{"id":39220,"date":"2026-07-22T17:38:27","date_gmt":"2026-07-22T16:38:27","guid":{"rendered":"https:\/\/www.hult.edu\/blog\/?p=39220"},"modified":"2026-07-24T10:25:16","modified_gmt":"2026-07-24T09:25:16","slug":"ai-faculty-lead-patrick-lynch-on-ai","status":"publish","type":"post","link":"https:\/\/www.hult.edu\/blog\/ai-faculty-lead-patrick-lynch-on-ai\/","title":{"rendered":"AI Won’t Take Your Job, But It Will Change What It Takes to Do It"},"content":{"rendered":"

Hult’s AI Faculty Lead, Patrick Lynch<\/strong>, has spent years studying how humans and AI can work together without losing what makes human judgment irreplaceable. His new book,\u00a0<\/a><\/span>How to\u00a0Outsmart AI and Thrive<\/span><\/i><\/a>, will be on the shelves on July 29.<\/span>\u00a0<\/span><\/p>\n

Ahead of the launch, we spoke to him about the misconceptions holding leaders back, what businesses need to do to move forward, and what you should do this Monday morning.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Hult:\u00a0Your book opens with a provocative idea: AI may not\u00a0take\u00a0your job, but it will change what it takes to do it.\u00a0What’s\u00a0the most common misconception you see business leaders holding\u00a0onto\u00a0about\u00a0AI and the future of work?<\/span><\/b>\u00a0<\/span>\u00a0<\/span><\/h2>\n

Patrick:<\/span><\/b>\u00a0The most common misconception is\u00a0very\u00a0expensive: leaders treat AI as a project. Projects end. AI is\u00a0a\u00a0practice. AI compounds. Get that\u00a0wrong,\u00a0and you feed both sides of the AI panic: the\u00a0doomers\u00a0who say\u00a0it’s\u00a0coming for our jobs and the hype crowd who say\u00a0it’ll\u00a0remake everything overnight\u00a0(often the people selling us the tools).<\/span>\u00a0<\/span><\/p>\n

If the question is, will AI replace some tasks and augment others? The answer\u00a0is yes. And yet,\u00a0Daron\u00a0Acemoglu,\u00a0a\u00a0Nobel Prize-winning MIT economist,\u00a0doubts any occupation that exists today will be eliminated in five or ten years.\u00a0Instead,\u00a0leaders should invest in changing what it takes to do jobs, tapping into new\u00a0capabilities,\u00a0and\u00a0creating new value over cost-cutting.\u00a0That’s\u00a0augmentation\u00a0over imitation.<\/span><\/p>\n

\u201cLeaders should invest in changing what it takes to do jobs, tapping into new capabilities, and creating new value over cost-cutting.\u201d<\/span>\u00a0<\/span><\/p><\/blockquote>\n

H:\u00a0Creating new value over cost-cutting feels like an important distinction. How can business leaders\u00a0make sure\u00a0they’re\u00a0doing\u00a0this\u00a0right?<\/span><\/b>
\n\u00a0<\/span><\/h2>\n

P:<\/strong>\u00a0Using\u00a0AI\u00a0technology to imitate what you already do, just faster, is a trap I call\u00a0\u201cvanity AI.\u201d\u00a0The alternative,\u00a0viable\u00a0AI, is using\u00a0AI\u00a0to create value\u00a0you\u00a0couldn’t\u00a0create before. That often takes collaboration with AI tools, people, or both. To get there,\u00a0you reimagine the jobs and the teams.\u00a0<\/span>\u00a0<\/span><\/p>\n

Yesterday’s silos, with people in one box and data in another, are wrong for work where the value comes from collaboration.<\/span>\u00a0<\/span><\/p>\n

H: Can you\u00a0give us an example of\u00a0how\u00a0viable\u00a0AI\u00a0works\u00a0in\u00a0practice?<\/span><\/b>\u00a0<\/span><\/h2>\n

