The days of scrolling through endless blue links are behind us as AI has transformed how we find information online. Every time you type a question into Google or another AI-powered search tool, a complex process decides whether you’ll see traditional search results or a direct AI-generated answer. Understanding this process helps PR professionals create content that thrives in the new AI-driven search landscape.
Three Types of Search Queries AI Recognizes
AI engines classify your intent into three main categories:
- Informational Queries: Questions seeking specific facts like “Who was the first person to walk on the moon?” These trigger direct AI responses because the system recognizes you want a concrete answer.
- Navigational Queries: Searches aimed at finding specific websites such as “Facebook login.” These return traditional links since you’re trying to reach a particular destination.
- Transactional Queries: Searches with commercial intent like “buy iPhone 16.” These often blend AI recommendations with traditional results, providing comparisons alongside purchase options.
How AI Understands What You Really Want
The magic happens through Natural Language Processing (NLP) and advanced models that interpret context, not just keywords. These systems understand that “How tall is Mount Everest?” needs a direct answer while “best hiking trails near me” requires location-based results with multiple options.
AI models analyze word patterns, question structures, and contextual clues to determine the best response format. This sophisticated understanding helps AI deliver exactly what users need without making them click through multiple pages.
Why Some Queries Get AI Answers While Others Don’t
Well-structured information on clear topics like historical events or scientific facts leads to confident AI summaries. The AI can easily process this data into concise, accurate answers.
However, subjective queries like “best smartphone of 2025” often return traditional results to avoid bias. When data involves opinion-based information, search engines show various sources to ensure users get a balanced view rather than a potentially incomplete AI-generated answer.
The Secret to Getting Better AI Responses
Query length matters more than most people realize. Short, specific questions generate the most accurate AI responses.
Instead of asking “What are all the different ways that public relations professionals can use artificial intelligence to improve their work?” try “How can PR pros use AI to work faster?” The shorter query yields clearer, more actionable results.
Preparing for a Two-Track Internet
Forward-thinking publishers are already adapting to this new reality. The Economist, for instance, is preparing for a “two-track internet”—one experience designed for human readers and another optimized for AI agents that crawl, summarize and surface content in generative search results.
This emerging dual approach signals a major shift for PR and marketing professionals: it’s no longer enough to create content that resonates with people alone. Brands must also consider how their messaging is structured, tagged and made accessible to the AI systems that increasingly act as gatekeepers between audiences and information. Anticipating this bifurcation now will help communicators stay visible as the search ecosystem continues to evolve.
What This Means for PR and Marketing
This shift demands new strategies from PR and marketing professionals. Creating content that AI systems understand requires clear structure, authoritative information, and direct answers to common questions.
Your content needs to anticipate how people phrase questions and provide clear, factual answers. Structure information with headers, bullet points, and concise paragraphs that AI can easily parse. Focus on becoming a trusted source that AI systems will reference when answering queries in your field.
The future of search is here, fundamentally changing how people discover information about brands and services. To dive deeper into AI’s impact on search and learn practical strategies for optimizing your content, download our Invisible Influencers report.
The way people find information online has fundamentally changed. Instead of scrolling through search results, millions now get instant answers from AI that writes comprehensive responses. For PR professionals, this shift creates both challenges and opportunities that demand immediate attention.
Our new Invisible Influencers: Search Engines and Generative AI report reveals exactly how this transformation affects your communications strategy. The comprehensive guide examines how AI-powered search engines like Google’s Gemini, ChatGPT, and Perplexity are reshaping content discovery. Most importantly, it provides actionable strategies to ensure your messages reach audiences in this new landscape.
What’s Inside the Report
The Invisible Influencers report delivers practical insights across several critical areas on search engines. First, it explains how AI systems decide which content to feature in their responses. You’ll discover why some brands consistently appear in AI-generated answers while others remain invisible.
The report also reveals security concerns with AI search and addresses how to safely use AI tools while protecting sensitive client information. It compares major AI platforms and identifies which ones offer enterprise-grade security for PR teams.
Why PR Professionals Need This Report
Traditional SEO strategies no longer guarantee visibility. When AI generates direct answers without sending users to websites, your carefully crafted content might never reach its intended audience. The Invisible Influencers report shows how to adapt your approach for this new reality.
