The next great GPT | Global Nonprofit Leaders Summit 2025

Summary

At the Global Nonprofit Leaders Summit 2025, hosted by Microsoft AI Skills, the focus was on the transformative power of AI as the next general-purpose technology. This event highlighted the unprecedented pace of change in 2025 and the significant role AI can play in aiding nonprofits. It stressed the importance of rapid technology adoption and the four critical factors for successful AI integration: technology, economics, skilling, and social acceptance. The summit underscored the urgent need to avoid replicating the past global divides seen with electricity's diffusion and aim for a more inclusive technological future, leveraging AI to solve global issues effectively and inclusively.

Highlights

• AI is identified as the next general-purpose technology, akin to electricity 🌍.
• The summit stresses the urgency of adopting AI across all sectors to harness its full potential 🏃‍♀️.
• Microsoft’s 50-year mission to empower everyone with technology continues with AI as the focal point 🔧.
• Four essential elements for AI success: technology, economics, skilling, and social acceptance 🔑.
• A call to action for rapid and inclusive AI deployment, unlike the slow diffusion of electricity 🚦.

Key Takeaways

• AI is set to be the new electricity, revolutionizing every aspect of our lives and economy ⚡️.
• Microsoft's mission is to empower every person and organization with technology 🌏.
• Success in AI requires mastering technology, economics, skilling, and social acceptance all at once 🎯.
• Learning from electricity's history, the goal is to bring AI to the world swiftly, avoiding past pitfalls 🚀.
• Partnerships between governments, nonprofits, and companies are essential for solving global problems together 🤝.

Overview

The Global Nonprofit Leaders Summit 2025, orchestrated by Microsoft AI Skills, centered around the remarkable potential of AI to function as the next general-purpose technology, similar to electricity. The summit addressed the rapid evolution seen in early 2025, emphasizing the crucial role AI can play in supporting nonprofit organizations worldwide.

Within the context of history and previous industrial revolutions, Microsoft detailed how technology like AI should be rapidly adopted to maximize its usefulness, warning against the replication of historical global inequalities seen during the spread of electricity. The importance of understanding AI's technological stack, alongside mastering economic and skilling needs, was a focal point.

In conclusion, the summit called upon leaders and innovators to ensure that AI doesn’t follow the slow growth path of electricity, but instead, be swiftly integrated worldwide in the next decade. This approach aims to prevent repeating historical mistakes and leverage AI's full potential to solve pressing global issues efficiently and equitably.

Chapters

• 00:00 - 00:30: Introduction and Thanks The chapter titled 'Introduction and Thanks' opens with applause, indicating the start of a speech or presentation. The speaker expresses gratitude towards Kate and Daria and reiterates their appreciation for being able to spend the morning with the audience. They emphasize the significance of the event and express gratitude towards both in-person and online participants for joining, highlighting the event's importance and the pleasure of being present with the attendees.
• 00:30 - 01:00: Context of Current Times for Nonprofits The chapter discusses the current tumultuous times, emphasizing how certain periods experience rapid changes. The speaker reflects on the significant changes witnessed in the first three months of 2025, indicating a time of accelerated transformation for nonprofits.
• 01:00 - 01:30: Technology's Role for Nonprofits The chapter "Technology's Role for Nonprofits" discusses the profound changes occurring in the nonprofit sector, particularly focusing on the challenges tied to funding sources. Amidst these challenges, technology emerges as a pivotal factor for nonprofits. The chapter's aim is to explore how technology fits into this changing landscape and what it can do to support and enhance the efforts of nonprofit organizations. The discussion is positioned within the broader context of a conference dedicated to the role of technology in this field.
• 01:30 - 02:00: Two Types of Technology This chapter titled 'Two Types of Technology' discusses the perspective on technology, particularly AI, and its implications for nonprofits. The narrative begins by placing the discussion within an economic context, highlighting that economists categorize technology into two distinct types: general-purpose technologies and single-purpose tools. It hints at a more comprehensive exploration of how these types of technologies are perceived and utilized, especially from Microsoft's viewpoint.
