Deer Valley, Utah | July 28–31, 2025
2025 KPMG
Tech and Innovation Symposium
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Managing Director and Head of Emerging Solutions
Enterprise Innovation,
KPMG US
Richard Entrup
National Managing Principal of Clients and Markets
Leader for Advisory Markets,
KPMG US
Todd
Lohr
US Leader
Enterprise Innovation,
KPMG US
Cliff
Justice
Over three incredible days in Deer Valley, we explored the forces that will shape the next five years, including the geopolitical landscape, climate perspectives, groundbreaking topics such as AI/GenAI, quantum computing, semiconductors, advanced manufacturing, digital assets, and more.
AI's pervasive influence was evident throughout our discussions, serving as a foundation for much of the dialogue and shaping insights across multiple topics.
I invite you to revisit key moments from this year’s symposium, and I hope to see you again in 2026. Until then, let’s keep shaping the future of business and technology—together!
Disruption is exponential. We’re navigating the most disruptive period in any of our lifetimes. As Salim Ismail shared in his opening keynote, multiple “Gutenberg Moments” are occurring at once—creating significant uncertainty, volatility, and opportunity.
Innovation should be exponential, too.
This is a time for breakthrough ideas, not incremental improvements. To power positive disruption, innovate at the edge of your organization. Otherwise, you risk attack by the legacy “immune system.”
AI will impact everything. AI will change every product, service, and job. While no one can pinpoint when these impacts will happen, now is the time to invest in the human side of innovation.
Focus on the frontiers. The time is NOW for bold thinking and active planning about innovation frontiers like spatial computing and immersive experiences, decentralized technologies, quantum computing, and the space economy.
Sincere thanks to everyone who joined us at the 2025 KPMG Tech and Innovation Symposium in beautiful Deer Valley, Utah!
I invite you to revisit key moments from this year’s symposium, and I hope to see you again in 2026. Until then, let’s keep shaping the future of business and technology—together!
Cliff Justice National Leader of Enterprise Innovation, KPMG US cjustice@kpmg.com
Disruption is exponential.
We’re navigating the most disruptive period in any of our lifetimes. As Salim Ismail shared in his opening keynote, multiple “Gutenberg Moments” are occurring at once—creating significant uncertainty, volatility, and opportunity.
Innovation should be exponential, too.
This is a time for breakthrough ideas, not incremental improvements. To power positive disruption, innovate
at the edge of your organization. Otherwise,
you risk attack by the legacy “immune system.”
AI will impact everything.
AI will change every product, service, and job. While no one can pinpoint when these impacts will happen, now is the time to invest in the human side of innovation.
Focus on the frontiers.
The time is NOW for bold thinking and active planning about innovation frontiers like spatial computing and immersive experiences, decentralized technologies, quantum computing, and the space economy.
1
2
3
4
Executive Director
Enterprise Innovation,
KPMG US
Stephanie
Kim
Powering AI with Nuclear
Gina Raimondo, former Sec of Commerce & former Gov of Rhode Island
Rewiring the Enterprise
Summary:
The opening session, which kicked off the 8th annual KPMG Tech & Innovation Symposium, highlighted significant transformations across industries driven by social, technological, economic, and geopolitical changes. The event host, Cliff Justice, emphasized the rapid advancement of AI and automation, the emergence of "dark factories" in manufacturing, and the critical need for innovation and energy solutions. The discussion highlighted the convergence of various forces shaping the future of technology and innovation over the next three to five years.
Key takeaways:
Rapid technological advancement is reshaping industries and creating a potential AI arms race. Justice noted that AI is on an exponential path to potentially becoming super intelligence, driving dramatic changes across various sectors. These changes are happening in a geopolitical context that is becoming increasingly complex, with major powers competing for dominance in AI development.
The emergence of fully automated "dark factories" is transforming manufacturing. The concept of "dark factories" with minimal human presence is becoming a reality, particularly in China's electric vehicle market. This development marks a shift towards hyper-automation.
The energy crisis poses a significant challenge to AI expansion. The enormous energy demands of data centers require immediate and innovative solutions. Estimates suggest that data centers will require an additional 29 gigawatts of power by 2027 and 67 gigawatts by 2030.
A culture of innovation and a focus on change management will be crucial for companies to survive in the age of AI. Various forces are converging as catalysts for competitive advantage. A culture of innovation, driven by visionary leadership and a bench of strategic partners that includes startups, will differentiate successful companies.
Memorable quotes:
"There has never been a better time to be a startup, and there has never been a better time to change the trajectory of a business."
"Since cultures of innovation are going to differentiate companies, there must be a clear vision that cascades from company leadership to the board to the C-suite to managers to the entire workforce."
How to move forward:
Focus on developing a culture of radical innovation, driven by strong leadership and integration of startups.
Prioritize ways to address the energy demands of AI by exploring diverse energy sources.
Advocate for more direct regulations to guide companies in the safe and secure development of AI initiatives.
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Charting New
Frontiers
2025 KPMG Tech and
Innovation Symposium:
Charting New
Frontiers
2025 KPMG Tech and
Innovation Symposium:
Reframing the Climate Debate
From Content to Context: The Rise
of Agentic AI in
the Enterprise
View the presentation deck from this session
At the event, our team used AI to capture and generate recaps of all the sessions. After the event, we applied human intelligence to quickly validate and refine what the AI produced. The result? Better insights at greater speed and lower cost.