You’ll learn practical techniques for structuring press releases, blog posts, and other materials to maximize AI visibility. The report also includes specific guidelines on building authority that AI systems recognize and trust. Additionally, it covers new metrics for measuring success beyond traditional page views and clicks.
Legal considerations around AI-generated content also receive detailed coverage. From copyright concerns to attribution requirements, you’ll understand the evolving rules that govern this space. This knowledge helps you navigate potential pitfalls while capitalizing on new opportunities.
The shift to AI-powered search has already begun transforming how audiences discover content. PR professionals who understand these changes can maintain their influence and reach. Those who don’t risk becoming invisible.
Download the Invisible Influencers report to equip your team with the insights and strategies needed to succeed in the AI era. Stay ahead of the curve and ensure your messages continue reaching the right audiences, regardless of how search technology evolves.
There’s nothing quite like the rush of filling out a MLB postseason bracket and declaring, “This is the year I outsmart the AI machines.”
This year, I stepped into the ring against a team of AI heavyweights: ChatGPT, Perplexity, Claude, and Précis AI – each trained with tons of data and loaded with confidence only technology itself has. The twist? Neither supercomputers nor ‘resident Cubs fans’ were safe with the Yankees lurking in the bracket.
Read: Man vs Machine: Can a Cubs Fan Beat AI Databases? MLB Postseason Is Here!
The Chicago Cubs and Claude AI
Let’s talk about how it came down to me – Patrick, the resident Cubs fan resident and human expert, and Claude, one of the most hyped AI tools.
Most people fear AI will take our jobs. But, it turns out maybe the bigger fear should be that AI will hallucinate the Braves into the postseason. Yes, your read that right. While Claude nailed the World Series matchup, it also picked the Atlanta Braves to make the playoffs, a feat about as real as my hopes for the Cubs in October.
Meanwhile, my bracket journey had its own dramatic moments. I had the Blue Jays losing to the Yankees, which stung especially hard after the Yankees pulled off the kind of heartbreak only New York can deliver. Still, I managed to land my final pick, which should earn some bragging rights.
But here’s the kicker: is it worse to hallucinate a whole team into existence, or to trust the Yankees?
Read: Man vs Machine: Why Human Instinct Beat the AIs in the MLB Wild Card Series 2025
AI’s weak spot in sports predicting
Even the best sports prediction algorithms, running on millions of games, stats, and maybe a dash of overconfidence, isn’t 100% accurate. Meaning, every so often, a bot looks at the numbers, shrugs, and gives us playoff picks from an alternate universe. Claude’s Braves pick made me wonder if it confused “October baseball” with “October fantasy.” I can respect the hustle, even if the logic circuits still need a little work.
The obsession with the Phillies was another plot twist. Nearly every AI leaned into the Phillies, picking them as the victors in the postseason bracket. Maybe it’s the love of underdog stories, or perhaps an overfitted Phillies dataset from that one miracle season.
In comparison, I kept it simple and focused – sometimes choosing logic, sometimes trusting my gut. Is there data to back up the value of human instinct in sports picks? Not enough – but I promise, Pepsi tastes sweeter after a correct pick while the robots argue over imaginary Braves games.
Read: Man vs Machine: MLB Division Series 2025 Scoreboard Update
Man vs Machine MLB World Series Winner is…
Between Claude and me, the finish line was surprisingly close. AI’s data-fueled magic clashed with my bracket’s human touch.
In the end, it boiled down to one series game: Blue Jays versus Mariners.
Both, Claude and myself had the Dodgers winning it all, but it’s that one hinge game that reflects why no amount of algorithms can steal the thrill – or the agony – of live competition. So here’s to the next bracket battle – where man, AI and the Yankees all take another swing.
Everyone expected the machines to sweep the bracket. Four AI tools – Perplexity, Claude, ChatGPT, and Précis AI – lined up against me to predict the MLB playoffs. But October keeps rewarding a mix of gut feel and scar‑tissue know‑how.
I ran a perfect Wild Card Series round while every AI stumbled, then dropped just one pick in the Division Series (thanks, Yankees) and kept the lead. The result so far: a friendly, data‑driven reminder that instincts can outfox the consensus.
Read: Man vs Machine: Why Human Instinct Beat the AIs in the MLB Wild Card Series 2025
The Case for Instinct
The Division Series round kept the same beat as the Wild Card Series predictions. I missed just one—courtesy of the Yankees as mentioned—but I stayed in front.
