Keynote-Julie Sweet

19 Feb 2026 13:45h - 14:00h

Keynote-Julie Sweet

Session at a glance

Summary

This discussion features Julie Sweet, Chair and CEO of Accenture, addressing an AI summit convened by Prime Minister Modi, focusing on how to harness AI’s potential for global benefit. Sweet draws from Accenture’s experience as one of the world’s largest AI and technology transformation companies, with over 350,000 employees in India and extensive AI operations globally. She presents three key perspectives for ensuring AI benefits everyone: using AI as an engine for growth, embracing unprecedented reinvention, and maintaining human leadership over AI implementation.

Sweet illustrates her growth argument by referencing the 2013 Oxford study that predicted 47% of U.S. jobs would be automated, yet the IT services industry thrived by embracing new technologies like robotic process automation. She notes that Accenture grew from 275,000 employees and $29 billion revenue in 2013 to over 750,000 employees and $70 billion today. According to her latest C-suite survey across 20 countries, 78% of companies are using AI, with 80% viewing AI’s greatest value as driving growth. Sweet emphasizes that AI should “make the impossible possible,” citing examples like large language models transforming retail commerce and AI accelerating pharmaceutical drug development from the current nine-year average.

She stresses the importance of ensuring small and medium-sized enterprises have access to AI technology and talent, noting they represent 50% of global GDP and 70% of employment in the global south. Sweet argues that successful AI adoption requires companies to reinvent their operations and workforce strategies, countries to transform their educational systems and partnerships with private sector, and individuals to embrace lifelong learning. She concludes by advocating for “humans in the lead, not humans in the loop,” emphasizing that technology remains a tool whose impact depends on human leadership and decision-making.

Keypoints

Major Discussion Points:

– AI as an Engine for Global Growth and Prosperity: Julie Sweet argues that embracing AI for growth and productivity is the only path to global prosperity, drawing parallels to how the IT services industry thrived despite automation fears in the past decade, with Accenture growing from 275,000 to 750,000 employees.

– The Need for Unprecedented Reinvention: Companies, countries, and individuals must fundamentally reinvent how they work, operate, and learn. This includes reshaping workforces, changing processes, embedding AI in education systems, and creating global standards for AI deployment across industries.

– Ensuring AI Access for Small and Medium Enterprises: Since SMEs represent 50% of global GDP and 70% of employment in the global south, providing them access to AI technology and talent through public-private partnerships is crucial for inclusive growth.

– “Humans in the Lead, Not Humans in the Loop”: Sweet emphasizes that while AI is powerful, it remains a tool, and human leaders must decide how to use it responsibly, commit to reinvention, and ensure people are brought along the transformation journey.

– AI Should Make the Impossible Possible: The technology should enable new products, services, and performance levels previously unattainable, such as LLMs becoming “the new mall” in retail or accelerating drug development in pharmaceuticals.

Overall Purpose:

The discussion aims to present a strategic vision for AI adoption at scale, moving beyond hype to provide practical insights on how organizations, governments, and individuals can harness AI’s potential for inclusive growth while addressing associated challenges and risks.

Overall Tone:

The tone is consistently optimistic and forward-looking throughout, with Sweet maintaining confidence in AI’s potential while acknowledging the magnitude of required changes. She balances enthusiasm with pragmatism, using concrete examples and data to support her arguments. The tone emphasizes collaboration, responsibility, and the need for urgent action, ending on an inspirational note about collective capability to create a better future.

Speakers

– Moderator: Role/Title: Not specified, Area of expertise: Not specified

– Julie Sweet: Role/Title: Chair and CEO of Accenture, Area of expertise: AI and technology transformation, leading one of the world’s largest AI and technology transformation companies with hundreds of thousands of professionals across every sector of the global economy

Additional speakers:

– Mr. Ankur Vora: Role/Title: Not specified, Area of expertise: Leveraging AI for social impact (mentioned by moderator as previous speaker)

– Prime Minister Modi: Role/Title: Prime Minister, Area of expertise: Not specified (acknowledged by Julie Sweet as convener of the AI summit)

– Minister Vaishnav: Role/Title: Minister, Area of expertise: Not specified (acknowledged by Julie Sweet as convener of the AI summit)

Full session report

This keynote presentation features Julie Sweet, Chair and CEO of Accenture, delivering a strategic address on harnessing artificial intelligence’s transformative potential for global benefit. Speaking from her position as leader of one of the world’s largest AI and technology transformation companies, with over 350,000 employees in India and one of the largest AI workforces globally, Sweet offers a grounded perspective on AI adoption at scale that moves beyond theoretical discussions to operational reality. She opens by thanking “all of our people in India for your incredible commitment to value and to our clients.”

