Why AI Transformation Fails Without an "Enterprise IQ": Four BCG Korea Partners on Reshaping Work
EO Korea
Companies around the world are pouring money into AI, yet many struggle to say what has actually changed. In this documentary, partners from Boston Consulting Group's Korea office discuss why that happens and what separates the companies that get results. Their position is that AI is only a means. Rolling out tools, assigning an AI executive, or launching dozens of pilots does not by itself transform a business. What matters is redesigning how the company works around the logic of how it wins in its market. The partners also describe how the same pressures are reshaping consulting itself, and why they think Korean companies are unusually well placed in this period.
From "What" and "Why" to "How"
One partner identifies the biggest change in client conversations over the past two or three years. In late 2022, executives were still asking what AI fundamentally was, and then why they should bring it into their business at all. Today, the partner says, almost no executives raise "what" or "why." The conversation is about "how": how to apply AI meaningfully to their business environment and to their own company in particular. Questions from an applied-AI perspective have become far more common, and the partner calls this a defining shift.
From a Chief AI Officer to the CEO
The partners compare the current wave with the mobile era after the iPhone. Back then, "mobile" was the buzzword and every company was told it needed a platform business. BCG observed companies creating a Chief Digital Officer role and driving change around that executive. The first two or three years of the AI wave looked similar, with companies appointing an AI executive to lead the effort.
According to the partners, that pattern is now changing quickly. Many people doubt that a Chief AI Officer alone can drive a company's entire AI transformation. Instead, CEOs are concluding that AI is the most important item on the company's agenda and that they should lead it personally. The partners report a sharp difference in business performance between companies where the CEO owns AI, invests heavily, and drives it, and companies where AI is a mid-level priority or not a priority. They believe companies that embed AI structurally across the organization to raise productivity and profitability will separate clearly from those that cannot, and that the gap will widen.
Two Approaches: Bottom-Up and Top-Down
One partner says the ways companies adopt AI, which they call "AI-izing," are becoming very diverse. They group the approaches into two broad camps. In the bottom-up approach, a company rolls out AI services such as OpenAI or Claude to every employee and hopes for productivity gains. In the top-down approach, a company asks how AI can reshape its fundamental sources of competitive advantage.
The partner sees the second question as the central one of this era: how to use a top-down approach to redefine the competitive edge a company holds. Many companies understand AI, the partner says, but few approach it in a way that actually produces results.
"Deploy" Versus "Reshape," and the Idea of Enterprise IQ
The first key point, one partner says bluntly, is that AI is merely a means. In "AI transformation," the emphasis often falls on the AI when it should fall on the transformation, and companies become absorbed in adopting the technology for its own sake.
The partner illustrates this with new product development at consumer companies, which typically takes six months to a year. Under a "deploy" approach, the company keeps its existing way of working, breaks it into tasks, and inserts AI here and there to speed things up. "Reshape" is different. The AI has to understand the logic by which the company reads its market and extracts insight. BCG calls this Enterprise IQ, and the partner describes it as the company's "brain."
The real value, in this view, does not come from building faster hands or more hands. It comes from whether those hands and feet are built together with a brain that carries the company's way of winning in its own market. The partner argues that how well a company builds this Enterprise IQ decides success or failure, and that it has to be built in-house. OpenAI cannot build it for you and neither can Palantir. Only the company that knows its own logic can.
So the starting question is not "where can we use AI?" but "what does a successful new product actually rest on?" If BCG were to reshape new product planning, the partner explains, it would use AI to read the market and identify opportunity areas, then quickly generate many candidate product concepts instead of one. The partner says this would compress a six-to-twelve-month process to about one or two months. Instead of committing to a single concept for half a year or more, the team would start with several and narrow down to those with the highest probability of success. The point is to redesign the whole sequence of product-planning work from scratch, not to wedge AI into the existing process. The partner says many companies still take the simple deploy approach and therefore fail to reach meaningful results quickly, something BCG often sees in the field.
Goldman Sachs: From a Hundred Pilots to Five or Six Workflows
As an example of a course correction, one partner cites Goldman Sachs. According to the partner, CEO David Solomon described how, before 2024, the bank pursued company-wide AI transformation by running about a hundred different proofs of concept at once. That approach did not produce proper success stories, and Solomon acknowledged the failure. From 2024, the partner says, Goldman Sachs pivoted to a philosophy of transforming the five or six most critical workflows that touch the fundamentals of the business.