Meanwhile, the AI tools showed a strange pattern: three out of four clustered on the Phillies to move on, and all three missed. When machines converge on the same wrong answer, it usually means they’re drawing from the same data—and that creates shared blind spots.
My edge has set me apart. While the AI tools went with safe, popular choices, I’ve leaned on bold insights from that hard‑to‑define “feel” you get from watching baseball for years.
MLB World Series Picks
My World Series prediction is Dodgers vs. Mariners, with the Dodgers finishing the job. Claude and I agree on the Dodgers taking home the championship, but we split in the American League: I’ve got the Mariners; Claude’s on the Blue Jays. With Game 1 done, I’m feeling good about my shot.
Scoreboard Snapshot
- Wild Card: Patrick 4/4; every AI missed at least one.
- Division Series: Patrick dropped one (Yankees) but retained the lead.
- Best‑performing AI so far: Claude—still trailing.
- Big divergence: AI clustering on the Phillies vs. my Mariners lane.
Keep Following the Man vs. Machine Series
This friendly contest makes one thing clear: AI prediction tools are strong, but sports keep them humble. Baseball is wild and hard to pin down. One swing, a single play, and team spirit can swing a series—and those things rarely show up in the numbers. Sometimes, a fan’s seasoned gut beats even the smartest algorithm.
Go Cubs.
Read: Man vs Machine: The Yankees Were the Real Villain in MLB World Series 2025
The machines slipped while I stayed sharp.
In this installment of Précis AI’s Man vs Machine series, I break down my MLB postseason 2025 predictions, how the Wild Card series actually played out, where the models missed, and what we can expect heading into the Division Series.
Read: Man vs Machine: Can a Cubs Fan Beat AI Databases? MLB Postseason Is Here!
MLB Wild Card Recap 2025: How the Picks Landed
I called every Wild Card game correctly with a perfect four-for-four with the Mariners, Yankees, Dodgers, and Cubs. The AI systems? Each missed at least one – hence challenging the idea that algorithms always have the edge. Let’s take a closer look:
- ChatGPT went 2-for-4, missing on the Red Sox and Guardians.
- Perplexity, Claude, and Précis AI each finished 3-for-4 — all stumbling on the Guardians.
When every model trips on the same matchup, that’s a clue: shared inputs can create shared blind spots.
Why I Think the AIs Missed
Baseball is more than numbers and charts. Team spirit, late surges, match‑up edges, nagging injuries, clubhouse energy — they’re real, and they often don’t register cleanly in model inputs. A player with a sore shoulder won’t tank his WAR overnight, but he might change a series. A team riding a hot September can outperform its season-long mean.
We’ve already seen the models wobble even before the games started: in our series kickoff, Claude penciled in the Braves and ChatGPT still had the Mets on its bracket — neither belonged in this year’s postseason picture.
MLB Division Series Picks 2025: My Calls vs the AI Models
I’m keeping it straightforward:
- American League: Mariners and Yankees
- National League: Dodgers and Cubs
The AIs mostly line up with me on the Yankees, Mariners, and Dodgers. Where we split is the NL: most models lean Brewers over my Cubs. And for an odd twist, Claude even floated the Braves in earlier DS logic — a reminder that model outputs are only as grounded as their inputs.
Read: Man vs Machine: MLB Division Series 2025 Scoreboard Update
What This Faceoff Teaches Me
AI is phenomenal at scanning mountains of data and surfacing patterns. But it can struggle to read the moment — the mood in the dugout, the way a veteran steadies a bullpen, the confidence of a kid who just found his swing. The sweet spot is obvious: let AI handle the facts and probabilities, and let human judgment interpret the pulse of October.
As the Division Series gets underway, I’ve got the early lead. Will instinct keep me in front, or will the models regroup and surge over the next rounds? Either way, this experiment proves that in a world buzzing with new tech, human insight still matters — sometimes most when the margins are thinnest.
Read: Man vs Machine: MLB World Series Results
Every company has a Chicago Cubs fan. At Précis, that’s me.
This October, I’m kicking off our new Man vs. Machine series for the MLB postseason by putting my bracket head‑to‑head against four leading AI models — Perplexity, Claude, ChatGPT, and Précis AI. It’s a friendly, data‑driven showdown to see whether a lifetime of baseball heartbreak and hope can outduel cold algorithmic logic — or at least make it sweat.
