A slew of major stories in AI writing that broke in Q2 have made the future for writers and editors crystal clear: The wholesale transition of writing-by-humans to writing-by-AI-machines has begun.
Fading are the days when publishers and AI evangelists hid behind the euphemism that AI writers are just Silicon buddies looking to shoulder the drudge work so their human counterparts can do more interesting work.
And in their place are increasingly candid, bald admissions — or unquestionable evidence of the same — of a common-sense reality that anyone paying close attention to AI has known for years.
Specifically: If words are your stock-in-trade and AI-powered machines can do your kind of writing much faster — and much more inexpensively — it makes no sense to keep you employed.
A few examples of that new reality from Q2:
~Sam Altman, CEO of ChatGPT-maker OpenAI, predicts that AI will ultimately usurp 95% of all marketing work currently performed by agencies, strategists and creatives
~The BBC reports that a publisher reduced its writing and editorial staff from 60+ to a single, lone editor — simply by switching to AI
~A Swedish financial company reduced its marketing costs by $10 million, simply by funneling that marketing work to AI rather than to outside, human creatives
~WPP — the world’s largest ad agency — cut a deal to bring in Google Gemini, a ChatGPT competitor, to help write ad scripts, auto-create narration and auto-generate product images
~Newsweek announced it’s all-in on AI and has plans to integrate the tech into the magazine’s operations as deeply as possible
Granted, news editors and reporters still have some cover, given that AI in many instances still does not have the trust and sources to unearth new data from the world — and then work that new information into news stories.
But for writers in marketing, copywriting and similar jobs who are playing around with ideas and concepts — but not bringing fresh data to their audiences — there is only one recourse: They need to get smart, very quickly, on how to best leverage AI writing tools in their day-to-day work.
And once they’re up-to-speed, they need to engage with that AI knowing that like the 60+ copywriting shop that was shrunken down to a single editor by AI, they still may be out-the-door — no matter how sophisticated their AI smarts.
Here’s detail on the wholesale migration, along with other key stories that shaped the growing impact of AI writing in Q2:
*ChatGPT CEO: AI Will Usurp 95% of Marketing Work: In a stunning moment of candor, ChatGPT CEO Sam Altman has stated that AI will usurp 95% of all the marketing work currently performed by agencies, strategists and creatives.
Altman’s prediction can be found in a new book — offered by subscription — “Our AI Journey,” by Adam Brotman and Andy Sack.
Observes Mike Kaput, chief content officer, Marketing AI Institute, in reaction to Altman’s reported prediction: “To say it blew us away is an understatement.”
Altman’s exact words, according to Brotman and Sack, were: “95% of what marketers use agencies, strategists, and creative professionals for today will easily, nearly instantly and at almost no cost be handled by the AI.
“And the AI will likely be able to test the creative against real or synthetic customer focus groups for predicting results and optimizing.
“Again — all free, instant and nearly perfect. Images, videos, campaign ideas? No problem.”
For more on Altman’s revelation, check out this riveting article by Kaput.
Keep on rockin’ in the free world.
*The Myth of the ‘Cheery, AI Collaborator’: AI Reduces 60+ Copywriting Team to One Editor: In yet another bone-chilling example of how AI is hollowing-out copywriting teams, this BBC report details how AI turned a 60+ copywriting team into a one-man operation.
First introduced by the publisher in 2023, AI slowly began to usurp more and more jobs until by 2024, everyone on the team was vaporized save for one, lone editor.
Observes the last of the team, who chooses to remain anonymous: “All of a sudden, I was just doing everyone’s job.
“Mostly, it was just about cleaning things up and making the writing sound less awkward, cutting-out weirdly formal or over-enthusiastic language.
“It was more editing than I had to do with human writers, but it was always the exact same kinds of edits. The real problem was it was just so repetitive and boring. It started to feel like I was the robot.”
That account is a long way from current-day AI evangelism, which insists AI is little more than a warm-and-fuzzy friend who will always help you — and never hurt.
