Below are all the posts — topics as well as replies — that mention the hashtag #ai.
Mention #ai in your post to continue the discussion!
Cisco announced record revenue figures. The technology company also cut approximately 4,000 jobs on the same day. This decision quickly sparked public backlash. Critics argue the move prioritizes shareholders over workers. The timing raises concerns about AI-driven restructuring.
https://finance.yahoo.com/sectors/technology/articles/cisco-posts-record-revenue-4-214000754.html
Cisco | CSCO
Intuit plans to eliminate approximately 3,000 jobs. This represents about 17% of its total workforce. The company is undergoing a broad restructuring effort. This effort aims to reduce complexity and accelerate AI integration. Two office locations, Reno and Woodland Hills, are also slated to close.
https://finance.yahoo.com/sectors/technology/articles/intuit-layoffs-3-000-jobs-142453143.html
Acrisure is laying off 2,250 employees. This reduction represents 11% of its total workforce. The layoffs will begin now and continue in phases into 2027. These changes primarily impact U.S.-based operations. The company cites advances in technology, AI, and digital platforms as reasons.
Grand Rapids, Michigan
https://www.wzzm13.com/article/news/local/source-acrisure-announces-2250-layoffs-totaling-11-of-workforce-citing-technology-al-digital-platforms/69-339a1b30-018e-4c2e-885a-c0a82e7583f7
Intuit announced plans to lay off 17% of its global workforce. Approximately 3,000 employees are impacted by this decision. The company aims to accelerate AI integration and streamline operations. Intuit is also closing key hubs in Reno, Nevada, and Woodland Hills, California. Impacted workers will receive a severance package including 16 weeks of pay.
https://www.fastcompany.com/91545602/intuit-layoffs-today-stock-down-job-cuts-citing-ai
For all meta users who need support! Know all your CS tickets are being routes to AI. We are not looking at them only tagging them.
Some managers have less than 5 reports
AI is barely being used, if at all
Meanwhile companies that will survive are flattening the orgs and making managers have at least ten reports and AI is used everywhere
We are so far behind it's worrying
Besides people in positions considered management are very clueless.I mean this is contractor type ,engineering type,Actual managers.First all you need to see on here is employees who barely go to office or interact with anyone asking if there’s gonna be a strike still.Then you go in asking actually direct managers at all levels questions but they cannot answer anything.Then there is the group that won’t answer or make any decisions at all because they are either clueless or scared.My God company is such a disaster.Bad cell coverage losing customers left and right in all lines of business.I am glad I am at the end of it all ,I am also glad that I was never management as bad as the Union contracts may get over the years at least I can say as associates we have a clue starting to think the people in field are only ones floating the company anymore.Just rif all nonunion employees at this point let AI be my managers
OPED in today's WSJ. I think Verizon will likely see another big round of layoffs in the fall. SMH.
Algi Febri Sugita/Zuma Press
Two weeks ago I laid off more than 20% of my workforce. I didn’t do it because Cloudflare is struggling. We posted record revenue growth, have strong free cash flow and are adding an unprecedented number of customers around the world. I did it because business is changing, and to win the future, Cloudflare needs to change with it.
We haven’t found another example in U.S. business history of a public company growing at more than 30% that laid off more than 20% of its workforce. Yet what we did is likely going to become the norm over the next year. This is a story about artificial intelligence, but executives and commentators are misunderstanding how it will disrupt business and who will be affected.
To understand the issue, I went back to a book published in 1954, 20 years before I was born: Peter Drucker’s “The Practice of Management.” Drucker explores the different roles inside every business, which I would categorize as builders, sellers and measurers.
Builders create products. Sellers sell those products. Measurers do everything else: internal audit, revenue recognition, finance, legal, compliance, middle management, operations and on and on.
Contrary to what some analysts predict, builders aren’t going anywhere. If an engineer on my team can now be 10 times as productive, I’m going to hire as many as I can find.
Sellers, too, are safe from extinction. Humans still control budgets, and they want to buy from people who take the time to understand their needs, build trust and fix whatever goes wrong.