• 02:00 - 02:30: History of General Purpose Technologies The chapter discusses the concept of General Purpose Technologies (GPTs), which are technologies that have a broad impact on the entire economy. Examples include electricity, which is considered the archetype of GPTs as it transformed every aspect of the economy. In contrast, single-purpose tools like a light bulb or a drill serve specific functions.
• 02:30 - 03:30: The Importance of Technology Diffusion The chapter emphasizes the significance of General Purpose Technologies (GPTs) throughout history, particularly as catalysts for industrial revolutions. It highlights the first industrial revolution in England during the 1700s, primarily driven by advancements in iron working and the steam engine. It notes the second industrial revolution's prominence in the United States.
• 03:30 - 04:30: Microsoft's Role in Technology Diffusion The chapter discusses the pivotal role that Microsoft played in the diffusion of technology, particularly during the Third Industrial Revolution. It started with the advent of the computer chip, which, when paired with software, drove the digital era forward. This period is marked as a transformative time that built the modern manufacturing economy, reminiscent of how electricity and machine tools once spurred the manufacturing sector's growth.
• 04:30 - 05:00: AI as the Next General Purpose Technology The chapter focuses on the idea that while being at the forefront of technological innovation, such as AI, is important, historical trends show that the widespread adoption and integration of these technologies, known as diffusion, is even more crucial for economic growth and development. The emphasis is placed on how these technologies permeate through different sectors and become a part of everyday life, rather than just being groundbreaking inventions that remain at the top tier of technological advancements.
• 05:00 - 05:30: Critical Ingredients for AI Success The chapter 'Critical Ingredients for AI Success' highlights the importance of the widespread and rapid adoption of technology, referred to as diffusion by economists and adoption by the tech sector. It emphasizes that countries leveraging transformative technologies like electricity across all economic sectors tend to benefit the most.
• 05:30 - 06:00: Technology Stack in General Purpose Technologies The chapter discusses the significant correlation between the growth in electricity consumption and GDP per capita in the United States. It notes that as electricity consumption increased, so did GDP per capita. This pattern is consistent across various countries, illustrating the profound impact of electricity as a general purpose technology on economic growth.
• 06:00 - 07:30: AI's Technology Stack The chapter titled 'AI's Technology Stack' begins by drawing parallels between the industrial revolution and digitization, highlighting the third industrial revolution's impact. Microsoft, as a company, is deeply intertwined with this historical context. Founded on April 4th, 1975, Microsoft is on the verge of celebrating its 50th anniversary, marking its journey and contributions to the evolution of technology.
• 07:30 - 08:30: Economic Aspects of Technology Stacks This chapter explores the economic implications and impacts of technology stacks in the context of a company's evolution. It uses Microsoft as a case study to demonstrate how a company traditionally known as a software and technology company has transitioned into becoming a 'GPT diffusion' company. The historical perspective provided highlights the continuous nature of technological evolution and how it influences economic strategies within firms.
• 08:30 - 09:30: Evolving Financial Architecture Supporting AI This chapter delves into the evolution of financial structures that support AI technologies. It begins by highlighting the early technological ambitions set by influential figures like Bill Gates, Paul Allen, and Steve Balmer. The mission was to have 'a computer on every desk and in every home,' emphasizing universal accessibility and integration of technology in daily life. The repetition of the word 'every' underscores the goal for widespread technology diffusion, setting the foundation for understanding how financial architectures evolve to support such expansive technological ecosystems.
• 09:30 - 11:30: Importance of Business Models for Success This chapter discusses the evolution of the company's mission statement over 50 years. While the font has changed, the word 'every' remains central, reflecting the company's ongoing commitment to empowering every person and organization on the planet to achieve more. This reflects the company's goal to make technology accessible to all, anytime.
• 11:30 - 12:30: Skilling for Industrial Revolutions The chapter highlights Microsoft's integral role in the third industrial revolution. As the company approaches its 50th anniversary, there's an emphasis on looking towards the future, considering advancements in technology on a multi-year scale. This forward-thinking approach encourages imagining the potential developments in future industrial revolutions.