P:<\/strong>\u00a0Two studies drew the line between when\u00a0viable\u00a0AI works and when\u00a0it\u00a0doesn’t. At Procter & Gamble, they took\u00a0nearly\u00a0800\u00a0professionals, split them into individuals and teams, gave half of them AI and half nothing, and had them\u00a0brainstorm\u00a0new products.\u00a0The teams working with AI generated more creative solutions and did it faster than the people working alone.\u00a0<\/span>\u00a0<\/span><\/p>\n

The second study gave the same AI tool to employees at IG, a UK financial services firm, split across writers, marketing staff, and developers.\u00a0Everyone planned equally well with AI.\u00a0<\/span><\/p>\n

However, only the people with existing marketing\u00a0expertise\u00a0could turn that plan into a promotional pitch.\u00a0That’s\u00a0good news for educators,\u00a0because foundational knowledge and skills still matter,\u00a0maybe matter\u00a0more than ever, to get value from AI.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

\u00a0<\/span><\/p>\n

\n

\u201cFoundational\u00a0knowledge and skills still matter,\u00a0maybe matter\u00a0more than ever, to get value from AI.\u201d<\/span>\u00a0<\/span><\/p>\n<\/blockquote>\n

\u00a0<\/span><\/p>\n

H: In your book, you draw on other stories from companies like Stitch Fix, GitHub, and JPMorgan Chase. Was there a moment from one of those organizations that genuinely surprised you? Something that shifted your own thinking about how AI and humans can work together?<\/span><\/b>\u00a0<\/span><\/h2>\n

P:<\/strong>\u00a0The real surprise came from stepping back and looking across companies.\u00a0Two\u00a0things\u00a0really stand out, both about expectations we set too high and too fast.<\/span>\u00a0<\/span><\/p>\n

The first is the productivity paradox. In 1987, after a decade of heavy IT spending, economist Robert Solow wrote,\u00a0\u201cYou can see the computer age everywhere but in the productivity statistics.\u201d\u00a0Nearly forty\u00a0years later, economist Torsten Slok said almost\u00a0exactly the same\u00a0thing about AI:\u00a0\u201cAI is everywhere except in the incoming macroeconomic data.\u201d\u00a0<\/span>\u00a0<\/span><\/p>\n

A February 2026 NBER survey of\u00a0roughly 6,000\u00a0executives found\u00a0nearly nine\u00a0in ten firms have seen no measurable dent in productivity or employment from AI in three years.<\/span>\u00a0<\/span><\/p>\n

What surprises\u00a0me\u00a0is\u00a0our impatience and amnesia. Electricity took about forty years to show up in\u00a0the productivity\u00a0data. The last computing wave took about\u00a0twenty. In November 2022, ChatGPT launched the democratized generative AI era, and\u00a0it’s\u00a0too early to call it a bust on tonight’s evening news. Give it a beat. Roll up your sleeves and be the change you want to\u00a0see.\u00a0There\u00a0is\u00a0a need and obligation to do so because the future of education and work depends on it.<\/span>\u00a0<\/span><\/p>\n

The second surprise cuts the other way. AI is supposed to save time,\u00a0and,\u00a0in plenty of ways,\u00a0it does.\u00a0But an eight-month study tracking AI use\u00a0at\u00a0one company found the opposite happening.\u00a0One engineer put it,\u00a0\u201cYou had thought\u00a0that maybe, because\u00a0you could be more productive with AI, you could work less. But then really, you\u00a0don’t\u00a0work less. You just work the same amount or even more.”\u00a0<\/span>\u00a0<\/span><\/p>\n

The study found that as people used AI, their work intensified and blurred boundaries between jobs. Prompting an AI feels more like chatting than laboring, and multitasking climbed as people used AI alongside their own effort rather than in place of it. AI is expanding what we ask of ourselves and others\u00a0nearly as\u00a0fast as it saves us time.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

\u201cRoll up your sleeves and be the change you want to see. The future of education and work depends on it.\u201d\u00a0<\/span><\/p><\/blockquote>\n

H: Many professionals must be feeling that AI is expanding what we expect from ourselves. Part of that must be associated with the fear of humans being replaced by AI.<\/span><\/b>\u00a0<\/span><\/h2>\n