For editors and writers who are not tasked with unearthing fresh news data in their jobs, the message is clear: Increasingly, staying alive in copyediting has become a fight to be ‘the last one standing.’
*Pink Slip Heaven: Scores of Jobs Go Bye-Bye as Marketing Department Embraces AI: Remember that cheerful AI assistant and ‘collaborator’ that was going to free-up your days so you could indulge in much more meaningful work?
It just took your job.
Writer Megan Graham reports that $10 million worth of marketing work that would have gone to content creators for a Swedish financial company is now handled by AI.
Observes Graham: “Using generative AI tools such as Midjourney and DALL-E saved the company $1.5 million on image production costs in the first quarter — while slashing its image development timeline to seven days from six weeks.
“Klarna also said it had decreased by 25% its spending on external marketing suppliers (code-phrase for editors, writers and graphic artists) for tasks such as social media, translation and production.”
*Newsweek Goes Full AI: Reporters That Boot-up in Seconds: Brushing aside fears of editorial job loss, Newsweek has fully embraced AI and is looking to integrate the tech as deeply as possible into the magazine’s operations.
Says Jennifer Cunningham, executive editor, Newsweek: “I think that the difference between newsrooms that embrace AI and newsrooms that shun AI is really going to prove itself over the next several months and years.
“We have really embraced AI as an opportunity — and not some sort of boogeyman that’s lurking in the newsroom.”
We’ll see.
*Dreams Of AI Mojo: World’s Largest Ad Agency Partners With Google: In a head-turning move, WPP — parent company of some of the biggest agencies in advertising — has reached-out to Google for AI enhancement.
Specifically, the company is looking to integrate Google’s Gemini AI into its services to auto-write ad scripts, automate ad narration and auto-generate product images.
Observes Stephan Pretorious, Chief Technology Officer, WPP: “I believe this will be a game-changer for our clients and the marketing industry at large.”
*AI Now Crafts Fictional Characters While You Nap: AI pioneer Sudowrite is promising a new module writers can use to auto-build personality traits, background, physical appearances and mannerisms for fictional characters.
Also promised is a new world-building tool that will enable writers to auto-design fictional worlds ranging from dystopian cities to magical realms.
The AI tool — which uses AI engines like GPT-4 and Claude 3 to work its magic — will also be enhanced system-wide to enable writers to auto-generate fiction more efficiently.
*Apple Goes All In on ChatGPT: It’s official: One of the world’s richest and mightiest tech companies has turned to ChatGPT to bring AI to its smartphone.
A major coup for ChatGPT’s maker OpenAI, the deal will bring ChatGPT to millions of iPhone users who are running — or will be running — iOS 18 software on their devices.
The Times of India also reports that Apple may feature ChatGPT competitors on its iPhone as well — such as Google Gemini.
But so far, no such deals have been inked.
*Thousands of Free, ChatGPT Competitors Pop-Up on the Web: Thousands of free, alternative versions of a new AI engine released by Mark Zuckerberg of Facebook fame are popping-up on the Web.
The reason: Zuckerberg released his new AI engine — dubbed Llama 3 –as free, open source code that can be downloaded and altered by anyone interested in doing a little tinkering.
This is great news for consumers, given that thousands upon thousands of AI pros are coming up with competitive — and free — AI alternatives to proprietary AI solutions like ChatGPT.
That forces market leaders like OpenAI — the maker of ChatGPT — to continually develop ever-more-sophisticated versions of their tech.
And it makes it much tougher for OpenAI and similar proprietary companies to raise prices aggressively when thousands of free alternatives abound.
*Less Popular Than Your Average Cat Video: Only 23% of U.S. Adults Have Tried ChatGPT: Nearly a year-and-a-half since ChatGPT first stunned the world, only 23% of U.S. adults have actually used it, according to a new study from Pew.
For many who track the tech closely — and see the emergence of ChatGPT and similar AI as a pivotal moment in the history of humanity — the meager adoption rate is tough to understand.