• 12:30 - 15:00: Skilling for AI The chapter 'Skilling for AI' discusses the future impact of Artificial Intelligence (AI) as a general-purpose technology in the second quarter of the 21st century. Despite uncertainties, AI is positioned as a transformative force akin to electricity, offering solutions to various global problems and influencing every sector of the economy.
• 15:00 - 16:00: Social Acceptance's Role in Technology Adoption The chapter delves into the role of social acceptance in the adoption of new technology. It raises the question of how society can ensure that emerging general purpose technologies serve the world positively. The discussion identifies four critical ingredients for successful technology adoption, suggesting that the process begins with an initial key concept that is essential for acceptance and success.
• 16:00 - 17:00: Trust and Security in AI This chapter delves into the concept of 'Trust and Security in AI' by using the historical example of general-purpose technologies (GPTs). It starts by explaining the technological stack - a combination of technologies that come together to make GPTs functional. Using electricity as a well-known GPT, it highlights how Thomas Edison accumulated these technologies to effectively light a bulb in 1878. By drawing parallels between past and present GPTs, the chapter emphasizes the importance of assembling the right technology components and creating a secure environment for AI advancements.
• 17:00 - 18:00: Environmental Sustainability in AI The chapter "Environmental Sustainability in AI" explores the historical progression from the invention of the light bulb to the establishment of power plants, specifically highlighting the transition marked by the New York Times building being the first to be lit up. It underscores the unforeseen development of a technological infrastructure on a large scale following Edison's initial invention in 1878. The chapter possibly draws parallels between this historical instance and the current trajectory of AI, emphasizing the unexpected requirements and structures that accompany technological advancements.
• 18:00 - 20:30: Bringing AI to the World The chapter discusses the requirements and infrastructure needed to bring AI and electricity to the world. It begins with the need for fuel to power generators in power plants, and the establishment of a grid to connect power to every building and home. It highlights the necessity for transformers, circuit breakers, wiring, switches, and appliances to make electricity practical and useful.
• 20:30 - 22:00: The Role of Companies and Nonprofits The chapter discusses the transformative impact of electricity on the economy, highlighting how it created a technology stack with various layers. Each layer of this tech stack spawned new businesses, jobs, and skill sets, ultimately leading to the emergence of a new economy. The text emphasizes the innovation that was sparked by this development.
• 22:00 - 23:00: Conclusion and Call for Collaboration The chapter discusses the transformative power of electricity, drawing a parallel to the early days when it first became widespread. The speaker invites the audience to envision a world where all modern appliances, commonly found in homes today, were invented just within the first two decades after electricity began to thrive in lower Manhattan. This historical perspective is used to highlight the pace of technological advancement and to inspire collaborative efforts for future innovations.

The next great GPT | Global Nonprofit Leaders Summit 2025 Transcription

• 00:00 - 00:30 [Applause] thank you Kate thank you Daria uh it's such a pleasure for me to spend some time with you this morning and I definitely want to second what both Daria and Kate said thank you for coming here for those of you in the room thank you for joining us online for those of you who are participating this way this is a really important event for us it is so great to be here with all of you um
• 00:30 - 01:00 because right now when you wake up in the morning let's be honest it's a pretty tumultuous time you know I just think that when you look at history there are some years that witness relatively little change and yet there are some months where you see years worth of change in what feels like a few weeks and I think in many ways the first three months of 2025 have brought
• 01:00 - 01:30 enormous change and not all of it is easy for nonprofits especially when you look at sources of funding and so we realize what an important time this is what I want to do this morning is talk about where technology fits in because after all as you can imagine this is really a conference about what technology can do for nonprofits and so where I think I fit into the time that we have together is to share some
• 01:30 - 02:00 perspective about technology and especially AI what does it mean for nonprofits but even more than that how are we thinking about it at Microsoft and let me start by putting it in the context of what economists think about as economists think about technology there's really two types of technology a generalpurpose technology and a singlepurpose tool most technologies in the world are in fact
• 02:00 - 02:30 singlepurpose tools a light bulb a smoke detector a drill they do one thing really really well but a generalpurpose technology what economists call a G GPT is a technology that basically impacts the entire economy electricity is really the archetype and when you think about it every aspect of our economy runs on electricity it changed everything and
