- 6 hours ago
Speaking at the India Today Conclave 2026, the founder of OpenExO and founding executive director of Singularity University said rapid advances in AI are changing how companies operate and compete.
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00:00The speaker here has spent years studying how the world's most powerful companies are built.
00:09He is a Hyderabadi who has spent a lot of time in Bandra in Mumbai as well.
00:18Someone who has spent seven years in Silicon Valley, worked at Yahoo and sold a company to Google.
00:27And among other developments in his life in recent years, he also did a workshop in Vatican.
00:36But today he is here as the founding executive director of the Singularity University and the mind behind the idea
00:44of exponential organizations.
00:46Salim Ismail, thank you for joining us here on India Today.
00:50Let's begin with the big opportunity.
00:52You have said, and I'm quoting you here, the world's biggest problems are the world's biggest opportunities.
01:00So what is the world's biggest problem right now?
01:03Well, we have any number of big problems.
01:06First of all, wonderful to be here.
01:08I always love coming back to India.
01:12When you look at our grand challenges or the UN development goals, you have huge opportunities in health care, education,
01:22clean water, energy, etc.
01:24And what technology is allowing us to do is address those problems directly, and therefore those huge problem spaces also
01:32become the world's biggest markets.
01:34If you can solve education, that's an 8 billion person market.
01:39So it's education, health, climate change?
01:42Clean water, energy, poverty, hunger, all sorts of areas are enormously difficult.
01:50So which of these would be the next trillion dollar company, or all of these?
01:56You'll see some in all of them, but the two I would expect the most to see in would be
02:00health care and education,
02:02because those are very legacy industries that are stuck.
02:06For example, the model of a university has not changed in 450 years.
02:11It really needs an upgrade, and the way technology is accelerating, the entire secondary, post-secondary market and education is
02:20going to basically implode.
02:22You have spoken about immune system in legacy organizations.
02:27Yeah.
02:28Are legacy organizations rejecting immune systems?
02:35And are these systems within the legacy organizations?
02:40They're within.
02:40What happens is if you try anything disruptive in a legacy environment, the antibodies attack you.
02:45Why?
02:46Because all of our organizations are designed to resist change and withstand risk, right?
02:52If you ask anybody that's the head of innovation at a big company, just turn them around, you'll see arrows
02:57in their back from all of the rejection efforts they've had from the antibodies in the company.
03:02This is why big companies have an enormous time innovating.
03:06This is why Facebook buys WhatsApp.
03:08This is why the car industry does not come up with Tesla.
03:11This is why Microsoft puts money into open AI rather than building itself.
03:16A small, nimble team will always outperform a big legacy organization.
03:21And as technology is accelerating, especially with what's possible with AI today, that goes 100x.
03:27So all disruptive innovation comes from individuals or small teams.
03:33And so when you try anything disruptive in a big company, you're stuck fighting the legacy.
03:37And that's bad in big companies, but it's worse in public sector where the existing policy is the immune system.
03:43So the phone call I got from the Vatican was they called up and said, look, the Pope is trying
03:47to change the church and his immune system is 2,000 years old.
03:50So can we have you come and have a conversation?
03:52So I did a half-day workshop with the Vatican, which was rather interesting.
03:56So tell us about this.
03:58A 2,000-year-old immune system.
04:00How do you tackle that?
04:01So, you know, this is one of the oldest organizations in the world, and it does not like change.
04:06Yes.
04:07Yet you have the world moving quickly and moving past it.
04:11So I brought up problems like we have CRISPR where we can edit our own human genome.
04:15Well, what does that mean from a moral and ethical framework?
04:18We have life extension coming where we're going to be expending, we'll be doubling human lifespan in the next 10
04:25to 15 years.
04:27Their business model is about selling heaven.
04:29How are you going to sell heaven if people are not dying, right?
04:32That's a big challenge in their particular case.
04:34And so you have these structural issues where they're not able to really think about that or deal with it.
04:40And most people don't see these big structural challenges.
04:43So can I just take a quick diatribe on this?
04:46Please go ahead.
04:46So there are two things happening in technology today that are completely unique that we have never seen before in
04:52human history.
04:53The first is we've seen computation accelerate via Moore's law now for 60 years, okay?
04:59We have a dozen technologies now operating on that same platform, on that same foundational doubling pattern.
05:06So drones are doubling every nine months in their price performance.
05:09AI today is doubling about every 10 weeks.
05:12That's the fastest moving technology we've ever seen.
05:14Now each of these is doubling.
05:16Where they intersect, you add a whole other multiplier to the equation, right?