Unpacking the "KPMG 2025 Futures Report"
Adapting at Scale Through the Lens of a Tech Pioneer
Day 1: Drivers of Innovation
AI Adoption, Agents, and AGI/ASI
From Investment to Inference in an Instant
What's Next in Quantum
Navigating the
Energy Crossroads: Innovation, Risk, and Reinvention
Vibe Coding
Future of SaaS
Reframing Frontiers of Innovation
The Future of Everything
The Year in Review
Navigating Digital Assets
Building
and Scaling
AI-Native Products
Navigating the Innovation Economy: VC Perspectives
Boardroom to Breakthrough: Navigating Innovation at the Top
Cozy Cooking with AI
AI at the Edge
The Space Economy
Engineering the Quantum Future: Microsoft's Approach
Open and
Sustainable Compute for the AI Era
Innovation and Trends in Advanced Manufacturing
AI Governance
in the Agentic Era
Realities of
Enterprise AI Deployment
Cutting Through the Clutter
Day 2: Converge on the Frontiers
The Road to Superintelligence
AI and IP -
A Legal Perspective
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Shaping the future through targeted investments in start-ups
KPMG Ventures
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Navigating the opportunities in today's space economy for tomorrow's leaders
KPMG Astro Economy
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Bridging industry and space for limitless opportunities
KPMG +Space
Infinite Horizons
Session recaps
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Unlocking the next level of AI value
The agentic
AI advantage
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Are you ready to harness the power of AI? The time to act is now.
You can with AI - Strategy and Innovation with KPMG
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Seizing opportunities in an era of disruption
KPMG 2025
Futures Report
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Discover how GenAI can unlock uptapped oipportunity for businesses
Quantifying the GenAI opportunity
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A global study 2025
Trust, attitudes and use of artifical intelligence
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From the agent experimentation to rapid scale and deployment
KPMG AI Quarterly Pulse Survey
Summary:
Peter Diamandis explored the exponential transformation driven by converging technologies such as AI, robotics, and epigenetics. He stressed the emergence of advanced AI that will be capable of generating original scientific hypotheses and even designing experiments autonomously—a development that could fundamentally accelerate the pace of discovery in medicine and life sciences. He predicted that humanoid robots will soon be as common as smartphones, reshaping daily life and labor. Most compellingly, he discussed “longevity escape velocity”—the point at which science, propelled by AI and epigenetics, extends human life faster than time passes—suggesting that humanity could eventually reverse aging.
Key takeaways:
AI is driving a global technological arms race: The competition in AI development is intense, with significant investments being made globally. When it comes to innovation, there is a real possibility that startups and smaller companies could outpace traditional multinationals.
“Longevity escape velocity” is on the horizon: Advances in AI and epigenetics are expected to extend human lifespans significantly, with science extending life by more than a year for every year lived.
Humanoid robots will become increasingly common: The development of affordable humanoid robots used in the home will lead to significant changes in daily life and could be an effective way to gather data on human behavior.
Memorable quotes:
"Your job is not to die from something stupid before we are able to extend human life.”
"The competition out there is not the other multinational. It is the young team that is building something that your team thinks can't be done."
"I think one day maybe we can cure all diseases with the help of AI."
How to move forward:
Commit to adapting to the rapid technological changes driven by AI and robotics.
Consider redefining core business models and investing in continuous learning and development for the workforce.
As individuals, adopt proactive health monitoring and preventive measures as AI-driven longevity research progresses toward life extension.
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Summary:
Richard Entrup interviewed Phil Wiser of Paramount about the transformative impact on the media and entertainment industry of emerging technologies, particularly generative AI. The discussion highlighted how AI is reshaping production processes, enabling more agile and iterative storytelling, and presenting both challenges and opportunities for the industry. The discussion delved into the entertainment industry's eagerness to adopt AI and interactive, real-time tools for film production, while balancing the use of these technologies with proprietary content-specific models.
Key takeaways:
AI is driving a shift towards more agile storytelling: The entertainment industry is leveraging AI to enable early visualization and real-time feedback loops, making storytelling more iterative and efficient.
Balancing general and proprietary AI models is critical: The industry is finding a balance between using general AI models for broad applications and developing proprietary models tailored to specific content needs.
Interactive, real-time AI tools are on the horizon: The future of AI in film production is expected to enhance creators’ workflow and make the production process more dynamic and responsive. Many organizations are using interactive tools such as those being developed by companies like Runway.
Memorable quotes:
"FOMO is the most powerful force besides nuclear forces in Hollywood." Phil Wiser
"Emerging technologies, particularly generative AI, are reshaping the future of media and entertainment." Richard Entrup
"The industry is balancing the use of general AI models with proprietary, content-specific models to leverage the strengths of both." Phil Wiser
How to move forward:
Consider investing in AI technology and developing strategies to balance general and proprietary AI models.
Explore emerging tools and resources to future-proof production processes.