• 02:30 - 03:00 interestingly what historians have learned is that GPTs have really been the driving force of all of the industrial revolutions the first industrial revolution started in England in the 1700s and it was really driven by iron working and the steam engine but iron working more than anything else the second industrial revolution really took off more in the United States than
• 03:00 - 03:30 anywhere else and it was a combination of electricity and machine tools machine tools really built the modern manufacturing economy and the third industrial revolution is really the story of our lives it started with the computer chip and when it was combined with software it fueled a digital era now interestingly when people think
• 03:30 - 04:00 about these industrial revolutions and I find especially when you meet with people in government they always think first and foremost about what it means to be at the frontier of the leading edge the leading sector like a GPU when you're thinking about AI those things matter but what history teaches us is that what matters even more is not being the inventor of the leading edge is what economists call diffusion it's actually
• 04:00 - 04:30 the use of technology as quickly and as broadly as possible or what economists call diffusion we in the tech sector call adoption and this makes great sense when you think about it because after all take electricity if it can change every part of the economy then the countries that benefit most are those that use it in every part
• 04:30 - 05:00 of the economy and you see this in the data for example this is the growth in electricity consumption on a per capita basis in the United States as electricity consumption grew GDP per capita grew as well i have slides like this for basically every country on the planet and they're all the same the correlation is extraordinary and what was true for electricity in the second
• 05:00 - 05:30 industrial revolution also became true for digitization in the third industrial revolution and this is something that we at Microsoft understand not only because we're interested in history and we read but in a sense this is actually our story as a company microsoft was founded on April 4th 1975 if you look at the calendar you realize that we'll have our 50th
• 05:30 - 06:00 birthday a week from Friday but what's interesting when I look at the history of Microsoft and as somebody who's been here for almost 32 years in many ways we are a software company and always have been a technology company and have always been but we're really a GPT diffusion company a generalpurpose
• 06:00 - 06:30 technology diffusion engine the company's very first mission was defined by a young Bill Gates and Paul Allen and Steve Balmer it was about a computer on every desk and in every home running Microsoft software now what I find most interesting about this first mission statement is there is one word in it that's used twice the word every and we
• 06:30 - 07:00 fast forward almost 50 years to today and the font in our mission statement has changed but that same word is still used twice now we are about empowering every person and every organization on the planet to achieve more every is something that defines what we have always tried to do as a company to bring technology to everyone and in many ways
• 07:00 - 07:30 Microsoft is one of the companies that has served of as the heart of if you will of this third industrial revolution we'll celebrate our 50th birthday next Friday it'll be fun but really it's always here about the future usually a year at a time maybe five years at a time but I do think we're at a moment when we can look forward more broadly and start to imagine
• 07:30 - 08:00 collectively what might the second quarter of the 21st century bring well one thing we believe is clear even in a world with so much uncertainty AI really is the next generalpurpose technology you think about the problem on planet earth AI will serve a role in helping to solve it it will impact every part of the economy i do think it really is the electricity
• 08:00 - 08:30 of our era so the real question is how do we as a company really how do we as a community think about what it will take to ensure that this new general purpose technology in fact serves the world well well interestingly the more we've thought about it the more we've concluded there's actually four critical ingredients for success and I want to talk about each of them briefly not surprisingly it starts with the
• 08:30 - 09:00 technology itself it turns out that every GPT every general purpose technology is built with a technology stack a stack of technologies that need to come together and you can see this from a from electricity really the GPT that's most familiar to most people in the world it was 1878 when Thomas Edison first was able to use electricity to light a light
• 09:00 - 09:30 bulb and then it was four years later in Manhattan that for the first time there was a power plant that illuminated the lights in buildings the very first building to light up was the New York Times building i think that no one uh probably imagined in 1878 when Edison lit that first light bulb that they were going to need to build an entire tech stack but that's
• 09:30 - 10:00 what was required it started with the fuel to power the generators in the power plants and then they needed to be connected with a grid that would reach every building and home that was using electricity there needed to be transformers and circuit breakers built into the grid there needed to be wiring and switches and circuit breakers there needed to be appliances that actually made electricity useful and then there