05:19So one thing that's happening that's completely unique is the fact that we have this many technologies all accelerating at
05:25the same time.
05:26But the second thing I think is even more important, especially important from an India context, which is the cost.
05:33So throughout human history, it's always been true that advanced technologies cost a lot.
05:38And only a government or a big corporate lab could do R&D, launch new products and services.
05:43Today, for the first time in human history, advanced technologies are cheap.
05:47Solar energy is cheap.
05:48Sensors are cheap.
05:50Blockchains are open source and free.
05:52So you now have what I call PDI, permissionless disruptive innovation, in a very profound way.
05:58Okay?
05:58I'll give you a specific example.
06:01There's a car called the Vega.
06:04It's a 900-horsepower car, right?
06:08A third fastest car ever created, designed, built, engineered in Sri Lanka, that hotbed of automotive innovation, right?
06:16I love showing that example to German car executives.
06:19Their brains absolutely melt.
06:21Because how is it possible on an island of fishermen and farmers you can come up with something like that
06:27with no ecosystem, no investors, no education, no experience?
06:31And so this is what we're going to see an explosion of.
06:34And when you can do disruptive innovation at low cost, I think that fits perfectly into the Indian Jugar capability,
06:41the psyche here, where if something can be done, we'll do it.
06:45And so I think we're going to see incredible things happen as a result of that.
06:48So it will not be about capital.
06:50It will be about coding then?
06:51Or disruption will be about a group of individuals coming together and ensuring that their brains and their functionality meets?
06:59Yes, a single person using AI to write software is outperforming institutional capital today.
07:07Institutional capital?
07:08Oh, yeah.
07:09There's no way you can invest in anything like that.
07:11Look at something called Open Claw when you get a chance, which is completely disruptive, created by a hobbyist,
07:18and it's completely taking over the AI world right now.
07:21So then it is about speed, which matters more than size of a company.
07:29A thousand times.
07:30So in the past, all big companies are architected for two things, efficiency and predictability.
07:37Right?
07:38If you're a Pampers, you're trying to deliver the same diaper in a million locations.
07:42But today you need to be architected for agility, flexibility, adaptability, speed,
07:48because the customer forecasts that you thought you could make six months ago don't exist anymore today.
07:53So you need to be able to move with the market very, very quickly.
07:56Most big companies are not able to do this.
07:59So in 1937, an economist called Ronald Coase wrote a paper and he theorized that the reason big companies exist
08:10is transaction costs inside a big company are cheaper than outside a big company.
08:15And therefore, they'll just keep getting bigger and bigger until the equilibrium is met.
08:20He won the Nobel Prize for this paper that he wrote.
08:23In the recent book that we wrote, we declare Coase's Law dead because if you try and get a website
08:29built inside your company,
08:31it's a thousand times more expensive than hiring a developer outside your company today.
08:35And today you can do it with AI in eight minutes at zero cost.
08:40So the transaction costs inside any company today are actually more expensive than the outside world.
08:48This is an existential threat.
08:50To big companies.
08:51To all companies.
08:52To all companies.
08:53But especially big companies.
08:55So there is, I'm writing a paper right now that I'm titling the organizational singularity
09:01because all our organizations, every single organization in the world,
09:05pretty much dissolves now in the face of what's coming.
09:08Because today we do all of our workflows from a human to human perspective.
09:13If a trucking delivery arrives, I have a human being signing off on it.
09:18I may digitize that, but it's still human detected.
09:22Then we take it into the warehouse as another sign-off.
09:24Then it makes it onto the production floor, another sign-off.
09:27And we go human to human in all of our workflows.
09:30We're re-architecting our workflows to now go AI to AI.
09:34And we don't need the human in the middle.
09:36Too inefficient.
09:37And human beings are error-prone.
09:39And they have politics.
09:40And they get sick.
09:41And they take vacations.
09:43And they unionize.
09:44All of that stuff.
09:45So what's going to happen is we're going to automate all of our workflows,
09:49especially in the knowledge work side, with AI,
09:52with the human being doing oversight, dashboard monitoring, and exception handling.
09:58So I predict what will happen is you'll run a typical company
10:01with about one quarter of the employees that you do today.
10:06But if everybody freaks out of a job loss,
10:08we'll end up creating four times more companies.
10:10So the next trillion-dollar company will have perhaps 40 to 50 employees or less?
10:17Probably five.
10:18Just five?
10:19Yeah.
10:20There are already billion-dollar companies being created with three people today.
10:26If you go back a hundred years ago,
10:28it took about 100,000 people to create a billion-dollar company.