Sweet structures her presentation around three fundamental perspectives essential for ensuring AI benefits all of humanity: “Using AI as an engine for growth is the only path for global prosperity for all,” “The agenda ahead of us is unprecedented. Companies, countries, and individuals must reinvent how they work, how they work together, and how they learn,” and “It is humans in the lead, not humans in the loop, that will determine our future.” Her arguments are consistently optimistic yet pragmatic, drawing from concrete data and real-world experience to support her vision of an AI-enabled future characterised by expansion rather than contraction of opportunities.

AI as the Engine for Global Growth and Prosperity

Sweet’s first major argument centres on using AI as a driver of growth and productivity as the only viable path to global prosperity. To illustrate this principle, she draws a compelling parallel to the technological transformation of the previous decade, specifically referencing the 2013 Oxford University study that predicted 47% of US jobs would become automatable. Despite widespread fears about technologies like robotic process automation (RPA) devastating the IT services industry, the opposite occurred. Companies that embraced these new technologies, including digital and classical AI, not only survived but thrived by creating investment capacity for further innovation and growth.

Sweet provides concrete evidence through Accenture’s own transformation journey. In 2013, the company had roughly 275,000 people and $29 billion in revenue; today, it has grown to over 750,000 and growing and $70 billion in revenue. This dramatic expansion exemplifies how embracing technological change creates opportunities for unprecedented growth. She reinforces this with current data from Accenture’s latest quarterly survey across 20 countries, revealing that 78% of companies are actively using AI, with 80% identifying AI’s greatest value as driving growth rather than merely reducing costs.

Central to Sweet’s growth philosophy is her assertion that “AI should make the impossible possible.” She establishes this as a concrete benchmark for successful AI implementation, arguing that if CEOs cannot point to new products, services, and performance levels that were previously unattainable, they have failed to capture AI’s true potential. This reframes AI adoption from incremental improvement to transformational change.

Sweet illustrates this transformative potential through specific industry examples. In consumer and retail sectors, she predicts that large language models (LLMs) will become “the new mall,” representing an entirely new paradigm for customer engagement that simply did not exist in 2022. In pharmaceuticals, she envisions AI accelerating drug development significantly beyond the current nine-year average, enabling life-saving treatments to reach patients faster whilst simultaneously accelerating pharmaceutical companies’ revenue cycles.

Addressing the SME Challenge for Inclusive Growth

A critical component of Sweet’s growth-focused approach involves ensuring that small and medium-sized enterprises (SMEs) have adequate access to AI technology and talent. She emphasises the economic imperative behind this inclusion, noting that SMEs represent 50% of global GDP and, crucially, 70% of employment in the global south. Without inclusive access to AI capabilities, these enterprises risk being left behind in the technological transformation.

Sweet acknowledges that whilst market forces will create some business opportunities for serving SMEs, market mechanisms alone will be insufficient to ensure equitable access. She advocates for robust private-public partnerships as essential vehicles for bridging this gap. As a concrete example, she describes Accenture’s collaboration with the US college system, where the company funds internships for college students at SMEs, creating valuable work experience for students whilst providing SMEs access to cutting-edge talent and AI capabilities.

The Imperative for Unprecedented Reinvention

Sweet’s second major perspective addresses the unprecedented scale of reinvention required across companies, countries, and individuals. She acknowledges that “advanced AI is much more powerful than the technology advancements of the last decade,” necessitating more profound changes, though the fundamental lesson about using technology for growth and productivity remains constant. What changes dramatically are the required actions, timeframes, need for global collaboration, and urgency of implementation.