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Summary:
Chris Stephens of AI company Groq detailed infrastructure requirements for AI inference, the process of leveraging a trained AI model to make predictions based on new data. He emphasized the rapid adoption of AI technology globally and the need for nations to develop sovereign AI capabilities to ensure data security and governance. This approach is evidenced by Groq's deployments in Saudi Arabia, Canada, and Finland. He also highlighted the importance of developing power-efficient solutions for sustainable AI infrastructure.
Key takeaways:
AI inference is becoming the primary focus of compute cycles: 90 percent of AI work is expected to be inference, driving the need for efficient compute infrastructure.
Sovereign AI capabilities are crucial for data security and governance: Nations are investing in AI infrastructure to maintain technological advantage and ensure data sovereignty.
Power efficiency is essential for sustainable AI infrastructure: The massive energy requirements to power AI capabilities necessitate power-efficient solutions and green energy. Advanced manufacturing and enhanced data center infrastructures will be critical to support growing AI adoption.
Memorable quotes:
"Nations are recognizing the importance of sovereign AI capabilities for data security and governance." Chris Stephens
"AI inference is becoming the primary focus of compute cycles, driving the need for efficient infrastructure." Chris Stephens
How to move forward:
Develop power-efficient AI infrastructures and invest in advanced manufacturing capabilities.
Leverage AI inference centers to support the growing demand for AI inference while ensuring data security and governance.
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Summary:
KPMG’s Kelly Combs and Jonathan Dambrot, CEO of Cranium AI (a KPMG spin-off) explored the cybersecurity implications of implementing AI at scale within corporate organizations. They stressed that continuous and AI-driven governance is critical, as is navigating the regulatory landscape and adapting business structures to align with an AI-enabled workforce. The conversation also touched on the implications of deep fakes and misinformation in the context of AI security.
Key takeaways:
Traditional risk management approaches are insufficient for AI governance. Traditional methods of risk management, established over decades, are not adequate for securing AI in production. It is critical to integrate “security by design” into AI development processes.
AI systems are often deployed quickly without adequate security measures. Although many companies want to rapidly operationalize AI solutions, doing so without considering security implications could put companies at major risk.
Machine-to-machine solutions are necessary to detect and prevent deep fakes and misinformation. There is a growing threat of deep fakes and humans are limited in their ability to detect such threats. Therefore, AI systems must be designed to detect and prevent these emerging threats.
How to move forward:
Prioritize the development of AI-driven governance frameworks that integrate security by design into AI development processes.
Implement continuous monitoring and control measures to address the rapidly evolving AI landscape and emerging threats like deep fakes.
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Summary:
Scott Lawrence, SVP & Chief Product Officer at Verizon Business, highlighted a transformative shift in AI adoption: moving intelligence from the cloud to the edge. Edge AI empowers businesses with ultra-low latency, real-time decision-making, and improved data sovereignty by processing information closer to its source. He underscored the urgency for organizations to rethink operations and infrastructure to harness these advantages - especially in healthcare, industrial automation, disaster management, and autonomous vehicles. As AI adoption accelerates, the edge is fast becoming a strategic battleground, offering unprecedented efficiency and autonomy. To stay ahead, companies must assess where edge AI can maximize impact, viewing it not just as a new location, but as a genuine power shift in business strategy.
Key takeaways:
Edge AI offers significant advantages in latency, autonomy, and data sovereignty. Edge AI reduces latency by processing data closer to the source, enhances autonomy by enabling real-time decision-making, and improves data sovereignty by keeping data local.
Businesses must radically change their thinking to succeed in an AI-driven future. The adoption of edge AI requires a fundamental shift in how businesses operate, strategize, and adapt their infrastructure.
Memorable quotes:
"Edge AI is no longer just a convenience, it's a way for AI to function at scale. "Building solutions at the edge is a way to future proof your business."
“We are now entering a new frontier where intelligence doesn’t live just on distant servers. It lives where the action is, right on the edge.”
"The shift to edge AI is influencing the design of new devices that are AI native and increasingly agentic acting will be deciding and engaging autonomously."
How to move forward:
Leverage edge AI effectively by focusing on understanding the different aspects of the AI landscape, including the races for models, talent, and infrastructure.
Assess your current infrastructure and strategies to identify areas where edge AI can be integrated to enhance latency, autonomy, and data sovereignty.
Consider that the future will require not just building AI products, but also building AI environments and connecting new AI ecosystems where infrastructure acts with purpose.
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Summary:
Host of the AI Daily Brief, Nathaniel Whittemore, spotlighted the unprecedented acceleration of AI, noting that Chat GPT reached 100 million users in just five weeks—a testament to the technology’s explosive growth. He emphasized agentic coding as a transformative force, empowering non-technical employees to build new tools and boost productivity. While enterprise adoption has surged—with 42 percent of US businesses using AI as of Q1 2024—challenges remain. A striking gap exists between executives and staff on perceived AI success, and only 22 percent of organizations feel their data architecture is ready for integration. As reasoning models and general-purpose agents redefine workflows, organizations are not just adapting to the technology but also reimagining their core operations to uncover fresh opportunities.
Key takeaways:
AI adoption is accelerating rapidly: The pace of AI adoption is unprecedented in both consumer and enterprise contexts.
