt a great book recommendation system, says Sebastian Cwilich, cofounder and CEO of online bookseller Tertulia, which launched in 2022. Even to this day, I dont think us or anyone else have absolutely cracked it. Tertulia began with the idea of building machine learning models to generate recommendations based on literary conversations then happening on Twitter. That approach became less viable once Elon Musk acquired the site, now X, since book-related posting on the site dramatically dropped and the new ownership significantly raised prices to access such data, Cwilich says. Its recommendations are still fairly data-driven, albeit more hand-curated, with the company tracking bestsellers, critical reviews, celebrity book clubs, and recommendations posted on Instagram. Much of that information is organized into a database for easy access by Tertulias editorial team. I think we do a really, really good job of unpacking a particular micro-genre or a particular author that’s kind of trending or in the cultural zeitgeist, says cofounder Lynda Hammes. Tertulia also offers a sprawling set of other features, from recommendations by authors from poet and novelist Patricia Lockwood to actor and memoirist Lukas Gage, an integration with online book club community Belletrist, and a newly launched platform for authors to quickly build their own websites. Of course, its also a bookstore, complete with a paid membership co-op program, and all those sources of book recommendations naturally help sell books, much like the staff recommendations bookstores large and small have long offered visitors. Even bookselling giant Amazon, in addition to personalized recommendations, offers editorial recommendations through its Amazon Book Review subsite. We’re all very passionate readers, so we really try to keep our fingers on the pulse of what’s trending and what’s interesting, says Amazons senior editor Lindsay Powers, who is also a published author. The site isnt simply recapitulating a list of Amazon bestsellers or titles highlighted by publishers, says Powers, whose work includes compiling monthly nonfiction and history lists for the site. She and her colleagues collectively read thousands of books each year, with Powers alone reading more than 300, and are given considerable freedom in their choices, she says. The site recently published a set of Best of 2025 lists, as well as holiday gift recommendations. Since 2013, Amazon has also owned the online reading community Goodreads, which enables readers to log and share their own reading, see updates from friends, and access a mix of algorithmic recommendations and editorial content. One day, you might see a book recommendation from a friend in your newsfeed, says managing editor Cybil Wallace. The next, you might see an editorial roundup that really appeals to you. We just want to make sure there are lots and lots of different ways for you to find a book that you love. Goodreads has almost two decades worth of data about what people like to read, and even editorial write-ups are heavily driven by what the stats show. We really pride ourselves in looking to our reading community to inform what we write about, Wallace says. Other sites use their own data-driven approaches to connect people to books and help them track their reading, sometimes also attracting users who prefer minimizing their ties to industry giant Amazon. The StoryGraph, often compared to Goodreads, offers tracking features along with AI-driven recommendations and filters to find new reads. And PipeRead, another startup, recently launched with its own AI-powered recomendations, presenting suggested books in a Tinder-style swipe interface. Fable, which launched in 2021 as a platform for online book clubs and now hosts more than 100,000 clubs for almost four million users, also includes an AI recommendation agent, as well as fitness tracker-style visualizations of individual reading habits that are often shared on social media. But the platform, which was acquired by Scribds digital book division Everand in 2025, still focuses heavily on person-to-person recommendations, whether thats through small-scale private book clubs, sprawling public clubs that can have thousands of members, or recommendations from celebrities like LeVar Burton or Paris Hilton. Theres a big crossover between Fable and BookTok, which makes sense with 90% of Fable users younger than 40, says Kim Allee, marketing director for Fable and Everand. And a recent survey the company conducted found personal recommendations still remain one of the most popular ways to find something good to read. I think finding that right book at the right moment from the right person means you’re going to have a deeper, kind of more human experience actually engaging with that book, says Allee. And I think especially in this day and age, that’s something that people really explicitly value. Some book recommendation sites still rely entirely on human expertise. Five Books, launched in 2009, offers readers what it calls the best books on everything, presented through interviews with various experts where theyre asked to discuss their areas of interest and five books from the field. The site, says cofounder and editor Sophie Roell, was inspired by the classic British university system, where tutors assign a list of books to study. It has recently featured a noir fiction list curated by activist and science fiction writer Cory Doctorow, a list of books on World War II chosen by military historian Antony Beevor, and a set of five books on Jesus selected by Oxford theologian Robert Morgan. Their expertise means their recommendations can carry more weight than casual posts on social media. Morgan, for instance, has read more than 100 books on Jesus, says Roell. “I thought he’s a reasonable person to choose the best books on Jesus, because if he’d only read seven, then, quite frankly, I’m not interested in his top five, she says. But if hes read 100, thats goodthats a pretty good filtering mechanism. The site takes donations but is primarily funded by Amazon affiliate commissions, meaning its recommendations also need to appeal to readers enough to sell books and keep the business afloat. One advantage is that many visitors come to the site through Google, searching for books to buy on a specific subject rather than seeking a general-purpose recommendation. It’s just such different strokes for different folks, really, with books, Roell says, which makes recommendations very hard.