Measurers are also critical to a business, but different from the other two. The best are hard to find. They work tirelessly behind the scenes, don’t seek the recognition of a front-of-house role, and ideally have a perspective independent from the rest of the organization. Drucker argues that measuring business is important, but customers are earned through building and selling. The best businesses would maximize investment in those two functions.
AI isn’t coming for builders or sellers, but it is coming for measurers. Tireless, independent, efficient and available, AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees.
For Cloudflare, internal audit previously picked a handful of business risk areas to scrutinize each quarter. Now we’re moving to a system in which every business risk is audited continuously. We’re closing our books faster. We’re making fewer mistakes and catching the ones we do more reliably. And, as CEO, I’ve never had better tools to measure exactly how the business is performing, including identifying our rising stars.
The vast majority of those we laid off last week were measurers. We cut middle managers across the organization because AI allows us to have more direct reports per manager while still measuring and mentoring our teams effectively. We consolidated our operations functions into a single group that can support teams across the business, using AI to gain specific expertise when needed. We significantly reduced our marketing team, which, like in most companies, was teeming with measurers. Across our finance team, we found opportunities to consolidate and automate.
But the layoff wasn’t about reducing headcount. In fact, we have a record number of open positions. In coming years I expect our number of employees will continue to grow. With fewer people needed for measuring, we can now invest more in people in the areas that drive growth.
We received almost a million applicants for 1,111 paid internships this summer. The interns we hired are extremely qualified and AI-native. They’re all builders or sellers, and we expect that the majority will get full-time offers.
They’re the next generation who will invent ways to drive our business. With AI we can now better measure their contributions and accurately identify those who will be tomorrow’s leaders. AI isn’t the harbinger of bleak youth unemployment—it is quite the opposite.
AI won’t ki-l all jobs. But it will change every business. Ultimately, it will prove Drucker right. AI will allow us to better measure our organizations so the humans on our teams can focus on where they create and capture value: building and selling.
Mr. Prince is CEO of Cloudflare.
WebLogic 26? Fusion Middleware 27? Who is left to build any of this? Will it all just be AI slop? https://blogs.oracle.com/fusionmiddlewaresupport/oracle-fusion-middleware-statement-of-direction-is-now-available
Call out your bad leaders
https://qz.com/meta-layoffs-8000-jobs-ai-restructuring-052026
6 in 10 workers say they have a toxic boss, study finds
Employees say poor leadership is driving stress, job changes, and even financial loss, while companies invest more in AI than in people.
Link: https://www.fastcompany.com/91534390/6-in-10-workers-say-they-have-a-toxic-boss-study-finds
BILL Holdings is cutting its workforce by up to 30%. This strategy aims to make the company leaner. The company also plans to leverage AI for increased efficiency. BILL Holdings faces headwinds from declining interest rates and SaaS sector pressures. Its stock has seen a roughly 20% decline year-to-date.
https://seekingalpha.com/article/4906834-bill-holdings-ramping-profitability-with-new-layoffs
The cuts amount to about 10% of the company's workforce.
Singapore-based workers were the first to learn their fate, with layoff emails arriving at 4 a.m. local time, according to Bloomberg. Employees in the U.K. and the U.S. were slated to be informed as their own mornings began. Meta asked North American employees to work from home Wednesday
New just in
Ty announced a giant reorg/struct after the recent LR's via Vidcast
Of course, Cisco is going all in on AI
Significant changes to Collab
How many years do you think we have until everyone is replaced with AI ?
During the Q2 Town Hall, a question was asked about our strategy to replace commodity IT roles with external partners.
The answer was that we're moving to more of a factory model of labor, and we're going to reduce the need to have specialized 3M knowledge.
Between that and the other half of the town hall being about how we need to scale up our use of AI, it's clear that they're looking to reduce headcount.
As a meta mate I heard about the 7k employees being moved to MSL to work on AI initiatives.