At the corporate level, Sweet emphasises that companies must demonstrate willingness to fundamentally reinvent operations and processes that may have remained unchanged for decades. She identifies a critical insight: “Underneath the headlines of a failure of AI is mostly a failure to reinvent.” Companies must invest substantially in reshaping their workforces through strategic transformation of roles and capabilities rather than mere redundancies.

Particularly significant is Sweet’s emphasis on creating sustained entry-level employment opportunities, which she argues “makes economic sense” as the only pathway to developing future leaders whilst bringing genuinely AI-native talent into organisations. However, AI fundamentally alters the nature of entry-level positions, requiring intentional redesign of roles and comprehensive investment in training programmes. Sweet demonstrates this commitment through Accenture’s practice of hiring more entry-level employees this year than last, though the required skills and onboarding processes have changed fundamentally.

At the national level, Sweet calls for countries to reinvent their approaches to private sector collaboration. Governments must become exemplars of AI adoption, demonstrating through their own operations why AI matters. They must work with private sector partners to establish lifelong learning systems, recognising that education can no longer be viewed as a destination but must become a continuous journey. Sweet commends India’s approach of embedding AI into educational systems starting at the primary school level.

Sweet argues for establishing global standards that extend beyond safety considerations to encompass industry-specific applications. Using pharmaceutical development as an example, she notes that if some countries allow pharmaceutical companies to leverage advanced AI for drug discovery whilst others do not, the resulting fragmentation prevents scaling and ultimately impacts vulnerable populations who need access to new treatments.

At the individual level, Sweet emphasises that people must recognise formal education as no longer sufficient for career-long success, requiring embrace of lifelong learning and continuous skill development.

Human Leadership in an AI-Enabled Future

Sweet’s third perspective centres on her assertion that “it is humans in the lead, not humans in the loop, that will determine our future.” This distinction represents a fundamental reframing of human-AI relationships, moving from a defensive posture focused on oversight to a proactive stance emphasising leadership and strategic direction.

She argues that whilst responsible AI deployment requires human oversight and compliance programmes, this should not obscure the critical lesson that technology, regardless of its power, remains fundamentally a tool. The transformative impact comes from how leaders choose to deploy it. Leaders make crucial decisions about committing to reinvention, dedicating resources to ensuring people are brought along the transformation journey, and choosing to collaborate for safe and widespread AI adoption.

Sweet contrasts the prevalent narrative of diminishment—predictions of fewer jobs and reduced opportunities—with Accenture’s vision of expansion and growth, grounded in their practical experience of technological transformation and commitment to creating more opportunities rather than fewer.

Drawing from Accenture’s leadership principles, Sweet highlights the importance of leading with “excellence, confidence, and humility.” Leaders must maintain confidence in their collective ability to create a better future whilst holding themselves to high standards because people worldwide depend on that excellence. Simultaneously, they must embrace humility to recognise that no individual or organisation can navigate this transformation alone—collaboration and partnership are essential.

Conclusion

Sweet’s presentation provides a comprehensive framework for AI adoption that balances optimism with pragmatism, individual responsibility with collective action, and technological capability with human agency. Her approach addresses both tremendous opportunities and significant challenges in AI transformation, providing concrete examples and actionable insights rather than abstract theorising.

The moderator’s closing observation that “AI should make the impossible possible” effectively captures Sweet’s central message of transformational rather than incremental AI adoption. Sweet’s vision presents AI not as a threat to be managed but as an unprecedented opportunity to be seized through thoughtful leadership, comprehensive reinvention, and inclusive collaboration, providing a roadmap for navigating AI transformation whilst ensuring its benefits are broadly shared.

Session transcript

Moderator

Thank you, Mr. Ankur Vora. Your perspectives on leveraging AI for social impact have undoubtedly added depth to the summit. And ladies and gentlemen, our next speaker is Ms. Julie Sweet, Chair and CEO, Accenture. Ms. Julie Sweet has repositioned Accenture as one of the world’s largest AI and technology transformation companies, deploying hundreds of thousands of professionals across every sector of the global economy. Her perspective on what AI adoption actually looks like at scale beyond the hype is grounded in hard operational reality. So please welcome the CEO of Accenture, Ms. Julie Sweet.