The People Problem: "I'd Put It at 70%"
The partners argue that the hardest part of AI transformation is neither the technology nor the data and infrastructure. It is the organizations and people who must lead the change, and the work of managing that change. One partner estimates that people account for 70% of the overall difficulty. BCG advises on AI strategy and platforms and designs and builds them, the partner says, but where the team concentrates its effort is how the work runs in the field and how people actually change along with it.
Another partner adds that the emphasis in "AI transformation" falls too heavily on AI. It is a redesign that assumes new technology will be adopted, so it must be accompanied by changes in ways of working, processes, and if necessary the organization itself. Otherwise, however good the AI is, results will not follow. The partner presents this kind of work, which requires deep organizational understanding and close, continuous engagement, as familiar ground for firms like BCG.
How AI Is Changing Consulting Itself
The partners say BCG partners from around the world recently met to discuss how the consulting business should evolve. One partner describes leaving with two feelings at once. One was hope that AI is pushing the business to evolve and expanding its opportunities. The other was anxiety that consulting might be diminished by AI or disappear entirely. The partner says both feelings still coexist inside the firm.
In their account, BCG used to be a firm that excelled at setting strategic direction and advising on execution. It is now becoming a firm that also combines the technical elements needed downstream to deliver real impact. Internally, they say, BCG describes itself less as a consulting firm and more as an "impact company" or "impact core." One partner summarizes the new role as an orchestrator that coordinates the entire process.
One partner says consulting exists to solve client problems. Clear impact for the client, such as a better business, revenue growth, much greater cost efficiency, or a real change in how people work, is the reason the firm exists, and without it the firm cannot survive. The partner's central message is that using AI everywhere is not what matters. Applying it well, in the right places, and getting results is the only measure.
The partners say BCG is reorganizing around two axes: strategy and applied AI. The emphasis is on AI actually applied inside companies and on how that application drives change, not on AI as a technology in itself. They describe this as walking the "reshape and reimagination journey" together with clients. On the talent side, BCG is building teams of AI engineers, data scientists, and other builders, along with forward-deployed engineers (FDEs) who are embedded on-site to understand and solve client problems in depth. One partner describes the aim as an FDE organization broad and deep enough to hold its own against fast-growing enterprise software companies, and calls the firm's strategic focus on AI a deep commitment rather than a slogan.
Another partner argues that BCG's essence has not changed, because its mission is still to create results. What has expanded is the service offering. It now covers strategy, execution combined with technology, and embedding the change inside the company, including change management and operating-model change, because results only come when all of these change together.
What Kind of Talent Matters Now
One partner says companies increasingly tell them they want people who ask good questions, on the theory that in the AI era everything comes down to prompting well. The partner notes that BCG has wanted curious people who ask good questions since its start, which they date to 1993. Now, however, AI is getting good at asking, defining problems, solving them, and communicating them. What matters more at BCG today is taking a well-solved problem, persuading people with rapport and empathy, and then actually carrying it through together. The partner describes people who can appeal to both reason and emotion, and who then execute, see results, and create value, as far more valuable than before.
Another partner frames the shift in broader terms. Because this is artificial intelligence, intelligence itself is becoming universal: reasoning, logical thinking, and access to knowledge are being handed to everyone. In that world, the partner says, people with only technical expertise will find less and less room, while people who can design, plan, and drive the whole effort will become more valuable, at BCG as elsewhere. The partner calls this profile the "integrated builder-thinker": someone who can build, think, and use tools including AI. The partner expects client expectations to move sharply toward delivered outcomes, so consultants who can deliver results end to end will provide more value and take on bigger roles.
"AI Will Reshape More Jobs"
The partners point to a recent BCG report titled "AI Will Reshape More Jobs." As they explain it, the message is not that AI will eliminate jobs. It is that the thousands of task combinations that make up today's work will be reorganized and transformed by AI. Their practical advice is to sketch how your current work will be redefined by AI and then use that picture to redesign how you work and how you lead your organization. They call this probably the most useful way to break through in a confusing, unprecedented situation.