Few questions:
How can I volunteer to be moved, or was that already randomly determined?
What are they actually doing there? Anything cutting edge?
Will they the most safe from the next few layoffs since they just got re orged?
Anything good coming from VBG products that will generate good sales? (Or any current products showing potential?)
Seems like AT&T and T-Mo are putting out products - what do we have that's got potential?
Hard to tell if the AI Connect stuff is real.
Why in the world is Gemini AI being pushed for everything...from scripting to positioning statements to call analysis to coaching. Just stop already.
https://www.reuters.com/world/meta-lays-out-plans-may-20-layoffs-restructuring-internal-document-says-2026-05-18/
The New York Fed reports AI is not the main cause of the current hiring slowdown. Elevated interest rates and past overhiring play a major role. The Fed's analysis shows broad labor weakness, not automation, explains the trend. Most firms adopting AI are retraining workers, not initiating layoffs. Startups should focus on capital costs and macroeconomic pressures over AI fears.
https://startupfortune.com/new-york-fed-data-says-ai-is-not-driving-the-hiring-slowdown/
General Motors recently laid off 500 to 600 employees. These job cuts primarily affected information technology roles. Affected employees were largely located in Austin, Texas, and Warren, Michigan. Artificial intelligence played a role in the company's decision. GM offered severance packages and career support to the impacted workers.
Austin
https://www.msn.com/en-us/money/companies/laid-off-gm-employees-tell-of-ominous-email-severance-and-role-of-ai/ar-AA231HLA?cvid=6a0466f468f947e78a1f45a3db8de24d&ocid=hpmsn
Innovaccer has laid off staff members. The healthcare technology company is increasing its artificial intelligence efforts. Innovaccer plans to apply its automation principles internally. The company recently allocated $250 million for AI development. This funding supports small language models on its Gravity platform.
http://www.modernhealthcare.com/health-tech/mh-innovaccer-layoffs-ai-tools/
Does anyone have a general idea when they think AI will start taking over work/employees jobs. the more and more they talk about I feel its around the corner...like in 2 years tops.
Mass layoffs continue to impact Silicon Valley tech workers. Artificial intelligence is driving these job cuts and reshaping the industry. Many displaced employees struggle to find new roles despite extensive experience. Companies are now highly selective, often demanding specific AI skills. Workers are adapting by upskilling, networking, or exploring new career paths.
https://www.latimes.com/business/story/2026-05-19/ai-layoffs-jobless-tech-workers-silicon-valley
https://youtu.be/TZmR2BuCY0Y
One IT department just announced last week it will be moving to AI SDLC. This means developers will basically just be 'reviewing' AI agentic code instead of writing.
What do you all think about this? Will Vanguard be doing layoffs/stealthy layoffs more often over the coming months?
In my opinion, the writing is on the wall and it has been getting more clear across the organization for a handful of years now.
The online gambling industry is experiencing widespread layoffs. Penn Entertainment recently cut over 70 jobs in its interactive division. Gambling.com Group also laid off approximately a quarter of its employees. These reductions reflect a shift towards efficiency and AI adoption. Industry growth is slowing, forcing companies to streamline operations.
https://www.gamblingnews.com/news/betting-firms-cut-jobs-as-industry-growth-stalls/
Crypto exchange Kraken recently laid off approximately 150 employees. The company cited increased efficiencies from deploying artificial intelligence. These staff reductions could delay its planned US initial public offering. Kraken now reportedly aims for a public debut in 2027. Other crypto firms also cut jobs this year, often citing AI use.
https://www.tradingview.com/news/cointelegraph:b71f2d6f4094b:0-kraken-cuts-150-staff-amid-ai-efficiencies-potentially-delaying-ipo-report/
Healthtech unicorn Innovaccer laid off approximately 340 employees. These job cuts occurred across India and the United States. The company is restructuring operations to become "AI-native." This marks Innovaccer's third layoff round in four years. Affected staff will receive severance and transition support.