P:<\/strong>\u00a0What’s\u00a0surprising is\u00a0that\u00a0we keep forgetting\u00a0we’ve\u00a0been here before.\u00a0Remember\u00a0when automated teller machines (ATMs)\u00a0made\u00a0cash\u00a0accessible\u00a0at every corner store? That cut the number of bank tellers per branch by about a third.\u00a0<\/span>\u00a0<\/span><\/p>\n

But, because branches got cheaper to run, banks opened roughly 40% more of them, so total teller employment nearly doubled in the following decade. The tellers who remained shifted work, moving from clerk tasks into relationship-driven work, selling credit cards, loans, and investments, and solving customer problems. Economist David Autor frames this best when he explained that automating part of a job increases the value of the human tasks that remain.<\/span>\u00a0<\/span><\/p>\n

As this scales, I anticipate that the organizations five years from now will look different from the ones we have today, because so much of this is still being built, tested, and renegotiated. And, the last time I checked, that kind of change is exactly what spurs learning, builds expertise, and gets people ready to do something with it. Worry less. Inspire more. Get on with the work.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

\u201cAutomating part of a job increases the value of the human tasks that remain.\u201d<\/span> \u00a0<\/span><\/p><\/blockquote>\n

H: You talk about embedding human values into AI systems from the start. Who owns that\u00a0responsibility, and how do you stop it from becoming just another compliance checkbox?<\/span><\/b>\u00a0<\/span><\/h2>\n

P:\u00a0<\/strong>The short answer to \u201cwho owns it\u201d\u00a0is:\u00a0you do. Not the\u00a0legal team, not a compliance officer. The days when a leader could hide behind an algorithm are gone.<\/span>\u00a0<\/span><\/p>\n

In February 2024, Air Canada’s website chatbot invented a bereavement-fare discount the airline\u00a0didn’t\u00a0really offer. A grieving customer booked a full-fare ticket, trusting it would be refunded. Air Canada’s defense? It argued the chatbot was a \u201cseparate legal entity,\u201d responsible for its own words, as if the bot should lawyer up on its own. The tribunal\u00a0wasn’t\u00a0amused and\u00a0held the airline liable.<\/span>\u00a0<\/span><\/p>\n

On the horizon, the EU AI Act’s high-risk obligations soon become\u00a0binding,\u00a0and GDPR’s Article 22 already gives people the right not to be subject to a fully automated decision with no human review. Regulators are converging on the same idea: accountability\u00a0can’t\u00a0be outsourced to a tool.\u00a0It’s\u00a0on you.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

So,\u00a0in practice, ownership\u00a0isn’t\u00a0a department.\u00a0It’s\u00a0a commitment every team makes and\u00a0can’t\u00a0automate away. While AI may run in your operations, someone still\u00a0has to\u00a0hold onto what your company is and is not. What\u00a0it will\u00a0and\u00a0won’t\u00a0do.\u00a0It’s\u00a0a leadership job.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

H: A lot of AI leadership books are written for the C-suite. But transformation lives or dies at the manager and team level. What’s your message to the people in the middle who are trying to implement this without a clear mandate from above?<\/span><\/b>\u00a0<\/span><\/h2>\n

P:<\/strong>\u00a0My message to the middle is that you have far more power than you think. You may not have a mandate, but you rarely need one to start. You need a prototype, a small win, and eventually a few aligned peers to scale it.<\/span>\u00a0<\/span><\/p>\n

Take note of what Honeywell did. 95,0000 employees got access to generative AI. Leadership didn’t hand down a transformation plan or decide in advance which jobs would change. They did three things: invited employees to submit ideas for how to use the tools, prioritized those ideas by impact, and let the strongest ones scale. Sixteen use cases reached production. IT tickets dropped 80%. GitHub adoption among engineers hit 65%, adding 90,000 lines of code per week. That came from three things: access, invitation, and filter.<\/span>\u00a0<\/span><\/p>\n