Not surprisingly, young adults under 30 are most enthusiastic about ChatGPT — 43% have tried the AI.
Oldest adults, 65-and-up, are least interested in the tech — only 6% have tried the tool, according to Pew.
*AI Smarter Than Many Humans By 2027?: If it feels like we’re all living in a sci-fi movie that’s ready to careen off a cliff into AI oblivion, don’t blame Leopold Aschenbrenner.
His firsthand take on the potential devastation ahead — courtesy of AI — leaves him no choice but to sound the alarm.
A former researcher for OpenAI — maker of ChatGPT — Aschenbrenner warns that AI is moving so fast, we could see AI that’s as smart as an AI engineer by 2027.
Even more head-turning: Once AI is operating at that intellectual level, it’s just another jump or two — perhaps another few years — until we literally have “many millions” of virtual AI entities that have taken over the ever-increasing sophistication of AI, Aschenbrenner says.
Observes Aschenbrenner: “Rather than a few hundred researchers and engineers at a leading AI lab, we’d have more than one hundred thousand times that—(AI agents) furiously working on algorithmic breakthroughs, day and night.
“Before we know it, we would have super-intelligence on our hands — AI systems vastly smarter than humans, capable of novel, creative, complicated behavior we couldn’t even begin to understand.”
In essence, AI will have created its own digital civilization.
And it’s highly feasible that civilization would be populated by “several billions” of super-intelligent AI entities, according to Aschenbrenner.
The stomach-churning problem with that scenario: Given the human greed to possess such vast AI power unilaterally, it’s very likely that the U.S. could find itself in an all-or-nothing race with China to dominate AI.
Even worse: The U.S. could find itself in an all-out war with China to dominate AI.
Granted, it seems that for every in-the-know AI researcher like Aschenbrenner, there’s another equally qualified AI researcher who insists those fears are extremely overblown.
Yann LeCun, chief AI scientist at Meta — Facebook’s parent company — for example, believes that such AI gloom-and-doom nightmares are misguided and premature.
Even so, Aschenbrenner has staked his professional reputation on his assertions.
And he’s offered his complete analysis of what could be in a 156-page treatise entitled, “Situational Awareness: The Decade Ahead.”
(Gratefully, Aschenbrenner’s tome is rendered in a conversational, engaging and enthusiastic writing style.)
For close followers of AI who are looking to evaluate a definitive perspective on how our world could be completely transformed beyond our imaginations — within the next decade — Aschenbrenner’s treatise is a must-read.
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–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.
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If you want to get ahead in today’s market, you’ve got to bring your tech A-game. Gone are the days when sales were a telephone and a Rolodex—tech is now a necessity if you’re serious about pushing your sales numbers […]
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In the years since Gartner last released a Magic Quadrant for Data Science and Machine Learning (DSML), the industry has experienced massive shifts. DataRobot has also transformed dramatically from where we began to where we stand today. The rapid pace of AI advancement is unparalleled, and at DataRobot, I’m most proud of our ability to harness these innovations to ensure organizations can leverage them safely, with governance, and for impactful results.
This commitment to driving value through AI and our continuous product enhancement is why we are thrilled to be recognized as a Leader in the 2024 Gartner Magic Quadrant for DSML Platforms. Positioned in the Leaders Quadrant for the first time marks a significant milestone for DataRobot, which we believe reflects our transformation and growing influence in the market. I also extend my congratulations to the other companies recognized in the Leaders Quadrant—what a recognition!
As one of the industry leaders in this dynamic landscape, this marks the start of a new era for DataRobot. Our journey is defined by ongoing innovation and progression, ensuring that our current offerings are just the beginning of the groundbreaking advancements on the horizon.
Gartner evaluates the Magic Quadrant based on a vendor’s ability to execute and completeness of vision. Companies use the Magic Quadrant to shortlist technology vendors, typically focusing on vendors in the Leaders quadrant.
DataRobot is named a Leader in the Magic Quadrant and we also scored the highest for the Governance Use Case in the Critical Capabilities for Data Science and Machine Learning Platforms, ML Engineering.