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E-Commerce
For years, deepfakes were treated as a political or social media oddity, a strange corner of the internet where celebrity faces (of women 99% of the time) were pasted onto fake videos (porn in 99% of the cases) and nobody quite knew what to do about it. But that framing is now dangerously outdated, because deepfakes have quietly evolved into something much more systemic: an operational risk for corporations, capable of corrupting supply chains, financial workflows, brand trust, and even executive decision-making. Recent headlines show that synthetic media is no longer a fringe experiment. It is a strategic threat, one that companies are not prepared for. When a deepfake can steal $25 million In February 2025, global engineering firm Arup fell victim to a sophisticated deepfake fraud. Attackers used AI-generated video and audio to impersonate senior leadership and convinced an employee to transfer $25 million in company funds. The World Economic Forum described it as a milestone event: the moment synthetic fraud graduated from experiment to enterprise-scale theft. For any executive who still thinks of deepfakes as a social media phenomenon, this should be a wake-up call. Arup had strong cybersecurity. What it didnt have was identity resiliencethe ability to verify that the human on the other side of the call was actually human. CEO fraud, but this time with perfect replicas In the past year, deepfake CEO-fraud attempts have surged, targeting CFOs, procurement teams, and M&A departments. A 2025 report noted that more than half of surveyed security professionals had encountered synthetically generated executive impersonation attempts. Its easy to see why: Deepfake video is now real-time and high-resolution. Voice cloning requires only a few seconds of audio. Attackers can now spoof emotion, urgency, or stress, exactly the cues that override employee skepticism. One midsize tech firm reportedly lost $2.3 million after a convincingly faked audio call instructed finance to transfer funds for an urgent acquisition. Clearly, traditional anti-phishing training doesnt prepare employees for a perfectly reconstructed version of their boss. Deepfakes are no longer about politics: Theyre about business models When a deepfake impersonates a celebrity to promote a fraudulent investment scheme, thats reputational damage. When a deepfake impersonates your spokesperson, CFO, product, or supply chain partner, that becomes a corporate disaster. Weve entered a phase where synthetic media sits squarely inside the business risk landscape, according to Trend Micros 2025 industry report. Synthetic content now drives new waves of fraud, identity theft, and business compromise. This isnt hypothetical. Its operational. The new supply chain risk executives are not seeing Brands increasingly rely on complex ecosystems: logistics partners, suppliers, distributors, influencers, service providers, third-party integrators. Every one of those nodes depends on trust. Deepfakes turn trust into an attack surface. Imagine these scenarios: A fake video from your CEO announcing a shift in sourcing strategy sends suppliers into panic. A voice clone instructs your Asian manufacturing partner to halt delivery. A synthetic leaked clip of a defective product goes viral before your PR team wakes up. A deepfake of a key supplier falsely confirms cybersecurity weaknesses, causing downstream partners to sue. These are not science fiction. They are logical extensions of attack patterns that are already being deployedand they expose a blind spot in corporate risk management: the integrity of identity itself. Why deepfakes hit brands harder than politics Political deepfakes spark outrage. Corporate deepfakes trigger something worse: Loss of customer rust Stock volatility Insider trading vulnerabilities Lawsuits from partners Regulatory scrutiny The Securities an Exchange Commision has already warned the financial sector that AI-generated impersonation is reshaping fraud strategies, calling for upgraded identity-verification standards. If regulators are paying attention, executives should too. Why the traditional cybersecurity playbook isnt enough Firewalls wont stop a deepfake. Multi-factor authentication wont stop a deepfake. Encryption wont stop a deepfake. Deepfakes weaponize something no cybersecurity team has historically been responsible for: trust in human appearance and voice. The weakest link is no longer a password. Its a persons belief that theyre speaking with someone they know. Identity, not infrastructure, is the new vulnerability. Why brands must treat deepfakes as supply chain risk Most companies still relegate deepfakes to the PR desk or misinformation team. Thats naive. Deepfakes threaten: Procurement workflows (fake POs, fake cancellations) Vendor relationships (fake disputes, fake compliance issues) Finance approvals (deepfake CFO instructions) Customer trust (fake product failures, fake CEO messages) Employee morale (synthetic HR directives, fake memos) This is not just about fraud. Deepfakes can disrupt the coordination mechanisms that make supply chains work. They can paralyze a system without ever touching a firewall. What business leaders must do (now) Here is the emerging best-practice playbook for executives: Add deepfake risk to your enterprise risk management framework: If ransomware is a board-level issue, synthetic identity needs to be too. Implement verification protocols that do not rely on voice or video: Use secondary digital signatures, secure channels, or pre-agreed workflows. Audit your vendors, suppliers, and partners: Ask whether they have deepfake-resilience policies, because their vulnerabilities become yours. Deploy detection systems, but dont trust them blindly: Infosecurity Magazine notes that detection tools are improving but remain unreliable. Train employees to distrust urgency: Most deepfake fraud leverages emotional acceleration: This is critical, do it now. Your strongest defense is giving employees permission to slow down. Build an internal identity resilience policy: Define exactly how major decisions and financial approvals must be confirmed. No exceptions for I saw them on video. The uncomfortable truth is that AI has made seeing and hearing obsolete. With AI, weve crossed a psychological Rubicon: Your eyes and ears are no longer authentication mechanisms. Executives who fail to internalize this will face the same fate as companies that ignored phishing, ransomware, or cloud governance a decade agoonly faster, and with higher stakes. Deepfakes are not about what is true: They are about what is believable. And in business, believability is often all that matters. The new leadership challenge The companies that thrive in the AI era wont be those with the biggest models or the flashiest copilots. They will be the ones that redesign trust, identity, and verification from the ground up. Because if deepfakes can corrupt your operations and supply chain, then defending against them is not an IT problem. It is a leadership problem. And if you dont solve it now, someone else (perhaps an algorithm with your CEOs face) might solve it for you.
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E-Commerce
Big firms are fighting for talent and offering major perks to match. Heres how you can position yourself to be in the middle of a bidding war.
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E-Commerce
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