10:31Then you got it down to about 10,000 people.
10:34Google did it with about 1,000 people.
10:36OpenAI did it with a couple of hundred people.
10:38Now we're down to about five.
10:41You have a presentation for us.
10:43I mean, I've talked through a bunch of this, but I can just very quickly.
10:47So we can play some of those slides.
10:48Very quickly, there's a picture of the book that I wrote.
10:52I do a podcast every week or so with some interesting guests that we've had recently
10:57where we talk about what's the latest breakthroughs in technology.
11:02This graph, I think, really shows it.
11:04Ray Kurzweil put this graph together showing Moore's Law.
11:07And he goes all the way back to 1900 and finds we've been doubling computational price performance
11:12for more than 100 years.
11:13And the question he asked was, why is that curve so smooth and so predictable?
11:19We've had wars and recessions and ups and downs in the industry.
11:22You should expect a very jagged stock market-type shape.
11:25Yet you see this unbelievably predictable progression, and it absolutely makes no sense.
11:29He spent 10 years researching this and came up with a very fundamental observation,
11:35which is once you take a domain, discipline, industry area, product area, technology,
11:40you power it with information technologies, the price performance starts doubling.
11:44Most importantly, once that doubling pattern starts, it does not stop.
11:48It just keeps going.
11:50And we have a very difficult time cognitively with that.
11:53You can't have infinite growth.
11:55It has to level off.
11:56And the secret is in the different bands that you see there,
11:59those are different technologies like electromechanical, vacuum tubes, transistors.
12:04In computation, we've seen about five different technologies.
12:07Each one is like an S-curve, where technology takes off, accelerates,
12:11reaches its upper limits, but if you have an information-based paradigm,
12:16we then design the next generation, and you keep going.
12:20So we're reaching the end of integrated circuits today.
12:23The chips are getting very hot down at the surface levels.
12:25We're down to, what, two nanometers wire thickness.
12:28But now we have a cluster of technologies on the edge,
12:31like 3D chip design, the matrix architecture,
12:34that NVIDIA is using quantum computing as one candidate,
12:38which requires a lot of alcohol to discuss, so I won't get into it here.
12:41Before you move on, a word on, when you say end of technology,
12:45but haven't we reached a stage right now that AI is no longer a tool,
12:50it is becoming the organization itself?
12:52Yes.
12:53So what's happening is we've been using AI as a tool now,
12:56up till now, but now AIs are organizing by themselves to do things.
13:01And we're at a point of what's called recursive self-improvement,
13:04where the AIs are improving themselves to do the work.
13:08So you don't need humans in the middle anymore.
13:11What about imagination here?
13:14Imagination's still in the realm of human beings for now,
13:17but the AIs are getting really good at that.
13:19Okay, let's move on.
13:21So the next slide.
13:22Oh, next slide, okay.
13:22So this is the board of XPRIZE.
13:26We have some rather interesting people there.
13:29These are some of the technologies that are all doubling in their price performance.
13:32So, for example, in neuroscience,
13:33the speed at which we can image the human brain or the resolution is doubling every year.
13:38Drones are doubling every nine months in their price performance, etc., etc.
13:42And as I said, we've never seen this money happen at the same time.
13:45And we wrote a book and teased out this model,
13:48saying if you want to organize for this new world,
13:51this is the model you have to follow.
13:52And so hundreds and thousands of companies are using this model.
13:57You have five externalities on the right that allow you to scale very quickly
14:01and five internal mechanisms on the left that allow you to manage the control framework
14:05and drive culture.
14:06At the top, we have what's called a massive transformative purpose.
14:10What problem are you fundamentally solving?
14:13So that was the thesis of the book over the last 10, 12 years.
14:17But that thesis just broke.
14:19You have said that the most dangerous company is a startup that you have never heard of.
14:26Yes.
14:27Why do you say that?
14:28Because of that democratization of innovation happening all over the world,
14:34people are now doing very breakthrough things in their garages,
14:38at home, in their office, etc., etc.
14:40And you don't hear about it until it's too late.
14:44So this is a very difficult time trying to navigate this.
14:47I referenced earlier this new capability called Open Claw.
14:53It's a hobbyist Austrian developer who did this over a weekend, launched it,
14:58and now it's changing the entire AI world
15:00because he brought together a bunch of different capabilities into one structure
15:04and everybody's building on it.
15:07Then should the industry not be worried about these disruptions?
15:12If a dangerous product is coming up in a garage,
15:16then shouldn't we be worried about these disruptions?
15:18Yes.