Our journey from democratizing AI to a new set of users, to today expanding to become a unified system of intelligence systems, has been transformative. This journey has been propelled by our laser focus on reimagining our user experience for both generative and predictive AI, adding full support for code-first AI practitioners, broad ecosystem integration, and reliable multi-cloud SaaS and hybrid cloud support.
With each launch in Spring ‘23, Summer ’23, and Fall ‘23, we fortified our product offering. As an end-to-end platform, we provide an extensive range of capabilities, enabling us to deliver enterprise-grade AI-driven solutions. This evolution reflects how our hard work has kept pace with the rapid advancements in the generative AI space, as we believe is evidenced by our 4.6 out of 5 score on Gartner Peer Insights based on 538 reviews as of June 27, 2024.
Our platform is built on a foundation of advanced AI technologies for practitioners and their related stakeholders. Our customers leverage sophisticated machine learning algorithms to analyze extensive datasets, uncovering insights and patterns that drive smart and prompt decision-making. DataRobot complements the platform with forward deployed customer engineering teams and applied AI experts to accelerate value delivery.
Our goal is to enable synergy among participants throughout the end-to-end DSML lifecycle, addressing the needs of all stakeholders to integrate ML and generative AI into business processes. AI practitioners can share use cases, manage files, and control versions with CodeSpaces, a persistent file system integrated with Git, providing access to our comprehensive, hosted Notebook developer environment anytime, anywhere.
We ensure rapid deployment of any AI project – whether built on or off the DataRobot platform – to any endpoint or consumption experience, facilitating smooth transitions from AI developers to operators. Our unified approach to generative and predictive AI development, governance, and operations streamlines activities for data science teams, IT personnel, and business users.
The DataRobot AI Platform offers AI observability across environments, whether cloud or on-premise, for all your predictive and generative AI use cases. The unified view across projects, teams and infrastructure enhance cross-environmental governance and security for all customer AI assets.
Enterprise Strategy Group (ESG) validated DataRobot’s rapid deployment is up to 83% faster compared to existing tools. They also found that it can offer cost savings of up to 80%, with a predicted ROI ranging from 3.5x to 4.6x, providing the necessary analytics capabilities for organizations looking to productionalize 20 models. Having served over 1000 customers, including many of the Fortune 50, DataRobot understands what it takes to build, govern, and operate AI safely and at scale.
We built our governance capabilities to help our customers establish rigorous policies and procedures that protect their bottom line. Our governance framework is designed to uphold the highest standards of integrity, accountability, and transparency across all AI operations. We are thrilled to have been ranked the highest, with a 4.1 out of 5 governance score from Gartner for Governance Use Case!
Our continuous innovation efforts are evident in the over 80 new features we have released in generative and predictive AI over the last year. We continue to innovate and invest in the user experience, offering comprehensive support for both highly technical code-first users, and no-code users. Stay tuned to our “What’s New” page to see what we have in store next. We’re already deep into our next groundbreaking release.
I have been working in the DSML space for over a decade, and I recognize that we are on the cusp of what AI has to offer. What I look forward to most every day is listening and learning from our customers and partners to safely accelerate innovation and value delivery. It is both a challenge and pleasure to work in such a dynamic environment where no one knows the “right” answer and we get to test our best ideas and see what works. I look forward to an eventful year or two till the next MQ!
And, if you’re curious about all advancements I talked about, I encourage you all to watch the Data Science and Machine Learning Bake-Off video to see how DataRobot took a problem statement and a raw data set and turned it into an end-user application and judge for yourself.
Gartner, Magic Quadrant for Data Science and Machine Learning Platforms, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Raghvender Bhati, Maryam Hassanlou, Tong Zhang, June 17, 2024.
Gartner Critical CapabilitiesTM for Data Science and Machine Learning Platforms, Machine Learning (ML) Engineering, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Tong Zhang, Maryam Hassanlou, Raghvender Bhati, Published June 24, 2024.
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