Julie Sweet

Thank you, Prime Minister Modi, Minister Vaishnav, and your outstanding teams for convening us for this critical summit around AI. The breadth of distinguished guests from around the world is a recognition of the importance of broad global partnerships to capture the incredible potential of AI and address the risks. It is also a recognition of the importance of India in our AI -enabled future. At Accenture, we’re incredibly proud to have over 350 ,000 and growing reinventors here in India. We also have one of the largest AI workforces in the world, tightly integrated with our growing AI hubs in the US, Europe, the Middle East, and Japan. And I want to take this time to thank all of our people in India for your incredible commitment to value.

And to our clients. Today, I want to leave you with three perspectives that we believe will help us ensure that AI’s immense potential. is captured for the benefit of all. First, using AI as an engine for growth is the only path for global prosperity for all. Second, the agenda ahead of us is unprecedented. Companies, countries, and individuals must reinvent how they work, how they work together, and how they learn. And finally, it is humans in the lead, not humans in the loop, that will determine our future. As we turn to the imperative for growth, I want to take you back for a moment to 2013. Oxford University had just published a widely read study that said based on technology progress at that time, 47 % of U.S. jobs would be automatable.

dire headlines and predictions soon followed one of those technologies was robotic process automation or rpa and there were predictions that it services would be badly damaged because it would automate so many jobs and in fact we used rpa to automate thousands of jobs and we also as an industry embraced the new technologies of digital and classical ai and we created many many more jobs we helped our clients adopt rpa and those who did created investment capacity to invest in new technologies and to grow and in fact the it services industry has thrived over the last decade including many of india’s most successful companies that you’ve heard from today At Accenture alone in 2013, we were roughly 275 ,000 people and $29 billion in revenue, and today we’re over 750 ,000 and growing and $70 billion in revenue.

What the last decade has taught us is a critical lesson. When companies and countries embrace new technologies and then use them to drive growth and productivity, they prosper. Advanced AI should be the same. In fact, in our latest quarterly survey of C -suites across 20 countries, they agree. 78 % of all companies are using C -suites. 80 % say AI’s greatest value is in growth. Now, as we think about what growth should look like, there’s two important considerations. First. AI should make the impossible possible. AI should make the impossible possible. If in a few years as a CEO, you cannot point to new products and services, new levels of performance that were not possible before, then you have not captured potential of AI.

Think about the consumer and retail industries. LLMs are about to become the new mall. This is an entirely new way to engage customers and to engage in commerce that did not exist in 2022. If you think about pharma, we see a path toward bringing drugs to market much faster than the average of nine years. Not possible before, which means that life -saving drugs will get to people faster and pharma will have accelerated sales. Growth. Growth. And we are just beginning to understand how AI will create new drugs, new materials, new products across industries. A second consideration around growth is that we must commit to providing access to the technology and the talent for small and medium -sized enterprises.

If we are to use AI as an engine for growth, we need to make sure that the engine for growth, these types, these size enterprises, have access. 50 % of the world’s GDP are small and medium -sized enterprises. And in the global south, it’s 70 % of employment. To do so, there will be lots of business opportunities. So many industries will serve small and medium -sized enterprises. But that will not be enough. Private and public partnerships will be critical to making sure there’s access. For example, we’re working with the U.S. college system where we’re funding internships of college students at small and medium -sized enterprises. It’s a win -win. Statistically, if you have an internship, you have a better chance of getting a job.

And it’s providing these enterprises access to some of the cutting -edge talent. And so we must make sure that we’re continuing to focus on the small and medium -sized enterprises. Now, I know, and we all know, that advanced AI is much more powerful than the technology advancements of the last decade. And, of course, that means that the impact is more profound. But that doesn’t change the critical lesson that AI must be used for growth and productivity. What it does change are the sets of actions, the time frame, the need for global collaboration, the need for more public and private partnerships, and the urgency of what we must do in order for AI to drive growth.