Agentic coding is revolutionizing business operations: Agentic coding has emerged as a primary use case for AI in businesses, enabling non-technical employees to prototype new features and design internal tooling.
AI is redefining workflows and job roles: The introduction of reasoning models and general-purpose agents is leading to a fundamental rethinking and redesigning of workflows and job roles.
Memorable quotes:
"The more people use AI, the more that they discover that the best uses for AI are using more AI. Change is bigger and happening even faster than we think."
"One of the things that makes agentic coding so fascinating is that it's one of the first examples we have where AI capabilities are democratizing a capacity that wasn't available before."
"There's very clearly a sense among people deploying agents that the opportunity set is not constrained to just people doing their existing work a little faster, a little better."
How to move forward:
Take steps to bridge the gap between leadership and employee perceptions of AI adoption by enhancing communication and engagement.
Consider how AI can redefine workflows and job roles, potentially unlocking new revenue opportunities.
Stay abreast of the latest technology launches, such as agentic coding.
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Summary:
Professor Christa Laser of Cleveland State University explored the legal challenges posed by AI as it relates to intellectual property. Key topics included copyright risks from using protected content for AI training, the public domain status of AI-generated works, pitfalls in trademark and patent law, and dangers of deep fakes. Laser recommended protecting trade secrets and stressed the urgency of legal adaptation as AI reshapes creativity, ownership, and risk.
Key takeaways:
AI companies face significant legal risks: AI companies are at risk of facing billions or even trillions of dollars in damages for using copyrighted works to train their models without proper authorization.
AI-generated works may not be protectable: Works generated by AI are not protectable under current copyright law because they lack human creativity.
Trade secrets can be a fallback for protection: While copyright and patent protection may not be available for AI-generated content, trade secrets can serve as an alternative.
Users of AI systems are also at risk: Users can be liable for copyright violations if AI outputs infringe on existing copyrights.
Memorable quotes:
"There are legal risks that span the whole range of intellectual property law from AI companies that may face billions or even up to $1 trillion of damages for using copyrighted works to train their large language models."
"You cannot excuse piracy by eventually using that piracy for training an AI model."
"If you prompt ChatGPT to create an image that contains a Disney character, and then you publish that on your social media, you're infringing Disney's copyright."
How to move forward:
Establish clear policies regarding AI use, particularly for critical intellectual property.
Ensure that employees and contractors do not use AI for tasks where IP protection is crucial.
Be cautious about sourcing training data and monitor AI outputs to avoid potential infringements.
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Summary:
Cliff Justice interviewed Gina Raimondo, which focused on the AI arms race between the US and China and highlighted the resulting geopolitical and economic implications. Raimondo emphasized the complexities of controlling access to AI innovations and the need for the US to maintain its competitive edge through innovation and strategic alliances. The discussion also touched on how technological leadership in the US will be increasingly dependent on reform of higher education and immigration policies so that the best talent from all over the world can contribute to innovation in the US.
Key takeaways:
The AI arms race is complex and multifaceted: The AI arms race between the US and China involves not only technological competition but also geopolitical and economic dimensions. Raimondo highlighted the importance of tracking and controlling AI technologies to restrict their spread to China.
Innovation and regulation are crucial: To maintain its leadership in AI, the US must balance innovation with regulation to mitigate AI risks, including job displacement and threats to democracy. Raimondo stressed the importance of protecting leading-edge technologies while fostering cooperation with allies.
Reform of American universities and immigration policies will be key drivers of US innovation: Raimondo praised American research universities as global leaders and noted the significant contributions of highly skilled émigrés to US technology companies. However, she also criticized outdated practices in higher education and corporate hiring, calling for reforms to better prepare the workforce for an AI-driven future.
Memorable quotes:
"The AI arms race is not just about technology; it's about the future of our economy and our democracy."
"American research universities are the envy of the world, and we must continue to support them."
"We need to innovate in AI while addressing its risks to ensure it benefits our society."
How to move forward:
Focus on protecting and infusing AI technology throughout American businesses.
Reform higher education and hiring practices, while putting greater emphasis on vocational training.
Keep abreast of other nations’ innovation agendas, so the US can maintain its competitive edge.
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Summary:
The session "Reframing the Climate Debate" led by Steve Koonin focused on analyzing the current state of climate science, the reliability of climate models, and the challenges in transitioning to a future more focused on sustainable energy. Koonin emphasized the complexity of climate change, highlighting natural variability and the limitations of current climate-change models. The discussion also covered the technoeconomic realities of the energy transition and energy demand, as well as the importance of resilience strategies.
Key takeaways:
Climate change is a complex issue with significant natural variability: Koonin highlighted that natural variability has been a constant throughout history and that human influence, while growing, is still a relatively small factor (1%). He supports this with historical data, such as the 1000-year record of the Nile River's height.
The energy transition faces significant challenges: The global effort to reduce emissions is hindered by reliability, cost, and geopolitical factors. For example, fossil fuel use and greenhouse gas emissions remain at record highs despite efforts to transition to cleaner energy sources. Koonin emphasized the need to develop emission-light technologies like nuclear power to address energy demands while reducing emissions.