15:20You have to take on today the Bill Gates paranoia of healthy disruption
15:24or healthy paranoia where you assume you will be disrupted
15:27because you can't see it coming.
15:30Let me give a little example of that.
15:32So over the last 20 years,
15:34if you owned a car wash in Buenos Aires in Argentina,
15:37it turns out your revenues have dropped 50%.
15:39I have a global community of about 45,000 people all over the world
15:44following the book, etc.
15:45And one of my community members in Buenos Aires says,
15:48this makes no sense.
15:49The middle class has exploded.
15:51We bought a ton more Mercedes and BMWs.
15:54Argentinians are very proud people.
15:55They like to keep their cars clean.
15:57Why is there a 50% drop?
15:59It should double or triple.
16:00Is there hyper competition?
16:02Are there water restrictions?
16:03Are there legal issues?
16:04What's going on?
16:05So he looks into it,
16:06and over a couple of months is able to get rid of all of the obvious factors,
16:09and then he finds the answer,
16:10which turns out literally to be Moore's Law.
16:14Because of the increased computation ability over the last 20 years,
16:18we've become much better at modeling the weather.
16:21And over that 20-year period,
16:23we're exactly 50% better at knowing when it's going to rain.
16:27And when you know it's going to rain,
16:28you don't wash your car.
16:30Now, you can be the smartest car wash owner in the world,
16:34and you will not see that coming.
16:36Right?
16:36It doesn't matter how smart you are.
16:38And 50% drop is a pretty big number.
16:40You might consider closing up shop.
16:42That's the type of disruptive innovation that is going to hit us
16:46in industry after industry now.
16:48You can see what happened with Claude Code two weeks ago.
16:51We lost hundreds of billions off the software industry
16:55just from the release of a few plug-ins.
16:59Right?
16:59So this is going to start to accelerate in a very radical way.
17:02A kind of a comet has hit,
17:05which is how you design for organizations around AI.
17:09The dinosaurs, which are basically all medium and large-sized companies,
17:13are now under threat.
17:14You'll see a Cambrian explosion of little furry mammals
17:17running around starting in the next little while.
17:20Among all the innovations that you have seen in recent years,
17:24what, according to you, is the most dangerous or the smartest?
17:28Well, AI is now by far the most disruptive technology we've ever seen.
17:34Why?
17:34Because it improves itself.
17:36And also, we're doing some surreal things right now with AI.
17:40For example, in the next year or so,
17:42we will solve all mathematics with AI.
17:46And I mean all.
17:47Okay?
17:48It's already starting to happen.
17:49If you solve mathematics, it means you can solve physics.
17:52If you solve physics, it means you can solve material science.
17:55So the amount of breakthroughs happening is kind of incredible.
17:59I'll give you an example.
18:01There are what are called dark labs right now.
18:03So imagine a lab of millions of test tubes and different compounds
18:07and robots testing different combinations of these compounds.
18:12Okay?
18:12Normally, in the past, you had human beings running around
18:14testing different levels, et cetera.
18:16Now you have robots doing it.
18:18The robot is being run by AIs
18:20that are themselves coming up with the hypotheses.
18:23So this is a dark lab.
18:25It runs 24-7 with no human beings involved.
18:28And they're finding breakthrough innovation
18:30at the most unbelievable pace.
18:32And it's completely automated.
18:34So we're going to start to see a lot more of that happen.
18:37And all of the breakthroughs will start happening
18:39via these types of things.
18:40But humans would be needed for problem solving.
18:45Less people, but yes.
18:47Again, I'm not a job apocalypse person.
18:51I think we're going to be fine.
18:52You know, in the 1970s, we created bank ATM machines, right?
18:56And there was all sorts of hand-wringing.
18:58Oh, my God.
18:58Millions of bank tellers will be wandering the streets aimlessly.
19:01What will we do with all these people?
19:03Society will collapse, et cetera.
19:05It's much like you hear right now.
19:07What actually happened was the cost of running a bank branch
19:09dropped by about 10 times.
19:11The banks created 10 times more branches.
19:13The number of bank tellers has not changed at all.
19:15So what we found is whenever we have major automation and technology,
19:19we increase capacity.
19:21We don't lose jobs.
19:23So this is what we expect to see at the same time.
19:25However, it means you have to be unbelievably agile, innovative,
19:30be willing to...
19:31Today, you're either the disruptor or you're disrupted.
19:34There's no middle ground, right?
19:35And doing nothing means you're disrupted.
19:37So it's a really interesting model to think about where we go next.
19:41So for any legacy organization or large corporation,
19:44what are the three big ideas, according to you,
19:48that will protect the immune system?