Size Doesn't Decide Who Leads
One partner says AI progress has little to do with company size or revenue. Large companies are not necessarily ahead of small and mid-sized ones. Because large companies run on massive systems, the partner says, they often become late movers in AI adoption, while smaller companies frequently charge ahead.
Why the Partners See an Opening for Korea
The partners say interest and drive around AI are especially strong among Asian companies, and among those, Korean companies' drive feels exceptional on the ground. One partner suggests many people see generative AI as a chance to structurally overturn a game whose rules have long been written by the West. In consumer goods, for example, marketing is the core, and it has traditionally been hard to compete when well-capitalized Western firms moved in. If AI makes highly efficient marketing possible with far less money, the partner says, companies now hope they might out-execute those rivals in digital marketing.
Another partner calls being in the middle of such a large change genuinely exciting. They note that Korea excels in cars, shipbuilding, and more recently cosmetics and food, and that these large-scale, operations-heavy industries stand to gain a great deal from AI. The partner adds that Koreans have a conservative side but move fast and with passion once change arrives, and thinks the economy could do very well in the AI era.
On the global picture, one partner says the United States rightly leads in foundation models and core AI technology, but it is not yet clear whether it also leads in applying them. Applied AI, the impact achieved when AI meets real operations, is where the partner sees Korean companies as highly receptive and experimenting in diverse ways. The partner thinks there is a high likelihood that success stories of Korean companies redefining their competitive advantage will appear sooner and more powerfully than elsewhere.
No One Is Ahead Yet
One partner tells clients they understand the wish to look for global precedents but hopes clients will step outside that frame. In the partner's words, almost no one is truly ahead in the AI era, and no one can be, because the technology is brand new and everyone is figuring it out together. The partner encourages companies to aim to be the front-runner and the global case study, and believes they can.
The partners openly say no one knows what future this leads to, and that BCG itself has entered what they describe as unprecedented, chaotic territory. BCG does not hold a magic wand. It is going through the same process and trying to stay one step ahead. Their advice is to take the first step now, try things, and accumulate experience even when it is the experience of failure.
The Illusion of Being "Proactive"
The closing warning concerns self-deception. A company that grafts AI on in deploy mode and tells itself it is working hard and being proactive on AI may be under an illusion. One partner says some companies are already saying they have spent more than a year and plenty of money on AI and cannot tell what has changed. The partner urges companies to take AI as a given and focus on redesigning ways of working that have been kept for fifty or a hundred years, so they can deliver on the business fundamentals they were always trying to address.
That requires top leadership to commit to structural change over several years and to push through the difficulties along the way. The partners describe this kind of top-down drive as, in truth, the only way to ensure success.
On fears that AI will take everyone's jobs, one partner thinks that much anxiety is unnecessary and points to consulting as an example. Consulting is not disappearing, the partner says, but changing even faster in step with the times. The partners end on two points. First, since no one holds the answer, internalizing continuous learning is the most important virtue. Second, as they put it, using AI is not what matters; applying it well in the right places and getting results is the only measure.
AI is the talk of the town. Everyone says you have to go big on AI. The mood feels a lot like the past, but things are changing even faster now. Can a CAIO alone drive all of a company's AI transformation? Many now doubt it.
Almost no one is truly ahead in the AI era. No one can be. It's such a new technology. Whether you apply AI in the right places, well, and get results or not — that's the only measure.
We see ourselves evolving into an orchestrator that coordinates the entire process — that's our judgment. Across every single industry, the same thing is emerging — an unprecedented situation, I'd say.
When it comes to AI, Korean companies, with their early-adopter streak, are moving more actively and aggressively than most. 'I'm working really hard on AI, we're being very proactive' — that can be a kind of illusion. You need to guard against it.
One of the biggest changes: just two or three years ago — in late 2022 — the questions were 'what even is AI?' — about AI's very substance. And then 'why' — why should we bring AI into how we run the business? Those were the questions. So if 'what' and 'why' dominated back then, today almost no executives raise 'what' or 'why' anymore — the conversation is all about 'how.' Ultimately: how do we meaningfully apply AI to our business environment — to our company in particular? Questions from an applied-AI perspective have grown far more common. That's a defining shift.