The World Economic Forum echoed this in its\u00a0<\/span>Four\u00a0Futures for\u00a0Jobs<\/span><\/i><\/a>\u00a0report. It suggests you pair your most AI-fluent junior person with your most experienced senior one on a real task. Let the junior show the senior what the tool can do. Let the senior show the junior where it\u00a0gets it\u00a0wrong. That closes a cultural gap while building an understanding of what works and what\u00a0doesn’t.<\/span>\u00a0<\/span><\/p>\n

Access is the part you may feel stuck on. Someone with authority needs to turn the tools on. But the invitation and filter are yours. Invite your team to find the tasks they’d love to hand off, then filter for the lowest-risk ones and pilot those. Start small, fail cheap, and scale only what proves itself. <\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

BCG estimates about 70% of the value from AI adoption comes from people and process and only 10% from the technology itself. That 70% is sitting in your hands right now. Make it happen.<\/span>\u00a0<\/span><\/p>\n

H: We’re at a moment where business schools are grappling with the same thing you pose to leaders: shape this moment or let it shape you. As Hult’s AI Faculty Lead, how do you think management education needs to evolve to produce graduates who are genuinely AI-ready, not just AI-aware?<\/span><\/b>\u00a0<\/span><\/h2>\n

P: <\/strong><\/span>AI tools are the easy part now. Decisions\u00a0are the differentiator.\u00a0That’s\u00a0the difference between AI-aware and AI-ready.<\/span>\u00a0<\/span><\/p>\n

AI-aware means you can define its components and rattle off differences between machine learning and large language models, passing a quiz on it. AI-ready means you can stand behind a decision you made with AI when someone pushes back on it. Too many business schools are still teaching the first thing and calling it the second.\u00a0<\/span>\u00a0<\/span><\/p>\n

Our accreditors, like AACSB, are already moving beyond the idea that AI competency means knowing how a model works. Newer fluency frameworks organize the skill around four habits: delegation, description, discernment, and diligence.<\/span>\u00a0<\/span><\/p>\n

Anthropic tested that framework, analyzing thousands of conversations for its recent <\/span>AI Fluency Index<\/span><\/i><\/a>.\u00a0Here\u2019s\u00a0the\u00a0finding that should\u00a0worry\u00a0every business school: people are highly directive, good at describing what they want and delegating tasks to AI, but far less evaluative. When an AI’s output looks polished, people stop questioning whether\u00a0it’s\u00a0right.\u00a0That’s\u00a0discernment, and\u00a0it’s\u00a0the hardest to teach.<\/span>\u00a0<\/span><\/p>\n

Today’s business students need metacognitive judgment skills: the ability to\u00a0monitor\u00a0their\u00a0own thinking while using the tools. If schools are teaching students to be good individual users of AI tools, they are outdated and overmatched to meet future work demands.\u00a0<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

What graduates need from the first day on the job is the ability to collaborate with hybrid teams\u2014some humans, some agents\u2014and know when to trust the work and when to challenge it.\u00a0That’s\u00a0a different skill than knowing how to prompt well. Business schools that build toward that will produce graduates who are AI-ready.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

\u201cWhen an AI’s output looks polished, people stop questioning whether\u00a0it’s\u00a0right.\u00a0That’s\u00a0discernment, and\u00a0it’s\u00a0the hardest to teach.\u201d<\/span>\u00a0<\/span><\/p><\/blockquote>\n

H: Hult is launching the AI Lab this September as part of our postgraduate programs, where students will learn to design, deploy, and supervise AI agents in live business environments. From your research and experience, how critical is that kind of hands-on, applied learning compared to more theoretical approaches to AI education?<\/span><\/b>\u00a0<\/span><\/h2>\n

P: <\/strong>Very critical. You can lecture a student through a framework for evaluating AI output.\u00a0You cannot lecture them into what it feels like to watch an agent miscue in front of a real client and have to decide, in the moment, what to do about it.\u00a0That’s\u00a0the whole case for hands-on\u00a0learning\u00a0over theory.\u00a0Judgment\u00a0is only real when something real is at stake.<\/span>\u00a0<\/span><\/p>\n

That’s\u00a0what a lab does that a lecture\u00a0can’t. A student designs an agent, deploys it into a live business problem, and supervises it. They make the call on what to trust, what to fix, and what to shut down. They leave better\u00a0prepared\u00a0having already made those calls.<\/span>\u00a0<\/span><\/p>\n