• 10:00 - 10:30 were the new opportunities for manufacturers for users in effect this became the tech stack for electricity and it created a new economy because every layer of this tech stack had new businesses new jobs new skills that all needed to come together but what I think is most interesting about this is the innovation that was unleashed especially
• 10:30 - 11:00 at what I would call the appliance layer if you go to your home when you leave this or if you're watching online you may be watching from home if you look around your kitchen if you look around your flat or apartment or house almost everything you see will have been invented in the first 20 years after electricity took off in lower Manhattan imagine what it must have felt like if
• 11:00 - 11:30 it was a hot summer day and for the very first time you walked into a room that had an electric fan or imagine what life meant when you actually had a washing machine or in some ways my favorite imagine for the very first time walking into a kitchen that had a blender i mean what is this thing it's loud you know and then you would realize how much easier it made it to prepare dinner all
• 11:30 - 12:00 of these things probably felt like magic and in a sense they were magical in terms of the impact they had on societies that could benefit from them well it's no longer 1878 or 1882 now it's 2025 and interestingly AI is also being built on a tech stack the tech stack fundamentally has three
• 12:00 - 12:30 layers the infrastructure layer with the land and power and ships and data centers the platform layer and the counterpart to that appliance layer the applications layer and one of the things really the heart of what we're doing at Microsoft from a technology perspective is focusing on investing and innovating in all three layers it starts with the infrastructure layer which to me is just
• 12:30 - 13:00 extraordinary i love visiting data centers at some level they all look the same and at some level they're all different i'm amazed by just the extraordinary amount of wiring and liquid cooling and the chips and basically the electrical engineers and electricians and the mechanical engineers and the pipe fitters these really are in many ways the power plants of our time the critical digital
• 13:00 - 13:30 infrastructure on which AI relies and we're building it around the world we're spending $80 billion this year alone to build out this infrastructure we're building it in more countries than any other company because you have to have the infrastructure so that AI can be put to work but you can't stop there it's then the platform layer that makes it possible to build applications that will
• 13:30 - 14:00 put this infrastructure to work so there's foundation models like a GPT4 or a GPT40 coming from a company like OpenAI our critical partner but we're in fact seeing many of these foundation models some based on large investments in training some being more focused some being open-source but all of those are coming together they're all trained with
• 14:00 - 14:30 large amounts of data but what really is the key at the platform layer is in addition a third layer the platform level services so what we're doing at Microsoft is thinking and working and investing and innovating in putting these three pieces together there's all of the platform software components that we are building out because these are the digital tools or tool chain as software developers now refer to it that
• 14:30 - 15:00 make it possible for people then to build applications on top that are infused with the power of AI and so when you really look at what we're doing and I think where we so closely connect with all of you is the ability to support nonprofits around the world and startups around the world and large companies and governments around the world it's really all of the people who will unleash
• 15:00 - 15:30 innovation at the applications layer to put the power of AI to work to solve the world's problems now all of this is like a giant flywheel because in truth it all has to get moving you build the infrastructure so that you can train a model and deploy it around the world you provide those models so that applications can be built on top but you need the applications to
• 15:30 - 16:00 take off to become popular to be used to generate the revenue to keep investing in the infrastructure and like a giant flywheel oh there are days when it all seems to work seamlessly and in symmetry and most other days when there seems like there's more progress at one layer than another and you're constantly focused if you're at a place like Microsoft in identifying each area what
• 16:00 - 16:30 are the opportunities what are the challenges what are the problems that need to be solved a hundred years from now people will look back and say "Oh it must have been easy." Well if you're in the heart of it of course you appreciate that it's always hard but that's the technology layer now if the only thing we did as a technology company was master the technology we would do a quarter of what is needed in order to build this new era of AI so it's really combining the
• 16:30 - 17:00 technology with these other things starting with economics interestingly every tech stack actually has an economic structure and that's one of the really important things to always think about and understand because this is true of electricity it's true of AI it's been true of every general purpose technology if you look at electricity for example what you see is that the
• 17:00 - 17:30 power plants are enormously expensive the power grid is enormously expensive but the appliances in contrast are not they were cheaper to invent and obviously much cheaper to manufacture or buy now what is interesting is that fundamental economic structure of the second industrial revolution is in fact being repeated because AI infrastructure is very
