May Habib, co-founder and CEO of Writer AI, delivered one of many bluntest assessments of company AI failures on the TED AI conference on Tuesday, revealing that just about half of Fortune 500 executives consider synthetic intelligence is actively damaging their organizations — and putting the blame squarely on management's shoulders.
The issue, in accordance with Habib, isn't the know-how. It's that enterprise leaders are making a class error, treating AI transformation like earlier know-how rollouts and delegating it to IT departments. This method, she warned, has led to "billions of {dollars} spent on AI initiatives which can be going nowhere."
"Earlier this 12 months, we did a survey of 800 Fortune 500 C-suite executives," Habib instructed the viewers of Silicon Valley executives and traders. "42% of them mentioned AI is tearing their firm aside."
The prognosis challenges typical knowledge about how enterprises ought to method AI adoption. Whereas most main firms have stood up AI task forces, appointed chief AI officers, or expanded IT budgets, Habib argues these strikes replicate a elementary misunderstanding of what AI represents: not one other software program device, however a wholesale reorganization of how work will get accomplished.
"There’s something leaders are lacking after they examine AI to only one other tech device," Habib mentioned. "This isn’t like giving accountants calculators or bankers Excel or designers Photoshop."
Why the 'outdated playbook' of delegating to IT departments is failing firms
Habib, whose firm has spent 5 years constructing AI programs for Fortune 500 firms and logged two million miles visiting buyer websites, mentioned the sample is constant: "When generative AI began displaying up, we turned to the outdated playbook. We turned to IT and mentioned, 'Go determine this out.'"
That method fails, she argued, as a result of AI basically adjustments the economics and group of labor itself. "For 100 years, enterprises have been constructed round the concept that execution is pricey and exhausting," Habib mentioned. "The enterprise constructed advanced org charts, advanced processes, all to handle individuals doing stuff."
AI inverts that mannequin. "Execution goes from scarce and costly to programmatic, on-demand and considerable," she mentioned. On this new paradigm, the bottleneck shifts from execution capability to strategic design — a shift that requires enterprise leaders, not IT departments, to drive transformation.
"With AI know-how, it could now not be centralized. It's in each workflow, each enterprise," Habib mentioned. "It’s now an important a part of a enterprise chief's job. It can’t be delegated."
The assertion represents a direct problem to how most massive organizations have structured their AI initiatives, with centralized facilities of excellence, devoted AI groups, or IT-led implementations that enterprise models are anticipated to undertake.
A generational energy shift is going on based mostly on who understands AI workflow design
Habib framed the shift in dramatic phrases: "A generational switch of energy is going on proper now. It's not about your age or how lengthy you've been at an organization. The generational switch of energy is in regards to the nature of management itself."
Conventional management, she argued, has been outlined by the flexibility to handle complexity — massive groups, massive budgets, intricate processes. "The id of leaders at these firms, individuals like us, has been tied to old fashioned energy buildings: management, hierarchy, how massive our groups are, how massive our budgets are. Our worth is measured by the sheer quantity of complexity we may handle," Habib mentioned. "Right this moment we reward leaders for this. We promote leaders for this."
AI makes that mannequin out of date. "When I’m able to 10x the output of my workforce or do issues that might by no means be attainable, work is now not in regards to the 1x," she mentioned. "Management is now not about managing advanced human execution."
As an alternative, Habib outlined three elementary shifts that outline what she calls "AI-first leaders" — executives her firm has labored with who’ve efficiently deployed AI brokers fixing "$100 million plus issues."
The primary shift: Taking a machete to enterprise complexity
The brand new management mandate, in accordance with Habib, is "taking a machete to the complexity that has calcified so many organizations." She pointed to the layers of friction which have gathered in enterprises: "Good concepts dying in memos, the countless cycles of approvals, the loss of life by 1,000 clicks, conferences about conferences — a loss of life, by the way in which, that's occurring in 17 completely different browser tabs every for software program that guarantees to be a single supply of reality."
Quite than accepting this complexity as inevitable, AI-first leaders redesign workflows from first rules. "There are only a few legacy programs that may't get replaced in your group, that gained't get replaced," Habib mentioned. "However they're not going to get replaced by one other monolithic piece of software program. They’ll solely get replaced by a enterprise chief articulating enterprise logic and getting that into an agentic system."
She supplied a concrete instance: "We have now clients the place it used to take them seven months to get a inventive marketing campaign — not even a product, a marketing campaign. Now they’ll go from TikTok development to digital shelf in 30 days. That’s radical simplicity."
The catch, she emphasised, is that CIOs can't drive this transformation alone. "Your CIO can't assist flatten your org chart. Solely a enterprise chief can take a look at workflows and say, 'This half is important genius, this half is official scar tissue that has to go.'"
The second shift: Managing the worry as profession ladders disappear
When AI handles execution, "your people are liberated to do what they're superb at: judgment, technique, creativity," Habib defined. "The outdated management playbook was about managing headcount. We managed individuals towards income: one enterprise improvement rep for each three account executives, one marketer for each 5 salespeople."
However this liberation carries profound challenges that leaders should deal with immediately. Habib acknowledged the elephant within the room that many executives keep away from discussing: "These adjustments are nonetheless horrifying for individuals, even when it's change into unholy to speak about it." She's witnessed the worry firsthand. "It reveals up as tears in an AI workshop when somebody looks like their outdated talent set isn't translated to the brand new."
She launched a time period for a typical type of resistance: "productiveness anchoring" — when workers "cling to the exhausting method of doing issues as a result of they really feel productive, as a result of their self-worth is tied to them, even when empirically AI may be higher."