Back when the iPhone came out, mobile was the great buzzword, and everyone said every company had to run a platform business. What we observed back then was that each company created a CDO — a Chief Digital Officer — an executive-level role, and drove the business around that person. The AI wave we've watched over the past two, three years looked similar. Companies appointed an AI executive and had them drive the change.
Same pattern so far — but recently things are shifting fast. Can a CAIO alone drive all of a company's AI transformation? Many now doubt it, and instead CEOs are saying: the most important agenda our company must set is AI. Therefore I will lead AI myself. That's the shift.
So the CEO personally owns AI, invests heavily, and drives it — compare that company with one where it's treated as mid-priority, and one where it isn't a priority: the business performance — the gap in results — is diverging dramatically. Companies that structurally embed AI across the whole organization and use it to strengthen productivity and sharpen profitability, versus those that can't — they will split into clear winners and losers, we believe.
Lately, the ways companies adopt and apply AI are becoming really diverse. In English we've taken to calling it 'AI-izing,' so to speak. And we expect this gap to widen further from here.
Some companies — since many use OpenAI or Claude — roll out AI services to every employee and try to drive some productivity improvement through that. Meanwhile, other companies use AI to ask: how do we reshape the fundamental competitiveness — the sources of competitive advantage — that we have? They approach it very top-down. So you have these two approaches — bottom-up and top-down, you could call them. And how you weave in the top-down approach to redefine the competitive edge your company holds — that has become the single most important, central question of this era, I think.
Many companies understand AI, but few approach it in a way that actually produces results. To put it quite bluntly, there are a few key points. The first: AI is merely a means. In 'AI transformation,' the emphasis too often lands on the AI when it should land on the transformation — companies get absorbed in adopting the technology itself.
For example, many consumer companies spend a great deal of time on new product development and planning — usually six months to a year. Now, if you handle that with a simple 'deploy' approach, you keep the existing way of working, chop it into tasks, and slot AI in here and there to move a bit faster, pick up speed — that's what you end up pursuing.
But what we call 'reshape' is quite different. The AI has to understand the logic of how we read the market and extract insight. That's what we at BCG call Enterprise IQ. In the end, it's the brain. The real value isn't building faster hands, or building more pairs of hands — it's whether those hands and feet are built together with a brain infused with the way our company wins in our own market. How well you build that Enterprise IQ is what actually decides success or failure.
And that part you must build in-house. It's nothing OpenAI can make for you, nor something Palantir can build — only the company that knows its own logic can build it.
So the very starting point is: what does it even mean to be good at new products? You start there. Not 'where can we use AI?' — but 'what does a successful new product actually rest on?' So if BCG were to reshape new product planning with AI, we would get AI's help reading the market and spotting opportunity areas for product planning, and rapidly generate not one but many candidate product concepts.
That compresses a process that took six months to a year down to about a month or two, and instead of riding one concept for six months or a year, you start with several and narrow down to the highest-probability products. So it's not taking the old way of making new products as-is and wedging AI into the middle — it's redesigning the entire sequence of product-planning work completely from scratch.
Frankly, only when you can use AI this way can you actually create genuinely meaningful results. But on this front, many companies still take the simple deploy, use-as-is approach, so they fail to reach meaningful results quickly — we see it often in the field.
Not long ago, BCG partners from around the world gathered to discuss how our consulting business should evolve going forward. Through that process, every consultant who took part — myself included — came away feeling: AI is pushing our business to evolve anew, and through it our opportunities are expanding further. That hope and expectation exist — but at the same time, so does the anxiety: will consulting be diminished by AI, or disappear altogether? Both feelings coexist — for us too, still.
Looking at BCG: we used to be a firm great at crafting strategy — setting strategic direction and advising on how to execute against it. Now we combine the technical elements needed downstream as well, to produce real impact, real deliverables — that's the firm we're evolving into. So if you ask what BCG is today, rather than calling ourselves a consulting firm, we say 'impact company' or 'impact core' internally. A partner that companies work with to create impact and outcomes — that's what we're becoming, we believe. And in one phrase: we're evolving into an orchestrator coordinating the entire process — that's our judgment.