• 17:30 - 18:00 expensive and this is very different from say the third industrial revolution when somebody like Michael Dell could really make enormous progress in taking the costs out of call it the hardware layer and help make personal computers within a few years cost a half or only a third of what they cost before and then the software applications were built on top but this era requires massive capital at the
• 18:00 - 18:30 bottom and the infrastructure even when the opportunities at the top remain much less expensive now that economic structure actually translates into a financial architecture because you can't build this tech stack without having a real vision and a strategy for the financial architecture that's needed and you see Microsoft not only doing this in our own investments it helps explain why
• 18:30 - 19:00 you see headlines like the big capital funds coming together for example the one that Black Rockck and Microsoft and MGX and then more recently Nvidia and XAI are all helping to raise to generate even more capital to help you know bring innovation to the entire supply chain of what is needed and to help invest in all of this that needs to be built around the world in fact interestingly enough I
• 19:00 - 19:30 think we're seeing this financial architecture evolve before our eyes as well it starts with the big investments by private companies it then has this private capital it has investments by sovereign wealth funds and I do believe that we are likely to need other public funding as well to fill in the gaps especially on a continent like Africa where those gaps are real and you reach the limits of
• 19:30 - 20:00 what makes sense for private capital the private market to invest in and then the last piece of this economic aspect is really the business model it turns out that you always need stable oftentimes innovative business models that's what sustainable success is built upon and when you think about digital technology it always comes down to one of three
• 20:00 - 20:30 business models the first is a subscription it's like subscribing to a magazine you pay once and you can read one story a week you can read every story in every issue if that's what you want that is in fact M365 that we offer you know somebody can buy a subscription and they can use every feature very few people do they can use only one application but that is the way a subscription works then there's
• 20:30 - 21:00 consumption that's the way the cloud services work including Azure people pay for the amount they use and in effect they pay as they go and then there's advertising and advertising has really emerged as you all know as really being at the heart of many consumerbased digital services people may get up and look at Instagram in the morning and they'll never pay for it but obviously advertising is what is paying
• 21:00 - 21:30 for that service to exist to me the most interesting thing is just to recognize business models will evolve we don't yet know what they're going to look like a decade from now and I think the most interesting story if you look at the history of generalpurpose technologies is how they evolved for electricity electricity grew first in the United States as I mentioned and interestingly enough the person who was the leader of the basically the company that Thomas
• 21:30 - 22:00 Edison had founded was visiting the UK visiting England where he was born and had grown up and at the time in Chicago where he lived you could still walk down a street this was in the 1890s electricity had been around for 15 years at that point and you would see some stores and some homes that were clearly lit and others that were still running on kerosene
• 22:00 - 22:30 people were still slow to adopt it but this gentleman spent a weekend in Brighton on the beach on the south coast of England and when he arrived he walked down the street and every store was lit by electricity and he wondered what's going on here what have these people figured out that we have not figured out in Chicago or the United States so he found the manager of the local power plant and what he did was he showed him an
• 22:30 - 23:00 invention it was called a power meter it was what was put in every store so that people were not paying on a subscription basis as they were in Chicago but paying on a consumption basis instead it turned out for the first 15 years of electricity in the United States when you bought a light bulb you bought a subscription so that you could turn it on it turned out that once the business
• 23:00 - 23:30 model evolved to consumption it became far easier for people to go buy more light bulbs and just pay the bill at the end of the month i love that story because I think the real lesson is not just about business models it's about humility every industrial revolution is led by people who frankly not only are really smart but they think they're really smart and the real lesson is that nobody
• 23:30 - 24:00 knows everything we all are going to learn together as we go through this and that is in part how we'll master the economics that will be needed for success now the third key ingredient you might look at and sometimes people do and say well I'm surprised that this rate rises to the same level skilling why is that as important as economics
• 24:00 - 24:30 and technology well it turns out that skilling is the fundamental force that drives the adoption and growth of each of these industrial revolutions it makes sense because if a new technology is going to be used across the economy the skills to put it to work need to be mastered across the economy so why did ironwork take off in England it wasn't just because George