Some current climate models are limited: Koonin argued that many climate models are not fit for purpose due to their inability to accurately predict future climate trends. Many of these models are not able to track certain environmental aspects, such as clouds and ocean currents.
Memorable quotes:
"The climate is changing. Human influences are a factor, but the situation is complex and not as straightforward as often portrayed."
"We need a much greater focus on adaptation and resilience. We don't really have a good framework or good sense of the cost; we don't even prepare for the past as the floods in Texas illustrate."
"We need to focus on energy and climate literacy, continued climate observation, adaptation, and resilience."
How to move forward:
To effectively address climate change, prioritize adaptation and resilience strategies, particularly in developing regions.
Invest in research and development for clean-energy technologies, including nuclear.
Develop resilience in the face of extreme weather events by creating better frameworks for understanding the costs effective prevention measures.
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Summary:
KPMG CMO Lauren Boyman interviewed May Habib about the transformative impact of agentic AI on enterprises, focusing on its role in content creation, content strategy, and business transformation. Insights were shared about how KPMG has leveraged Writer's AI tool to enhance content creation, resulting in significant time savings and improved output quality. The dialogue stressed the importance of recognizing that AI adoption goes beyond technology implementation, requiring a human-centric approach, organizational restructuring, role transformation, and cultural shifts. The discussion also touched on the potential of AI in personalized education and the need for AI literacy across organizations.
Key takeaways:
AI enhances content creation processes: The integration of AI tools has significantly improved content creation for KPMG, saving thousands of hours and enhancing output quality, allowing creative teams to focus on higher-value tasks.
Cultural shifts are crucial: Successful AI implementation requires more than just technology; it demands a cultural shift within the organization. Leveraging AI effectively requires breaking down organizational silos and redefining job descriptions.
Flexible AI governance models are essential: Governance models like KPMG’s aIQ which enable scalable and secure AI agent development, allows companies to manage risks while fostering innovation.
New roles will emerge concurrently with AI adoption: New roles, such as agent builders and owners, are emerging to help companies effectively utilize AI and maximize its potential.
Memorable quotes:
"The future of AI is not just about technology; it's about how we use it to augment human capabilities." May Habib
"AI is not just a tool; it's a catalyst for cultural and organizational transformation." Lauren Boyman
"The key to successful AI adoption is not just implementing the technology but also transforming the way we work." May Habib
How to move forward:
Take a human-centric approach to AI initiatives and the development of AI agents.
Restructure your organization to allow innovation from anywhere.
Adopt governance frameworks to maximize the potential of AI while mitigating risks.
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Summary:
Jacob DeWitte, CEO of Oklo, discussed the critical role of nuclear energy in meeting the escalating power demands driven by advancements in AI. He stressed how nuclear fission is uniquely positioned to address the energy crisis due to its high material efficiency and reliable power generation. The advantages of small modular reactors (SMRs) were also highlighted, including their potential for quicker and more cost-effective deployment compared to traditional large-scale nuclear plants.
Key takeaways:
Nuclear energy is crucial to meet AI's growing power demands: AI could require up to 90 extra gigawatts of power over the next five years, and nuclear energy could provide a reliable and scalable solution to make up for potential shortages.
Small modular reactors offer scalability and flexibility: SMRs can be deployed more quickly and cost-effectively than traditional nuclear plants. DeWitte stressed that Oklo's approach centers on designing inherently and passively safe reactors, leveraging modern industrial practices to reduce costs.
Public perception and community engagement are critical: DeWitte emphasized the importance of engaging with local communities to build support for nuclear projects. There has been a shift in public opinion toward accepting nuclear energy as an avenue for combating climate change.
The regulatory environment is becoming more favorable: The regulatory landscape is evolving to support nuclear innovation, with potential for significant cost reductions through advancements in technology.
Memorable quotes:
"The energy potential of nuclear fission is vast and can meet the growing demands driven by AI."
"Designing inherently safe nuclear reactors is crucial for public acceptance and safety."
"Advanced nuclear technology with recycling can significantly reduce costs and improve efficiency."
How to move forward:
Consider leveraging small modular reactors for more rapid deployment.
Engage with local communities to address public perception challenges.
Ensure your focus is on inherently safe designs, which can result in reduced costs and faster scalability of nuclear energy solutions.
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Summary:
KPMG Executive Director of Enterprise Innovation, Stephanie Kim, gave a preview of the second day of the Symposium by presenting an overview of the seven frontiers of change detailed in the 2025 KPMG Futures Report. The frontiers are artificial superintelligence, computing infrastructure, quantum computing, advanced manufacturing, digital assets, environmental resilience, and the emerging space economy. The discussion stressed the importance of strategic foresight and identifying signals of change to prepare to take advantage of potential growth opportunities in each of these areas.
Key takeaways:
Subtle signals drive significant business transformations. It is critical to pay attention to minor but impactful elements that can significantly influence business strategy. Acting on these signals allows companies to plan for strategic integration of new technologies and understand their potential applications.
Advanced manufacturing is being reshaped by digitalization and sustainability. Significant investments are being made in sectors like semiconductors, clean energy, and smart factories, indicating a shift toward a digitally enabled and AI-augmented workforce.