Consulting's very business is solving client problems. How much the client achieves — impact, a better business, growing revenue, far greater cost efficiency, a real evolution in how people work — clear impact like that is our reason for being. Without it we cannot exist. Using AI everywhere isn't what matters — applying it well, in the right places, and getting results is the only measure. That's my message.
On that note, BCG's recent direction is being reorganized around two axes: strategy and applied AI. The AI BCG focuses on isn't AI as technology or AI as change — it's applied AI, genuinely applied to companies. How AI, once applied, drives change — around those two axes, BCG is being reorganized.
How to apply AI to companies — in our words, walking the reshape and reimagination journey together — that's our direction. So in talent: AI engineers, data scientists and other builders, and what people now call forward-deployed engineers — embedded on-site to deeply grasp and solve the client's problems — we're building that organization, one that holds its own against rising enterprise software firms: a broad, deep, first-rate FDE organization.
Seen that way, BCG's very DNA is wired to respond aggressively to a changing world. Pointing our own strategy so unmistakably at AI goes well beyond slogans — it's a very deep commitment, I think.
Honestly, I believe BCG's essence hasn't really changed. Creating results is, in the end, our mission. With AI now grafted on — with technology in the mix — how do you execute? And beyond that, changing how organizations work, changing processes — results only come when it all changes together, so it's right to say our service offering has expanded: strategy, execution fused with technology, and helping embed it all inside the company — change management and operating-model change too. It has expanded that far.
'AI transformation' — as I said, the emphasis lands too heavily on AI. It's a redesign premised on adopting new technology, so changes in ways of working, in processes, and if needed in the organization must come with it. Otherwise, however good the AI you plug in, results won't come. And that work — deep organizational understanding and constant, close engagement — is familiar ground for firms like ours: an area we can handle better than anyone.
AI — companies have done a lot, right? Some of it worked, some didn't. Goldman Sachs, a leading financial institution, is the case I should mention here. CEO David Solomon put it this way: before 2024, the way Goldman Sachs pursued company-wide AI transformation was running a hundred or so different POCs simultaneously, trying all sorts of things. Through that process, they failed to build proper success cases. 'We acknowledge our failure,' he said — and from 2024 they pivoted sharply to a philosophy of transforming the five or six most critical workflows that touch the very fundamentals, through AI.
More than the AI technology itself, or the data and infrastructure — this is the hardest part, people say. Harder still are the organizations and people who must lead it, and managing that change — that's truly hard. In numbers, of all the difficulty, I'd put the people part at 70%. In AI transformations, we advise on AI strategy and platforms, and design and build them — but beyond that, how you run with it in the field, how people actually change with it — that's where the BCG team focuses its consulting and delivers results.
These days companies tell me: we want people who ask good questions. In the AI era it's all prompting — ask well, instruct well, and you can solve all kinds of problems, right? I hear that a lot. But in fact, from its very start in 1993, BCG has wanted curious people who ask good questions. Asking well, defining problems well, solving them well, communicating them well — AI is getting good at that. So taking a well-solved problem and, with rapport and empathy, persuading — and then actually realizing it together, well — matters even more at BCG now.
People who convey, persuade, and captivate both reason and emotion — that talent matters more. And after that, executing for real, seeing results, creating value — that kind of person matters far, far more. People who take well-structured problem-solving, persuade others with it, and create real change in them — that's the talent we require and want much more of. That's how I'd put it.
It's artificial intelligence — which means intelligence itself is becoming universal. Reasoning, logical thinking, and access to knowledge are being handed to everyone. That world is coming. So nearly every role is being reshaped like this: people with only technical expertise will find less and less room. Those who can design, plan, and drive the whole will command ever more value, and BCG is no exception.
'Integrated builder-thinker' is my term for it — someone who can build, who can think, and along the way can wield tools including AI — that comprehensive talent is what's needed, inevitably. And client expectations will shift toward delivering outcomes far more sharply — that's where the bar is heading, I believe. Consultants who can deliver results end-to-end obviously provide far more value, and those who can will thrive, with bigger roles — that's what I believe, and this is the very core of the direction BCG pursues.
BCG recently published a report titled 'AI Will Reshape More Jobs.' What it means isn't that AI will eliminate jobs, that they will disappear — rather, that the thousands upon thousands of task combinations out there will be reshaped — newly transformed — by AI. Sketch out how the work you do today gets redefined and reorganized by AI, and against that picture, redesign how you work and how you lead your organization. Trying that is, amid this confusing, unprecedented situation, probably the most useful tip for breaking through effectively.