So companies, companies must be willing to reinvent how they operate, their processes, how they’ve been doing work for the last decades. Underneath the headlines of a failure of AI is mostly a failure to reinvent. Companies have to invest to reshape their workforces. And companies must commit to creating. Creating sustained entry -level jobs. Now, entry -level jobs makes economic sense. They’re the only way to create future leaders. And they bring needed, truly AI -native talent to each of our organizations. But AI fundamentally is changing what an entry -level job looks like. And so a commitment means we have to be intentional about changing the roles, investing in training, which is exactly what Accenture is doing. We will hire into more entry -level jobs this year than last year.

But the skills we require and the way we’re onboarding those individuals is fundamentally different. Now, countries must also reinvent. They must reinvent their role and how they work with the private sector. They have to themselves as governments become the best credential for why AI matters. They must work with the private sector to help create lifelong learning because education is no longer a destination. We have to have lifelong learning. India is doing a great job of embedding AI into the educational system, starting in primary school, and governments across the world will need to do so. At the same time, as countries are thinking differently, individuals have to think differently and recognize that formal education is no longer the destination.

But perhaps the biggest fundamental change that must be made is that companies and countries need to pound the table for global standards. These standards should apply to safety, but also to the industries where AI can make the greatest impact. For example, in pharma, if one country is allowing pharma companies to use the latest technologies to discover drugs, they should be able to make the greatest impact. If one country is allowing pharma companies to use drugs and then test drugs, but other countries don’t follow suit, it means that you won’t be able to scale, you won’t be able to bring it. And we know that most often that impacts the most vulnerable. now we have a view of course that we have to reinvent but as we think about that reinvention or to our future is the fundamental belief that it is humans in the lead not humans in the loop that will shape that future we should not confuse how you deploy ai responsibly of course all of our compliance programs have humans they have technology that doesn’t change the critical lesson that we’ve learned over and over again technology no matter how powerful is only a tool it is simply a tool it is leaders who decide how to use those tools It is leaders who decide to commit to reinvent, who dedicate their time to making sure that people come along the journey.

And it is leaders who must choose to work together to ensure the safe, widespread adoption of AI. There are lots of headlines today that predict less. Less jobs, less opportunity, less human relevance. We are here because we see a future of more. At Accenture, we live by eight leadership essentials, the qualities we believe we need to run our company. And one of them is particularly important. We expect leaders to lead with excellence, confidence, and humility. As we look to our collective future, we should have the confidence to have the unwavering belief that together we can make a future that is better for all. We also must hold ourselves individually and collectively accountable for executing on that belief with a high bar of excellence because our people around the world are counting on that excellence.

And finally, we must all have the humility to know that we cannot do this alone. Thank you very much.

Moderator

Thank you so much, Ms. Julie Sweet. I think I can take a tagline out of her address, which says that AI should make the impossible possible.

Julie Sweet

Speech speed

122 words per minute

Speech length

Leadership, Governance, and Global Standards

Topics

Artificial intelligence | The enabling environment for digital development

Moderator

Speech speed

137 words per minute

Speech length

122 words

Speech time

53 seconds

Tagline Summarizing AI Promise

Explanation

The moderator highlights a concise tagline that captures the aspirational promise of AI: making the impossible possible.

Evidence

“I think I can take a tagline out of her address, which says that AI should make the impossible possible.” [12]

Major discussion point

Tagline Summarizing AI Promise

Topics

Artificial intelligence

Agreements

Agreement points

AI’s transformative potential to enable previously impossible achievements

Speakers

– Julie Sweet
– Moderator

Arguments

AI should make the impossible possible by enabling new products, services, and performance levels that were previously unattainable

AI should make the impossible possible, representing the key promise and capability of artificial intelligence

Summary

Both speakers agree that AI’s fundamental value lies in its ability to make previously impossible things possible, representing a core transformative promise across industries and applications

Topics

Artificial intelligence | Information and communication technologies for development

Similar viewpoints

Both speakers emphasize that AI’s core value proposition is enabling breakthrough capabilities and achievements that were not possible before, with the Moderator directly endorsing and summarizing Julie Sweet’s central message