One thing\u00a0I’m\u00a0watching\u00a0as\u00a0this scales\u00a0is how we prepare our graduates to lead change. Learning to re-role a team, to get creativity and accountability out of humans and machines together, is fast becoming the job itself. The\u00a0AI\u00a0Lab is the difference between a graduate who’s heard about AI and one\u00a0who’s\u00a0already led it.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

\u201cTo get creativity and accountability out of humans and machines together is fast becoming the job itself.\u201d<\/span> \u00a0<\/span><\/p><\/blockquote>\n

H: Your book is deliberately practical. You want readers to know what to do on Monday morning. What’s the one thing a business leader could do right now to start building a healthier relationship with AI in their organization?<\/span><\/b>\u00a0<\/span>\u00a0<\/span><\/h2>\n

He\u00a0didn’t\u00a0need a computer science degree because he had something better: curiosity. Einstein put it better than I can:\u00a0\u201cI have no special talent. I am only passionately curious.\u201d\u00a0In a space changing this fast,\u00a0that’s\u00a0the whole strategy. The people getting ahead right now are the ones who keep asking\u00a0\u201cwhat if\u201d\u00a0after the first small win, technical background or not.<\/span>\u00a0<\/span><\/p>\n

So, here’s how you start your own version of what he did: open whatever AI tool you already use. Tell it, \u201cYou’re my career coach, and my goal is to cut the routine work in my week and free up time for something better.\u201d <\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Then,\u00a0ask it to interview\u00a0you\u00a0with\u00a0ten or twelve\u00a0questions\u00a0about what you really do all week:\u00a0the tasks, the frustrations,\u00a0and\u00a0what you wish you had more time for.\u00a0At the end, ask it to hand your answers back to you as\u00a0a new version\u00a0of your job.<\/span>\u00a0<\/span><\/p>\n

Do that yourself before you ask anyone on your team to. That’s the whole first step. Everything that Hult grad built started with one curious question: what else is possible? <\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

\u201cThe people getting ahead right now are the ones who keep asking: what if.<\/span>\u201d\u00a0<\/span><\/p><\/blockquote>\n

\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

\u00a0__________________________________________<\/span><\/p>\n

\"New<\/span><\/i>Hult AI Faculty Lead Patrick Lynch’s book, How\u00a0To\u00a0Outsmart AI and Thrive<\/em>, publishes July 29. You can pre-order your copy here.<\/a><\/h3>\n

The new Hult AI Lab launches this September as part of our postgraduate programs. Students will design, deploy, and supervise AI agents in live business environments and earn a Hult Certificate in Applied AI. To find out more, visit: hult.edu\/ai-lab\u00a0\u00a0<\/a><\/h3>\n","protected":false},"excerpt":{"rendered":"

Hult’s AI Faculty Lead, Patrick Lynch, has spent years studying how humans and AI can work together without losing what makes human judgment irreplaceable. His new book,\u00a0How to\u00a0Outsmart AI and…<\/p>\n","protected":false},"author":4,"featured_media":39233,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[114],"tags":[181,900,914,175,205],"yoast_head":"\nAI Won't Take Your Job, But It Will Change What It Takes to Do It<\/title>\n<meta name=\"description\" content=\"Hult's AI Faculty Lead Patrick Lynch talks about the future of work, AI-human collaboration, and his new book: How to Outsmart AI and Thrive.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI Won't Take Your Job, But It Will Change What It Takes to Do It\" \/>\n<meta property=\"og:description\" content=\"Hult's AI Faculty Lead Patrick Lynch talks about the future of work, AI-human 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P: <\/strong>A former Hult MBA<\/a> student of mine, a self-described non-techie, just\u00a0emailed\u00a0to say\u00a0he’d\u00a0built his first AI app and shipped it as a Chrome extension. Now\u00a0he’s\u00a0sketching a product roadmap to add features and\u00a0maybe turn\u00a0it into\u00a0a real business.<\/span>\u00a0<\/span><\/p>\n