The convergence of AI and quantum computing is opening new technological frontiers. Quantum computing could solve problems that are currently not feasible for classical computers, potentially revolutionizing various industries.
Environmental resilience is becoming a core business strategy. Companies are increasingly incorporating environmental resilience into their operations and financial strategies, reflecting a growing recognition of its importance.
The space economy is emerging as a new frontier for innovation. Reduced launch costs and private investments are opening real-world applications in the space sector.
Memorable quotes:
"The path to artificial superintelligence is being paved by advancements in compute infrastructure."
"Environmental resilience is no longer just a corporate social responsibility; it's becoming a core business strategy."
How to move forward:
Adopt forward-looking strategies by paying attention to subtle market signals.
Carefully consider how your organization can take advantage of opportunities in emerging frontiers such as digitally enabled manufacturing, quantum computing, and the space economy.
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Panel:
Shibani Ahuja, SVP, Marketing, Enterprise IT Strategy at Salesforce
Brian Emerson, GVP & GM, IT Ops Mgmt & Observability at ServiceNow
Riley Hawkins, Agentic AI Global Strategy Lead, Workday
Nathan Thomas, VP of Product Management, Oracle
Summary:
Todd Lohr hosted a panel of industry experts who focused on the evolution of the Software as a Service (SaaS) model in the context of emerging technologies like AI and agentic technologies. The discussion centered on the transformation of SaaS from a vertical solution to a horizontal platform, a shift that is expected to significantly impact how businesses operate. Forward-reaching assumptions are that the future of SaaS will involve a shift from traditional user interfaces to conversational and autonomous interfaces.
Key takeaways:
SaaS is evolving into a horizontal platform: The traditional vertical SaaS model is giving way to more integrated horizontal platforms, driven by AI and agentic technologies. This shift is expected to enhance customer experience and improve operational efficiency.
AI is accelerating SaaS deployment and maintenance: The integration of AI into SaaS platforms is significantly reducing the time to value for enterprise solutions and creating more seamless user experiences.
Conversational interfaces are on the rise: The future of SaaS is expected to see a reduction in traditional user interfaces in favor of more conversational and autonomous interfaces. Platforms like Slack are being integrated into unified platforms to facilitate digital and human labor convergence.
Memorable quotes:
"SAS 2.0 with the horizontal platform concept will allow our customers to move faster." Brian Emerson
"Agentic AI is doing things that we would never even have thought of doing with people because it was just impossible to do." Nathan Thomas
“AI can mitigate risk and provide compliance protection in ways that human teams alone cannot achieve.” Riley Hawkins
"Slack is now a deeply unified platform on a single code base where digital labor and human labor are coming together." Shibani Ahuja
How to move forward:
Integrate AI and agentic technologies into SaaS solutions to realize competitive advantage.
Track new developments in SaaS and AI technologies.
Leverage AI in SaaS to automate tasks and improve user interfaces.
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Summary:
The session on Vibe Coding centered on a live demonstration of how to develop an invoice processing application using white coding and AI tools like LlamaIndex and Cursor. Liu and Swami showcased how hand-sketch designs and natural language prompts can be transformed into functional apps, highlighting the ease and speed of modern AI-assisted software development. The discussion also touched on how white coding can enhance product managers’ roles and the importance of domain expertise when leveraging AI for application development.
Key takeaways:
Live coding and AI tools accelerate development: AI tools can significantly accelerate the application development process, even for non-technical users.
White coding enables rapid MVP and POC creation: White coding allows for the quick creation of minimum viable products (MVPs) and proofs of concept (POCs). However, rigorous testing is still required to ensure production readiness.
Domain expertise is crucial for AI-driven development: Domain expertise is essential for guiding AI tools and ensuring that developed applications are reliable and meet specific domain needs.
Memorable quotes:
"LlamaCloud basically is a knowledge management layer for AI agents. It can index thousands to even millions of documents and make all that context available to your LLM, effectively giving it an unlimited context window.” Jerry Liu
“White coding is the new PowerPoint. It's a way to bring concepts to life." Swami Chandrasekaran
How to move forward:
Explore white coding and AI tools like LlamaIndex and Cursor to accelerate your development processes.
Leverage domain expertise to guide AI-driven development and ensure thorough testing for production readiness.
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Summary:
Cliff Justice interviewed Mark Lashier, CEO of Phillips 66, on the company’s evolution from a petroleum company to an integrated downstream energy company, as well as its mission to improve lives while adapting to a low-carbon future. Lashier spoke about the use of AI and machine learning in improving operational efficiency and safety, while also reducing maintenance costs in refineries and petrochemical plants. Phillips 66 is investing in renewables and diversifying to manage geopolitical risks. Lashier emphasized balancing short-term profitability with long-term innovation to adapt to the rapidly changing energy landscape.
Key takeaways:
Energy companies must adapt to a low-carbon future through innovative technologies and strategic investments. Phillips 66 is investing in renewable energy, such as renewable diesel and sustainable aviation fuel, as part of the evolution to a low-carbon future. The company is also exploring solar and wind energy, hydrogen production, and carbon capture.