Speakers

– Julie Sweet
– Moderator

Arguments

AI should make the impossible possible by enabling new products, services, and performance levels that were previously unattainable

AI should make the impossible possible, representing the key promise and capability of artificial intelligence

Topics

Artificial intelligence | Information and communication technologies for development

Unexpected consensus

No unexpected consensus identified

Speakers

Arguments

Explanation

The discussion features only one main speaker (Julie Sweet) with the Moderator providing supportive commentary, so there are no unexpected areas of consensus between different perspectives or opposing viewpoints

Topics

Overall assessment

Summary

The discussion shows complete alignment between the main speaker and moderator on AI’s transformative potential, with the moderator explicitly endorsing Julie Sweet’s central message about AI making the impossible possible

Consensus level

Very high consensus level, though limited by having only one substantive speaker. The implications suggest strong agreement on AI’s fundamental promise for breakthrough innovation and transformation across industries, which could facilitate unified approaches to AI adoption and implementation strategies

Differences

Different viewpoints

Unexpected differences

Overall assessment

Summary

No disagreements identified as this transcript contains a single-speaker presentation by Julie Sweet with supportive moderator remarks

Disagreement level

No disagreement present – this is a keynote presentation format where the moderator introduces and concludes the speaker’s remarks, with the moderator’s single argument actually reinforcing Julie Sweet’s central message that ‘AI should make the impossible possible’

Partial agreements

Similar viewpoints

Both speakers emphasize that AI’s core value proposition is enabling breakthrough capabilities and achievements that were not possible before, with the Moderator directly endorsing and summarizing Julie Sweet’s central message

Speakers

– Julie Sweet
– Moderator

Arguments

AI should make the impossible possible by enabling new products, services, and performance levels that were previously unattainable

AI should make the impossible possible, representing the key promise and capability of artificial intelligence

Topics

Artificial intelligence | Information and communication technologies for development

Takeaways

Key takeaways

AI must be used as an engine for growth and productivity to achieve global prosperity, as demonstrated by the IT services industry’s success over the past decade

AI should make the impossible possible by enabling new products, services, and performance levels across industries like retail (LLMs as new malls) and pharmaceuticals (faster drug development)

Comprehensive reinvention is required at three levels: companies must reinvent operations and workforce strategies, countries must reinvent their role and embed AI in education, and individuals must embrace lifelong learning

Human leadership is critical – it’s humans in the lead, not humans in the loop, that will determine AI’s future impact

Inclusive access to AI technology and talent for small and medium-sized enterprises is essential, requiring private-public partnerships

Global standards for AI safety and industry applications are necessary for scaling benefits worldwide

Leaders must approach AI adoption with excellence, confidence, and humility while ensuring people are brought along the transformation journey

Resolutions and action items

Companies must commit to creating sustained entry-level jobs and invest in reshaping their workforces with new skills and training approaches

Countries must work with private sector to create lifelong learning systems and embed AI into educational systems starting from primary school

Private and public partnerships must be established to ensure SME access to AI technology and talent

Companies and countries need to advocate for global standards that apply to both safety and industry-specific AI applications

Organizations should focus on using AI to drive growth rather than just automation, creating investment capacity for new technologies

Unresolved issues

Specific mechanisms for implementing global AI standards across different countries and regulatory frameworks

Detailed strategies for ensuring equitable AI access in the global south where SMEs represent 70% of employment

Concrete measures to address the skills gap and workforce transition challenges during AI adoption

Specific timelines and benchmarks for the comprehensive reinvention required at company, country, and individual levels

Methods for balancing AI safety requirements with the need for rapid innovation and growth

Suggested compromises

Impact

This concluding framework ties together all her previous points about reinvention, growth, and human leadership into a coherent leadership philosophy. It provides a roadmap for how leaders should approach AI transformation while emphasizing the collaborative nature of the challenge ahead.

Overall assessment

Explanation

Sweet stated that CEOs should be able to point to new products, services, and performance levels that weren’t possible before, but didn’t specify concrete metrics or benchmarks for success

Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.