San Francisco
https://www.peoplematters.in/news/strategic-hr/indian-founded-unicorn-joins-ai-layoff-wave-with-340-job-cuts-across-india-and-us-49780
General Motors recently reduced its IT workforce. The company cut approximately 600 salaried positions. This move is part of a deliberate skills exchange. GM is now hiring for AI-focused IT roles. The automaker seeks professionals to build AI systems from the ground up.
https://www.indexbox.io/blog/gm-and-automakers-reshape-workforces-with-ai-focused-hiring-and-layoffs/
Seems like with sending jobs out of our country and their all in approach to AI, I wonder just how many jobs will be left.
So we got told that AI will be doing some of our work, the “easy cases”. I know Tampa will be seeing layoffs this year, anyone got insight if AML will be affected? They’re upping our pace in June due to an uptick in workload
Because the company wants to keep up with all the other tech and telecom layoffs, and they will blame “AI” like the others did.
https://www.salesforceben.com/the-midlife-crisis-of-the-salesforce-professional/
Layoffs even in AF, smaller territories, higher targets, no raises, greater levels of micromanagement, offshoring....leading many to question is the hard pivot to AI really worth it it just leave the ecosystem? Or even leave the entire tech industry as misery increases for everyone.
Billionaire Jim Goodnight Built An Analytics Profit Machine. AI Is Forcing Its Reinvention.
ByPhoebe Liu,Reporter.
May 15, 2026, 06:30am EDT
Updated May 15, 2026, 10:36am EDT
Unlike most of today’s biggest AI companies, SAS—once America’s largest privately held software company—has always operated slowly, steadily and profitably. Competition from all sides and an upcoming leadership transition will test the company’s longstanding strategy.
Clad in a plain white shirt, Jim Goodnight, billionaire cofounder and CEO of analytics firm SAS, eases into a leather rolling chair in a Cary, North Carolina, meeting room that looks less like a corner office than a geology exhibit. Behind him are glistening gemstones. A clump of pyrite. Purple amethysts. A fossilized dinosaur egg—a 69-million-year-old Hadrosaurus found in the Gobi Desert. A meteorite. “It’s not something you want to get hit in the head by,” he deadpans.
SAS is 50. Its CEO is 83. And like the rocks on display, both are artifacts from an earlier time long before fast-growing, deeply-unprofitable AI shook the world. SAS analyzes large troves of data from its customers in real-time to help them make better business decisions.
“People like to dismiss us by saying, ‘well, that’s legacy software,’” says Goodnight, a statistics pioneer who helped define what analytics would be long before AI became an umbrella term for everything. “But it’s not. We’ve been improving it for 50 years.”
Now SAS has to prove that endurance isn’t the same thing as stagnation.
The company generates just over $3 billion in annual revenue from most of the Fortune 100—including 90% of the financial services companies and all of the health and life sciences firms, plus most every government department. It has stayed private, profitable and debt free.
The AI bo-m is stress-testing that posture. OpenAI, Anthropic and a swarm of newer data-and-analytics rivals are selling the future as a clean break from “legacy” incumbents. Hyperscalers like Microsoft and Amazon are bundling data and AI into cloud contracts. Public-sector competition is heating up. And inside SAS, the next chapter is no longer theoretical: Goodnight has been hinting for years at a leadership transition, including an IPO as a possible succession plan. “When we go public, we need a different CEO,” he says. “You don’t want an old fa-t like me going around trying to sell stock.”
For a company designed to outlast market volatility, an uncomfortable question is suddenly immediate: can SAS modernize fast enough to matter in the AI era—without abandoning the slow, profitable discipline that made it an outlier in the first place? And can it do it without Goodnight?
Goodnight is confident it can; he’s seen this cycle before: the dot-com bo-m, when he considered outside money and passed; the dot-com bust, which rewarded that restraint; failed investments, including an airline; and the 2022 market correction which may have forced SAS to delay its IPO plans. He’s unmoved by the idea that generative AI has rewritten the laws of business.