AI can help energy companies increase their “up time.” AI is being used at Phillips 66 for predictive maintenance, reducing the need for routine shutdowns and enhancing safety.
Diversification is key to managing geopolitical risks in the energy supply chain: Strategic planning is critical for mitigating geopolitical risks, given the unpredictability of regulatory changes, especially in the renewable energy sector.
Memorable quotes:
"The biggest challenge that I faced over the last few years is getting our organization to challenge the status quo, to change how we think about things because things are changing so fast." Mark Lashier
"AI combined with quantum computing can really drive those kinds of innovations that we may be working on today, but it'll close that time gap and it won't force us to test 1000 different options. It'll identify the best three options that we can test and implement." Mark Lashier
How to move forward:
Focus on strategic investments in renewable energy to navigate the energy crossroads effectively.
Leverage advanced technologies like AI and machine learning to maximize operational efficiency and safety
Adopt a realistic and forward-looking approach to the energy transition, striking a balance between short-term profitability and long-term innovation.
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Summary:
Scott Crowder of IBM explored the current state and future prospects of quantum computing. He emphasized that, while quantum computing is advancing, it remains in an intermediate stage and faces significant challenges before becoming broadly useful. The session highlighted the potential impact of quantum computing on various fields and stressed the importance of a collaborative ecosystem for quantum development.
Key takeaways:
Quantum computing will have a profound impact on various fields. The technology is expected to significantly impact areas such as cryptography, materials science, and machine learning, offering solutions to complex problems that are currently unsolvable or require extensive computational resources.
A strong ecosystem is crucial for the development of quantum computing. Collaboration between industry, startups, and researchers will be necessary to develop algorithms and applications for quantum computing and ensuring practical uses of the technology.
Memorable quotes:
"Quantum computing is real and can perform tasks beyond classical computers."
"The development of efficient error-correcting codes is crucial for scaling up quantum computing."
"Building an ecosystem involving hardware, software, and algorithmic research is essential for advancing quantum computing."
How to move forward:
Consider how to build a collaborative ecosystem that integrates hardware, software, and algorithmic research.
Develop efficient error-correcting codes and modular approaches to scaling the technology.
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Summary:
KPMG’s Chad Seiler interviewed Yvette Kanouff and Sharon Zhou on the development of personal AI agents, the evolving role of humans in an AI-driven world, and the need for robust regulation and transparency around AI adoption. The panelists highlighted the trend towards larger, more intelligent AI models and that, while AI can automate many tasks, the key differentiator for human workers will be their drive and creativity.
Key takeaways:
The future of AI involves larger, more intelligent models. The trend of AI models getting larger and more intelligent will continue, driven by more data and more powerful compute.
Human drive and curiosity are crucial in an AI-driven world. As AI automates traditional tasks, human qualities like drive, curiosity, and transformational thinking will be more important than ever.
AI adoption requires robust regulation and transparency. Regulation and transparency are critical to ensuring fair and trustworthy AI systems.
Memorable quotes:
"AI is a probabilistic system as opposed to a deterministic system. A deterministic system will produce the same output all the time, whereas AI outputs probabilities of things." Sharon Zhou
“With AI, I think we have to change our whole ecosystem, the way we run the company, the way we interview, the way we transform our staff.” Yvette Kanouff
How to move forward:
Upskill the workforce to complement AI capabilities, particularly in areas requiring human drive and curiosity.
Evolve traditional interview processes to identify potential employees with the right qualities for working with AI as a thought partner.
Prioritize transparency and regulatory compliance in your AI strategies to ensure trustworthy and fair AI systems.
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Summary:
This panel, moderated by Greg Genega of KPMG examined how the Genius Act and other new regulations are shaping blockchain and stablecoin adoption, with a focus on cross-border payments and financial inclusion. Panelists explored Bitcoin’s continued value, the synergy between generative AI and blockchain, and the promise of improved user experiences and security. The discussion highlighted the vital role of regulatory clarity in driving innovation and trust in the digital asset ecosystem.
Key takeaways:
The Genius Act enhances the safety and security of stablecoins: By mandating registered issuers and third-party audits, the Genius Act provides a regulatory framework that could boost the secure adoption of payment stablecoins.
Stablecoins have transformative potential in cross-border payments: Stablecoins can significantly reduce the cost and increase the efficiency of cross-border transactions, making them a vital component of the future financial infrastructure.
Generative AI and blockchain synergy revolutionizes user experiences: The user experience can be elevated through the combination of generative AI and blockchain, which can be used to create more user-friendly interfaces and enhance the security of smart contracts.
Bitcoin remains a significant store of value: Bitcoin is viewed by some as a near-perfect store of value due to its use as a hedge against inflation and the collective agreement on its value in the digital asset ecosystem.
Memorable quotes:·
"Blockchain can provide a cryptographic anchor to us as humans and how we transact online and it provides things like deep fake protection." Greg Genega
"The Genius Act provides safety and security for stablecoins, ensuring that issuers are registered, hold reserves in specific assets, and undergo third-party attestation and audits. " Anthony Tuths
"The blockchain really does do something new and different, and it's important that the US embraces these technologies." Trevor Traina
"The combination of generative AI and blockchain technology can significantly enhance the user experience and security of smart contracts." Scott Stornetta
“There will be significant future demand as 90 percent of the people that are going to hold digital assets or Bitcoin aren't even in the market yet right now." Jody Mettler
How to move forward:
Develop solutions that comply with emerging regulatory frameworks like the Genius Act. Explore the integration of generative AI with blockchain technology to enhance user experience and security.