This actually has little to do with a company's size or revenue — it's not that large companies are far ahead while small and mid-sized ones lag. Not at all. If anything, because large companies run on massive systems, they often end up late movers in adopting AI and pursuing AI transformation — we see that a lot. Conversely, smaller companies often charge out in front far more — we observe plenty of those.
Especially on the topic of AI, Asian companies' interest and drive — and among them, Korean companies' drive — feels truly exceptional on the ground. Perhaps because the arrival of generative AI is seen as a chance to structurally flip a game whose rules were long written by the West — many seem to see it that way.
Take a consumer goods company: the core there is marketing. Traditionally, when Western firms with huge capital pushed in, it wasn't easy to compete. But if AI lets you run high-efficiency marketing with far less money, isn't that a game worth playing? Maybe we can out-execute them in digital marketing — that's the hope people now hold. Being in the middle of a change as enormous as AI is, to me, genuinely exciting.
Cars, shipbuilding — and lately cosmetics, even food — Korea excels across the board, and these are all large-scale, operations-heavy industries that stand to gain a great deal from AI, I think. And Koreans have a conservative side, but when change arrives, they move fast, with real fire and passion — so I think this economy can do very well in the AI era. America rightly leads in foundation models and core AI technology, but whether it also leads in applying them isn't clear yet, I'd say.
One of BCG's most important keywords is that phrase — strategy and applied AI. Applied AI, in the end, means technology that applies AI, or the impact you can achieve when AI meets the actual field — that's the point. In that sense, Asian companies — Korean companies especially — are highly receptive to this change and experimenting in remarkably diverse ways. So Korean companies redefining their sources of competitive advantage — such success stories emerging sooner, and more powerfully, than elsewhere? The odds are high.
When I meet clients, something I often say: I understand wanting to ask about global precedents, but I hope you'll step out of that frame. Almost no one is truly ahead in the AI era. No one can be. The technology is brand new, and everyone is figuring it out together. So set your mindset to: I will be the front-runner. I will be the frontier. I will become the global case study. Approach it that way — and I believe you can.
There's a lot of anxiety now, and no one can say what kind of future all this leads to. That's the era we're in. In a way, we've entered unprecedented, chaotic territory — we think so too. And BCG doesn't hold some magic wand that neatly resolves all of it. We're going through the same process, feeling it, and using it to work out how to stay one step ahead — and acting on it. That's the stage we're at too.
In this situation, what we suggest to people in companies: right now, you still have to take that first step. Try something — and even if what you gain is the experience of failure, accumulate it and push your way through the process. That's what's needed, we believe.
If you graft AI on in deploy mode and think 'I'm working really hard on AI, we're being proactive' — that's a kind of illusion. Guard against it. Because after some time passes, companies will start saying: we've spent over a year and plenty of money on AI, but looking closely, we can't tell what has changed. Those voices are already emerging,
So with AI technology as the given, how do we take the ways of working we've kept for fifty, a hundred years and redesign them again for the AI era — so that we deliver on the business fundamentals we were always trying to solve? Focus there — I hope companies see that clearly.
And top leadership must resolve: we will pursue structural change over years, and though there will be many hardships along the way, we will push through — driving change top-down like that is, in truth, the only way to guarantee success.
As for the fear that AI will take away all our jobs — I don't think you need that much anxiety. One of the clearest examples is the transformation of consulting I described earlier — the reshape. Our consulting isn't disappearing — it's changing even faster, in step with this era.
No one holds the answer. In this situation, internalizing a process of continuous learning is the most important virtue — the code of conduct, I believe.
In the past we were a firm that defined problems, solved them well, and persuaded. Now we're a firm that creates change. The essence hasn't really changed, I think. Creating results is, in the end, our mission.
Fundamentally: how does a company reach the point of creating impact? 'Impact company' or 'impact core' — that's what we call it internally. Consultants who can deliver results end-to-end provide far more value.
And using AI isn't what matters — applying it well, in the right places, and getting results is the only measure. That direction is the very core of what BCG pursues.
Article published