AI is “just picking the next word in a sentence based on probability,” Goodnight says, correctly, of large language models. “How’s that going to solve anything?” He thinks SAS’ decades of customer trust and “domain expertise,” particularly in finance, healthcare and government services, will help it retain its edge.
Yet Goodnight will likely leave SAS’ future in the age of AI to younger hands.
In recent years, he has ceded more of the daily operating work to a new generation of executives, especially chief technology officer Bryan Harris and chief operating officer Gavin Day. Goodnight says he’s training Harris and Day to take over, though he hasn’t yet decided which of the two he would like as CEO.
The plan they are inheriting is simple to describe and hard to execute: persuade customers that SAS is not the same company it was 50 years ago, sell them on AI that helps them make smarter business decisions instead of merely sounding like it might, and mold the products to meet every customer where it’s needed.
“Incumbency is our biggest headwind,” says Harris.
That incumbency can be seen in SAS’ sprawling North Carolina headquarters. Its 300-acre tree-lined property boasts a day care and doctor’s office, fields dotted with employees playing intramural soccer at lunchtime, one of the state’s few five-star hotels and dozens of docile sheep grazing underneath the company’s solar panels. Turn left from Analytics Drive onto Research Drive and walk down Binary Way, and you’ll be blinded by a shining silver sculpture of the mathematical constant pi. The company’s campus, as they call it, reflects Goodnight’s vision and SAS’ academic origins.
SAS, short for Statistical Analysis System, was born out of North Carolina State University where Goodnight—then a young faculty member fresh out of a statistics PhD—teamed up with Tony Barr in the late 1960s to create software that sifted through and analyzed N.C. State’s agriculture department data. After the tool attracted more than 100 outside customers, Goodnight, Barr, John Sall and Jane Helwig incorporated SAS Institute in 1976. Barr sold his 40% stake for $340,000 in 1979. Helwig, who died in 2021, left and sold her stake a couple of years later. Goodnight now owns two-thirds of SAS, making him worth $13.3 billion and the richest man in North Carolina; Sall owns the remaining third, a $6.5 billion stake.
From the beginning, the company was bootstrapped. Back when SAS software was sold as physical books, all staff—including the founders—would form an assembly line every time a new shipment of books arrived to unload the books into an employee’s basement, a tradition cofounder Sall recalls as “book brigades.”
When the phones from prospective customers stopped ringing, Sall says Goodnight—in keeping with his upbringing as a hardware shopkeeper’s son—forced the cofounders to split up SAS’ potential customers into four (grouped alphabetically) and do the marketing themselves.
The approach worked. SAS was cash-flow positive from day one and generated $600 million (revenue) on an estimated $300 million in operating income by 1996, Forbes previously reported. SAS grew steadily, always prioritizing profitability over the fastest possible growth, Sall says.
Along the way, as evidenced by its campus, SAS built up a reputation as a company that takes care of its employees. Extensive benefits—beginning with free M&Ms (11,000 pounds per week, company-wide) then expanding to on-site doctors and a pharmacy, subsidized on-site childcare and a hair salon—weren’t common in the ’80s and ’90s. It was Goodnight's retention strategy: keep employees happy, keep turnover low and avoid the expensive churn of bonuses and dilutive stock options.
He used to joke that 95% of SAS’ assets, its people, drove out the front gate every night. After the pandemic and a remote-work policy, the line no longer works quite the same way. “I can’t even get ’em to come in,” he says.
Three years ago, Harris brought Goodnight an idea he loved. SAS could use computer vision to analyze video feeds from farms and determine how illnesses spread among chickens. The tool would help farmers keep their flocks healthy. Goodnight ki-led it with a single question: “How much do the cameras cost? The farmers would never pay for that.”
From the perspectives of both customers like those farmers and SAS itself, Goodnight has been laser-focused on cost and profitability for decades. He criticized AI innovation for being 90% wasted dollars, and repeatedly emphasized SAS’ need to get further into the green.