• 24:30 - 25:00 Watt had invented the steam engine there it was because England at the time had a system of technical institutes and apprenticeships that taught people in the evening how to master iron working and so iron working spread more quickly the US benefited from this amazing coincidence when it came to electricity and machine tooling because in 1862 during the Civil War in the United States Abraham Lincoln had championed
• 25:00 - 25:30 and then signed into law what became known as land grant colleges the federal government granted federal land to the states to create land grant colleges i'm sure some of you have degrees from them and it was all started to really advance an understanding of agricultural science and agricultural engineering but it led to this new discipline in the United States called mechanical engineering and so because the United States had
• 25:30 - 26:00 mechanical engineers they were able to figure out how to put machine tools to work to change manufacturing across the economy and then when the industry standardized they were able to go even faster and the same thing was true in the third industrial revolution interestingly employers invested in training of employees in the 1980s and computer science departments absolutely swept the the nation in the United
• 26:00 - 26:30 States all the major colleges and universities created these computer science departments so the US had more people who could code on a per capita basis than any other country and people have learned over time that this need for skilling is not just deep it is broad one of the best illustrations of this was what the electricity industry realized in the 1950s they had built out power plants
• 26:30 - 27:00 but electricity was not being used as widely as the industry hoped so the industry got together and said you know what we need to do we need to help the American public actually just learn what a new generation of appliances can do in their fir in their homes we need to bring this into people's homes using the power of television we have to find somebody who can connect with the public and help them learn about this in an
• 27:00 - 27:30 interesting and even enjoyable way so they found this fellow who was working in Las Vegas at the time he was an actor he wasn't wellknown at the time but he had this natural ability not only to communicate but to connect his name was Ronald Reagan and so Ronald Reagan with his wife Nancy started to come to everyone's home every
• 27:30 - 28:00 Sunday evening when GE would host basically a theater a play that evening but before it began Ronald and Nancy would show off the latest appliance in their home they ended up with so many appliances in their home that they needed to put in place an additional electrical generator just to power all of it but it worked and it probably was indispensable in the rest of his career
• 28:00 - 28:30 including becoming president of the United States it shows how skilling needs to connect with people i think one of our great opportunities and challenges as a company as a community as an industry really as a planet is to think about AI skilling at scale and make it one of the great opportunities and causes together for the next decade and two to come and it really starts by
• 28:30 - 29:00 understanding thinking about what are the skills that people need to learn and we should recognize these are early days we don't yet know exactly what we're going to need but we do think there are at least three categories there's fluency just learning how to use AI learning how to use a co-pilot or chat GBT or in other everyday software applications that is what we are doing that's what we are doing in partnership with many of you it is a little bit like
• 29:00 - 29:30 what Ronald Reagan did we just haven't hired Ronald Reagan yet the next is AI engineering i think this is the future of computer science the real question is what will a computer science degree look like a decade from now will it be an AI science degree what will people need to learn in order to really create AI applications there's a good chance it will involve less code because AI is
• 29:30 - 30:00 getting very adept at coding but an enormous amount of design and probably I think more multiple disciplines because people need to really master all of the impacts of AI and how to make them more useful and then there's what we think about as AI systems design if you're an organizational leader how do you understand your workflows what we would think of as your business processes which ones are most likely to benefit from the application of AI how do you
• 30:00 - 30:30 measure the success how do you take people through cultural change and in effect every country is going to need to develop its own national AI talent strategy assessing their economy looking at the different sectors where are their real needs for skilling and what type where is there the ability to partner often with nonprofits and definitely through the education sector to build AI
• 30:30 - 31:00 fluency for everyone and build out all of the other skills that are needed all of these things will need to come together to master skilling and then you have the final piece it's what historians and political and social scientists call social acceptance it turns out that broad technology adoption requires social acceptance it sort of makes sense when you think about
• 31:00 - 31:30 it but in the 1980s social scientists went to work sociologists in particular and they asked a very important question why did some technologies take off and get used broadly when others did not and it turned out that their studies showed it always came down to two factors first something needed to be useful unless it was useful people wouldn't use it that seems obvious but the other is that it had to be trusted and I think it's this element of