I’ll be the human. The machines? They’re already talking a big game.
Our Man vs. Machine format pits a human enthusiast against multiple AI platforms and tracks the results as the competition unfolds, just as we did in our tennis edition.
The AI tryouts: mixed results
When I asked the models to generate their postseason picks, it wasn’t exactly a great day regarding AI hallucinations:
- Perplexity and Précis nailed the bracket entrants – every team correct out of the gate.
- Claude got bold with its path to the top, penciling in the Braves as the team to beat.
- ChatGPT refused to accept late-season reality and still had the Mets included.
Maybe they’re taking it easy on me. After all, I’m a Cubs fan.
Why Play Man vs. Machine?
Baseball fans are using AI more than ever — to weigh matchups, simulate series, and second‑guess their own gut. Major‑league front offices aren’t shy either: they’re constantly modeling probabilities and pressure moments. Our goal with Man vs. Machine isn’t to crown a permanent champion; it’s to show how human judgment and AI predictions can collide, converge, and — sometimes — completely disagree.
The Ground Rules
- The Contenders: Patrick (me) vs. Perplexity, Claude, ChatGPT, and Précis AI.
- The Measure: Round-by-round accuracy with a clear scoreboard update after each round.
I’ll share my bracket, the AIs’ brackets, and quick notes on the key calls where our picks diverge. Expect me to lean on clubhouse intangibles, recent form, and a lifetime’s worth of postseason scar tissue. Expect the AIs to lean on probabilities, historical comps, and pattern recognition. Then we’ll see who reads October better.
Your Turn
Will this postseason reward my stubborn optimism — or the models’ cool math? Drop your own picks, cheer for your favorite contender (hopefully me), and follow along as we update the leaderboard throughout the playoffs. If our tennis series taught us anything, it’s that the lead can flip fast — and the fun is in the chase.
Read: Man vs Machine: Why Human Instinct Beat the AIs in the MLB Wild Card Series 2025
Read: Man vs Machine: MLB Division Series 2025 Scoreboard Update
Read: Man vs Machine: The Yankees Were the Real Villain in MLB World Series 2025
Go Cubs. And may the best bracket win.
My MLB Postseason Picks
Perplexity MLB Postseason Picks
Wild Card: Guardians (3) vs Tigers (6); Yankees (4) vs Red Sox (5)
ALDS: Blue Jays vs Yankees; Mariners vs Guardians
ALCS: Blue Jays vs Mariners
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Wild Card: Dodgers (3) vs Reds (6); Cubs (4) vs Padres (5)
NLDS: Brewers vs Cubs; Phillies vs Dodgers
NLCS: Brewers vs Phillies
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World Series: Mariners vs Phillies
Claude MLB Postseason Picks
Wild Card: Guardians (3) vs Tigers (6); Yankees (4) vs Red Sox (5)
ALDS: Blue Jays vs Yankees; Mariners vs Guardians
ALCS: Blue Jays vs Mariners
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Wild Card: Dodgers (3) vs Reds (6); Cubs (4) vs Padres (5)
NLDS: Braves???? vs Dodgers; Phillies vs Cubs
NLCS: Dodgers vs Phillies
—-
World Series: Dodgers vs Blue Jays
ChatGPT MLB Postseason Picks
Wild Card: Guardians (3) vs Tigers (6); Yankees (4) vs Red Sox (5)
ALDS: Blue Jays vs Red Sox; Mariners vs Guardians
ALCS: Blue Jays vs Mariners
—-
Wild Card: Dodgers (3) vs Mets (6); Cubs (4) vs Padres (5)
NLDS: Brewers vs Cubs; Phillies vs Dodgers
NLCS: Brewers vs Phillies
—-
World Series: Mariners vs Phillies
Précis AI MLB Postseason Picks
Wild Card: Guardians (3) vs Tigers (6); Yankees (4) vs Red Sox (5)
ALDS: Blue Jays vs Yankees; Mariners vs Guardians
ALCS: Blue Jays vs Mariners
—-
Wild Card: Dodgers (3) vs Reds (6); Cubs (4) vs Padres (5)
NLDS: Brewers vs Cubs; Phillies vs Dodgers
NLCS: Brewers vs Phillies
—-
World Series: Blue Jays vs Phillies