The CEO credits SAS’ durability to that desire to stay profitable, even at the expense of rapid growth. While Anthropic has reportedly grown revenue at roughly 10 times year over year for three years, SAS’ revenue rose 9% last quarter, roughly in line with Morningstar's prediction that software companies will grow at around 10% per year through 2029.
Goodnight thinks the AI companies’ pace “needs to slow down.” But that doesn’t mean SAS has ignored the market. In 2023, the company announced a three-year, $1 billion investment to develop AI-powered products. “It looked like we were going to spend that much anyway, so we announced it,” Goodnight says flatly.
The problem is that SAS is hardly alone here. It is up against rivals that bet on AI first, and more heavily. On the mega-cap side, there’s Microsoft, Amazon and Oracle. Slightly newer entrants: Snowflake, Databricks, Alteryx and others. On the public sector side, Palantir has been siphoning U.S. government contracts from SAS and others. (Palantir’s U.S. government revenue grew by around double SAS’ total government revenue last year.)
SAS’ modus operandi is to meet customers wherever they are most anxious. The company works with nearly every major bank and the Big Four accounting firms, helping them use AI in ways that are secure, traceable and useful for fraud detection and financial risk. Healthcare, government, finance and other regulated industries are natural terrain for a company that has spent decades selling caution as a feature. Even there, the pressure is rising. Anthropic has been hiring industry experts and in May announced a suite of financial-services products that compete directly for the same customers.
“Everyone is in ‘coopetition,’” Harris says. Customers have asked SAS to integrate with its rivals, and the company has happily obliged.
That has made SAS uniquely malleable among its peers. If customers want their data analysis done in the cloud (Microsoft, Amazon, you name it), SAS can do it. If they want it done on premises, SAS will do that too—and in the programming language of your choice. That matters in hospitals and government agencies, especially when sensitive data and regulation collide here and abroad. In the executive building where customers are flown in for meetings, one screen recently read, “Welcome, U.A.E. Government Delegation.”
Harris thinks new revenue streams can come from digital twins—AI-rendered versions of complex physical facilities like manufacturing plants that are used to figure out a facility’s most efficient layout, predict safety incidents without putting workers at risk, and perform virtual testing—via a partnership with Epic Games. Paper products manufacturer Georgia Pacific, for example, uses them to test and train robots in its Savannah River Mill facility, keeping costs down and employees safe. Digital twins currently generate single-digit millions in revenue, but Harris believes the business can grow to $500 million within three or four years.
SAS is also experimenting with quantum computing for ultra-complex transactions, like in fraud detection for banks, that traditional computers can’t handle. Also in SAS’ plans: using data and AI to help sports teams. In December, SAS announced a partnership with Liverpool to use its products to market to the soccer team’s fans better. At SAS’ 50th anniversary conference, the company announced a smattering of new tools that incorporate AI agents.
“SAS has never met a problem they didn’t want to go after,” says IDC research director Kathy Lange, who previously worked at SAS and suggested that the company could benefit from more focus. “It’s a double-edged sword.”
Believing it’s the best way to sell some of his stake without needing to sell SAS for parts, Goodnight still wants an IPO. But five years after SAS first said it was preparing to go public, the window has narrowed, shifted and occasionally looked like a regret chute.“We don't want to go when all the money has been already used for SpaceX,”
The numbers also need work. Before hitting the roadshow, Goodnight wants to meet the Rule of 40, a common software company benchmark in which revenue growth rate and profit margin sum to 40. That might help the company defend its share price in public markets, especially when pitted against fast-growing competition. But with both components sitting at around 10%, Goodnight says SAS isn’t even halfway there.
For CFO Matt Parson, it’s optionality that’s the key here. SAS has to be ready for the public markets, but they can’t be the only path to helping Goodnight and Sall sell some of their stake. Why sell? The founders’ children aren’t planning to take over, but Goodnight and Sall might still like to leave them with some cash. They’ve yet to take much out of SAS: the company pays out a small dividend, but has invested most profits—“many billions of dollars”—back into the business over its lifetime.