• 31:30 - 32:00 trust that is also at the heart of what we need to advance when it comes to AI and that's what we're doing and as we think about trust we see these four elements it's there's security there's privacy there's digital safety i'd say especially the protection of children and others and there's this discipline called responsible AI that has emerged in the industry and has really spread around the world including through often
• 32:00 - 32:30 times new laws and regulations and just as there's a tech stack for the technology itself there's sort of a stack that we're building for AI governance there's an architecture i think it starts with the internal policies at tech companies we have now corporate standards in these places for these topics we train engineers we have engineering tools we have compliance systems and the same is true for
• 32:30 - 33:00 customers whether they're nonprofits or companies companies or governments but I think on top of that we're seeing emerge industry standards the standards are critical because they define best practices and as best practices emerge there's the foundation for say the domestic policy ultimately the international policies that are needed this too needs to come together in order for AI to spread around the world and
• 33:00 - 33:30 because this is 2025 and not 1882 we have to add an element to this aspect for social acceptance called environmental sustainability because it does turn out as everyone knows that those big data centers that you saw the pictures of run on a large amount of electricity which is why we're so focused and why we remain so committed to achieving in 2030
• 33:30 - 34:00 the goals we set for ourselves in 2020 to be carbon negative by the end of this decade and what that means is reducing our emissions from electricity and from the use of greener steel and greener concrete and greener fuels and the like and then engaging in carbon removal it is what has made Microsoft the largest corporate investor on the planet of the removal of carbon from the environment
• 34:00 - 34:30 so that's how we achieve we believe social acceptance what I think is most interesting about this is to be truly successful you actually have to do not one of those four things you have to do all four of them at the same time and I do think that what perhaps differentiates us from say other tech companies more than anything else it's the fact that we are working so hard to master all four of these things together
• 34:30 - 35:00 and you're going to see new initiatives new innovations and new investments in the coming months in the next year in all four of these areas i would then conclude by just offering a thought about what the history of technology teaches us i'd first start with the cautionary tale it goes back to electricity i actually believe that the
• 35:00 - 35:30 diffusion of electricity was both remarkable and at the same time represents the single greatest technology tragedy in history what is the tragedy it's the fact that today we come together 143 years after that power plant started operating in Manhattan and there are still 700 million people on planet Earth that tonight won't be able to use electricity
• 35:30 - 36:00 to light a light bulb because they don't have access to it it's 43% of the people who live in Africa i think that the number one cause of the great global divide between the global north and the global south the economic divide that has afflicted so many now generations of people's lives has fundamentally been based on whether they lived in a place that had access to
• 36:00 - 36:30 electricity we need to do better let's face it if it takes 150 years to bring AI to the world then we will have failed our goal I think needs to bring AI to the world not in 150 years but in 15 that is the opportunity that we have to think a new and act differently and then what it asks us to do is think
• 36:30 - 37:00 about how we work together because you're at Microsoft I would start with the purpose of a company sati Nadella our CEO likes to quote a professor named Colin Mayer who said "The purpose of a company is to find profitable solutions to the world's problems." I fundamentally believe that every healthy society is built on a healthy three-legged stool there are
• 37:00 - 37:30 governments that obtain money by taxing it and they spend money to solve the world's problems they create the fundamental social infrastructure needed for a civilized society and then you have nonprofits that raise money to solve the world's problems and then you have companies that sell products and services to earn a profit to solve the
• 37:30 - 38:00 world's problems and what is most interesting in the world today in my view is that while people often spend their time talking about how we're different what we don't talk about is how we do our best work not just as separate organizations but in communities and countries when we all compleiment each other because that is what we
• 38:00 - 38:30 do so in some we know our role well it is to pursue profitable solutions to the world's problems mostly by building out that infrastructure layer building out the platform layer so you can go to work as can we with applications that will make the world a better place in essence our role is to serve you at Microsoft we
• 38:30 - 39:00 serve the world's nonprofits so you can serve the world and when we do that together even in a hard day a hard month or a hard year we make the world a better place thank you very much [Applause]