The answer isn't to look away. "We have now to design new pathways to influence, to point out your individuals their worth just isn’t in executing a process. Their worth is in orchestrating programs of execution, to ask the subsequent nice query," Habib mentioned. She advocates changing profession "ladders" with "lattices" the place "individuals have to develop laterally, to increase sideways."
She was candid in regards to the disruption: "The primary rungs on our profession ladders are certainly going away. I do know as a result of my firm is automating them." However she insisted this creates alternative for work that’s "extra inventive, extra strategic, extra pushed by curiosity and influence — and I consider much more human than the roles that they're changing."
The third shift: When execution turns into free, ambition turns into the one bottleneck
The ultimate shift is from optimization to creation. "Earlier than AI, we used to name it transformation once we took 12 steps and made them 9," Habib mentioned. "That's optimizing the world as it’s. We will now create a brand new world. That’s the greenfield mindset."
She challenged executives to establish assumptions their industries are constructed on that AI now disrupts. Author's clients, she mentioned, are already seeing new classes of progress: treating each buyer like their solely buyer, democratizing premium providers to broader markets, and coming into new markets at unprecedented pace as a result of "AI strips away the friction to entry new channels."
"When execution is considerable, the one bottleneck is the scope of your individual ambition," Habib declared.
What this implies for CIOs: Constructing the stadium whereas enterprise leaders design the performs
Habib didn't go away IT leaders and not using a position — she redefined it. "If tech is everybody's job, you may be asking, what’s mine?" she addressed CIOs. "Yours is to offer the mission essential infrastructure that makes this revolution attainable."
As tens or lots of of 1000’s of AI brokers function at numerous ranges of autonomy inside organizations, "governance turns into existential," she defined. "The enterprise chief's job is to design the play, however you must construct the stadium, you must write the rule e book, and you must be certain these performs can win at championship scale."
The formulation suggests a partnership mannequin: enterprise leaders drive workflow redesign and strategic implementation whereas IT offers the infrastructure, governance frameworks, and safety guardrails that make mass AI deployment protected and scalable. "One can't succeed with out the opposite," Habib mentioned.
For CIOs and technical leaders, this represents a elementary shift from gatekeeper to enabler. When enterprise models deploy brokers autonomously, IT faces governance challenges in contrast to something in enterprise software program historical past. Success requires real partnership between enterprise and IT — neither can succeed alone, forcing cultural adjustments in how these capabilities collaborate.
An actual instance: From multi-day scrambles to prompt solutions throughout a market disaster
To floor her arguments in concrete enterprise influence, Habib described working with the chief shopper officer of a Fortune 500 wealth advisory agency throughout current market volatility following tariff bulletins.
"Their telephone was ringing off the hook with clients making an attempt to determine their market publicity," she recounted. "Each request kicked off a multi-day, multi-person scramble: a portfolio supervisor ran the present, an analyst pulled charts, a relationship supervisor constructed the PowerPoint, a compliance officer needed to overview every thing for disclosures. And the chief in all this — she was forwarding emails and chasing updates. That is the highest job: managing complexity."
With an agentic AI system, the identical work occurs programmatically. "A system of brokers is ready to assemble the reply quicker than any variety of individuals may have. No extra midnight deck evaluations. No extra days on finish" of coordination, Habib mentioned.
This isn't about marginal productiveness good points — it's about basically completely different working fashions the place senior executives shift from managing coordination to designing clever programs.
Why so many AI initiatives are failing regardless of large funding
Habib's arguments arrive as many enterprises face AI disillusionment. After preliminary pleasure about generative AI, many firms have struggled to move beyond pilots and demonstrations to manufacturing deployments producing tangible enterprise worth.
Her prognosis — that leaders are delegating quite than driving transformation — aligns with rising proof that organizational elements, not technical limitations, clarify most failures. Firms usually lack readability on use instances, wrestle with information preparation, or face inner resistance to workflow adjustments that AI requires.
Maybe probably the most hanging facet of Habib's presentation was her willingness to acknowledge the human value of AI transformation — and demand leaders deal with it quite than keep away from it. "Your job as a frontrunner is to not look away from this worry. Your job is to face it with a plan," she instructed the viewers.
She described "productiveness anchoring" as a type of "self-sabotage" the place workers resist AI adoption as a result of their id and self-worth are tied to execution duties AI can now carry out. The phenomenon means that profitable AI transformation requires not simply technical and strategic adjustments however psychological and cultural work that many leaders could also be unprepared for.
Two challenges: Get your arms soiled, then reimagine every thing
Habib closed by throwing down two gauntlets to her government viewers.
"First, a small one: get your arms soiled with agentic AI. Don't delegate. Select a course of that you just oversee and automate it. See the distinction from managing a posh course of to redesigning it for your self."
The second was extra bold: "Return to your workforce and ask, what may we obtain if execution had been free? What would work really feel like, be like, appear to be when you're unbound from the friction and course of that slows us down right this moment?"
She concluded: "The instruments for creation are in your arms. The mandate for management is in your shoulders. What is going to you construct?"
For enterprise leaders accustomed to viewing AI as an IT initiative, Habib's message is evident: that method isn't working, gained't work, and displays a elementary misunderstanding of what AI represents. Whether or not executives embrace her name to personally drive transformation — or proceed delegating to IT departments — could decide which organizations thrive and which change into cautionary tales.
The statistic she opened with lingers uncomfortably: 42% of Fortune 500 C-suite executives say AI is tearing their firms aside. Habib's prognosis suggests they're tearing themselves aside by clinging to organizational fashions designed for an period when execution was scarce. The treatment she prescribes requires leaders to do one thing most discover uncomfortable: cease managing complexity and begin dismantling it.