In case an IPO isn’t possible, Parson thus wants to prepare the firm for other solutions: an acquisition or outside investment. The company routinely gets acquisition offers, but Goodnight hasn’t entertained any of them. (The last publicly reported bid was Broadcom’s $15-20 billion offer in 2021; it was progressing until Goodnight changed his mind.) A minority investment could be in the cards, according to Parson, if the right partner came along. If SAS can remain profitable, it can also stay as-is for the foreseeable future: private and founder-owned.
Sipping a cup of black coffee, this time in front of a piece of the Berlin Wall he helped smash, Goodnight is risk-adverse as ever. He is ready to stop being the face of the story he created.
“I wish people knew nothing about me,” he says, with a wink
Turns out no one needs this much compute when everyone can just run quantized Chinese models on their iPhone. Elon the Dogefather had to give all his H100s to Anthropic just to make payroll... Such demand. Much wow.
Corporations are not necessarily pulling the plug on AI, but the initial, unbridled "gold rush" has definitely hit a wall of operational reality. The corporate approach has shifted from a frantic race to adopt any AI tool to a much more cautious, calculated, and sometimes frustrated effort to find actual business value.
The current landscape reveals why companies are reconsidering their initial "rush" strategy, pivoting toward a more structured approach:
During the initial hype, the assumption was that massive individual productivity gains (like writing code or drafting copy five times faster) would automatically translate to corporate profitability. It hasn't. Recent data, including a 2026 enterprise study by Writer, shows that nearly half (48%) of C-suite executives now call their AI adoption a massive disappointment, and only about 29% are seeing a significant return on investment (ROI). Companies are realizing that adding expensive AI tools on top of messy, inefficient legacy processes just creates faster chaos, not better outcomes.
There is a growing, uncomfortable realization in boardrooms that early AI roadmaps were built more for investors and public relations than for actual internal execution. In fact, three-quarters of executives admit their company's AI strategy has been "more for show" than actual operational guidance. Leaders are hitting severe bottlenecks when trying to scale experimental pilot programs into production-ready enterprise workflows.
The rush to implement AI has triggered significant internal friction.
The "AI Elite" vs. Non-Adopters:
Management is aggressively rewarding power users while planning to phase out employees who resist the technology.
Trust Deficits:
According to Cox Business research, nearly 50% of employees hide how much they rely on AI at work due to a lack of clear corporate policies, paired with a lingering fear (around 47%) that the technology will eventually eliminate their jobs.
Loss of Top Talent:
Gartner warned that companies focusing strictly on cutting payroll rather than training their people to use autonomous tools risk losing their best specialized AI talent to competitors.
When corporate IT departments didn't move fast enough to provide official AI tools, employees took matters into their own hands. This explosion of "shadow AI"—workers dropping proprietary code, sensitive financial spreadsheets, or customer data into unapproved, public LLMs—has terrified risk officers. Two-thirds of executives believe their companies have already suffered data breaches or compliance risks due to these unmanaged tools, forcing a hard pause to establish strict governance frameworks.
The Shift to "Agentic" and People-Centric Models
Instead of backing away from AI entirely—corporate spending remains incredibly high—organizations are drastically rewriting their execution playbooks. The "rush" is being replaced by two specific trends:
Moving to Agentic Workflows:
Companies are moving away from simple prompt-and-response chatbots and focusing on specialized "AI agents" built to handle specific, cross-functional business workflows with centralized IT guardrails.
The 80/20 Rule:
Forward-thinking organizations are abandoning the idea of total human replacement. Instead, they are structuring roles around an 80/20 model:
80% of roles are "human-led, AI-augmented" (the Ironman approach, where human judgment is non-negotiable), and 20% are "AI-led, human-supervised" (for high-volume, low-risk, repetitive tasks).
Ultimately, corporate America is learning that while adopting AI technology takes weeks, successfully restructuring a workforce to actually benefit from it takes years. The current pause isn't a retreat; it's a strategic realignment.
_
It's all doom and gloom. Is this AI wave really going to affect people?