19:51Well, the immune system, you have to beat the immune systems.
19:54We've actually solved that problem.
19:56We crafted a 10-week engagement that we piloted with Procter & Gamble
20:01and said, let's see if we can hack culture at scale.
20:03We've done it now 100 times with big companies around the world.
20:06So you have to do something like that to solve that immune system response
20:11so it doesn't attack new ideas.
20:13Then what you need to do is, on the edge of your organization,
20:17create an AI-native digital twin that's completely AI-based
20:21and little by little move workflows over to it.
20:24Do not try and fix your existing organization.
20:27It cannot be done, okay?
20:29I've seen about 400 major corporations around the world attempting innovation
20:34in all sorts of different ways.
20:36I've only ever seen one model work,
20:38which is you take your crazy people in your company to the edge
20:41and you build at the edge into adjacent areas.
20:45A great example would be Nespresso.
20:47Nestle ran Nespresso as a line of business for three or four years,
20:51failed miserably.
20:52They finally put it on the edge of the organization
20:54and boom, every hotel room in the world has an Nespresso machine.
20:57So that's the model that we'll start to see emerge now.
21:01We're starting to see it already.
21:02You see Facebook buying Instagram and WhatsApp
21:05and leaving it on the edge,
21:06not trying to bring it into the mothership.
21:08You try and bring it into the mothership, you will kill it.
21:11More such examples, please.
21:14Oh, this is why Google built Google X.
21:17Yes.
21:18Larry Page came to me a few years ago and said,
21:20hey, your unit at Yahoo is very successful.
21:22Should I do that at Google?
21:24I said, no, you'll have this immune system response,
21:26but do something like it.
21:28Keep it stealth.
21:29Keep it at the edge of the organization.
21:31And so they have their information capabilities at the heart,
21:34but they do disruptive things at the edge,
21:37Google car, Google glass, contact lenses, et cetera.
21:40The master of this technique for a long time has been Apple.
21:44What they do is they will form a small team that's very disruptive.
21:47They will put the team at the edge of the organization.
21:50They will keep them secret and stealth,
21:52and they will say to that team, go disrupt another industry,
21:55whether it's watches or payments or retail or whatever.
21:58At last count, they had about 18 teams looking at different industries.
22:02Now, even Apple has completely messed it up with AI.
22:05They've not had a reasonable response to AI for the last several years.
22:09Anybody trying to use Siri today, you'll see exactly what I mean, right?
22:13A complete mess.
22:14They will get very lucky because it turns out the Mac mini hardware is perfect
22:18for running these localized AI models, so they'll get very lucky there.
22:22But in general, they're operating on a very clunky model.
22:26But that's the only path that we see forward.
22:28It then becomes doubly important when you think about, you know,
22:31I talk about immune systems and companies, but public sector is even worse,
22:36where the existing policy is the immune system.
22:38So we do a lot of work with governments, helping them get through that thinking
22:41because there you have to solve that problem,
22:44and how do you do this type of disruptive innovation
22:47in legacy organization and public sector?
22:49So what was the advice that you gave to the Vatican?
22:52That's 2,000-year-old immune system.
22:56Well, we actually did a workshop there, and it was actually quite successful.
23:00They were much more aware of some of these ideas than I thought they would be.
23:05And the outcome was actually very powerful, except they were a little freaked out.
23:09They told me that maybe not since Copernicus has that much disagreement
23:14with the Church been presented inside the Vatican, which is quite something.
23:18I said, wow, you people need to get out more.
23:22But even those legacy organizations are starting to learn how to think about this.
23:26All right, we have really come to the end of this discussion.
23:29But before I let you go, a word on what do you think will be the next innovation order,
23:35and who will be building it?
23:38Who will be building it?
23:39I just told you we have no idea who's going to be building it,
23:42but I will give you a couple of thoughts.
23:44I think we're going to use AI to make some unbelievable breakthroughs in all sorts of various...
23:50For example, I have my degrees in theoretical physics.
23:52There's been a problem in theoretical physics called a grand unification theory for the last 100 years.
23:59People have been trying to solve it.
24:00I predict we will solve the grand unification theory in the next few months.
24:05That will be solved, finally.
24:06It will be solved.
24:08All right.
24:09Which is kind of a big deal.
24:10And who will solve it?
24:11We do not know.
24:12It's going to be some graduate Indian student.
24:15Maybe sitting somewhere here.
24:16Maybe sitting somewhere here.
24:17All right.
24:18Salim Ismail, thank you so much.
24:19You're very welcome.
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