Consider using AI tools, such as LLMs, for writing and auditing code.
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Summary:
Jason Calacanis delivered a provocative talk discussing the transformations in technology, media, and society over the past year and predicting future trends. He focused on the impact of artificial intelligence (AI) on various industries and how the rise of AI is rapidly changing the job market and the professional skills required for various professions. One example he highlighted was the media and entertainment industry, which is undergoing significant changes due to AI, leading to new business models and opportunities. He also provided insights on how healthcare is becoming more self-directed due to advancements in AI and personal health technology, which enable individuals to monitor their health metrics and make informed decisions.
Key takeaways:
AI is rapidly changing the job market and required skills. AI and machine learning models are significantly impacting the job market, with certain professions potentially being replaced by automation.
The media and entertainment industries are undergoing significant changes due to AI. Independent creators are leveraging AI to produce content and build their own platforms, often leaving traditional media companies behind.
The future of healthcare is becoming more self-directed. New technologies are empowering individuals to monitor chronic conditions and take control of their health.
Memorable quotes:
"We're now moving in venture and in startups to consumption-based or outcome-based pricing.”
“LLMs are becoming commodified, and the competition among AI companies is intense, with models improving rapidly.”
"If you want to have a great health span, think about GLPs, which will be in pill form next year. They are going to be free and ubiquitous."
How to move forward:
Consider how AI can be leveraged to enhance productivity and create new opportunities.
Explore tools and technologies that enable self-directed healthcare.
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Summary:
In a dynamic panel moderated by Jason Calacanis, visionary leaders gathered to explore the unfolding landscape of education, technology, and societal transformation. The conversation delved into how artificial intelligence and robotics are not merely altering educational models but reshaping the very foundation of how we learn and lead. The panelists championed innovative approaches, spotlighting the rise of personalized, AI-driven education and the potential obsolescence of traditional universities. The discussion extended into broader themes such as the ethical frontiers of brain-computer interfaces and the possibility of extending the average human lifespan.
Key takeaways:
Traditional universities will evolve as new education models emerge. In the age of AI, there will likely be a need for more and different types of education. However, it may not necessarily be provided in traditional four-year university settings.
Education leaders need to be careful about losing human connection: AI has the potential to significantly accelerate learning, but there are concerns about the loss of human connection and the ability to teach students how to handle complex, real-world problems.
Positive visions for the future are essential for progress. Leaders should endeavor to have a clear and positive vision for the future to guide current actions and decisions.
Memorable quotes:
"The future is not something we wait for; it's something we create." Peter Diamandis
“Ten years from now, there will be a transition from operating company to platform to ecosystem, just as we saw in the Internet world. These platforms will be smaller because innovation doesn't happen at a large scale.” Salim Ismail
“AI will provide personalized education that individuals can access as needed to inform new jobs or projects.” Ted Shelton
How to move forward:
Consider that liberal arts may evolve to be the best path to success in the age of AI because it fosters critical thinking, curiosity, creativity and the ability to forge interpersonal relationships.
Be mindful of the potential ethical consequences of machine/human interface and how that might widen the opportunity gap and foster greater inequality.
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Summary:
Claudia Saran, KPMG’s US Sector Leader for Industrial Manufacturing, moderated a discussion with Lerrel Pinto and Ethan Carp. The discussion centered on the future of manufacturing, focusing on the integration of humanoid robots and practical AI applications. The discussion highlighted the shift from structured automation to more versatile human-form factor robots, which, in combination with AI, can help address the labor shortage by complementing workers and increasing efficiency. One caveat is that the adoption of AI and robotics may be limited for some companies by high capital costs and the need for a clear return on investment.
Key takeaways:
Humanoid robots are revolutionizing manufacturing processes. Robots are being integrated into manufacturing to enhance processes rather than completely automate production floors.
Labor strategies require a comprehensive workforce development approach. Addressing labor shortages goes beyond technology adoption and requires community engagement and training programs to upskill workers.
There are ways to address high capital costs and ROI expectations. Manufacturers can address resistance to AI and robotics adoption by quantifying the benefits of resilience.
Memorable quotes:
"Robotics is the only answer here. It's the only way we can upskill people. Most of the robots we create, there is a human involved, but it allows humans to magnify the level of production they can create." Lerrel Pinto
"There may be a shortening of jobs, but also keep in mind that, in America at least, we've lost 70 percent of jobs already due to automation. It's not going to go much lower as we add robots. We will just grow the number of things we can make.” Ethan Karp
How to move forward:
Adopt human-form factor robots and gain familiarity with new technologies through proof-of-concept contracts.
Foster collaboration between workforce organizations, government, and businesses to forge effective workforce development strategies.
Understand the potential return on investment and monetize the benefits of resilience to make informed decisions about adopting AI and robotics.
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Summary:
AMD’s Mark Papermaster explored how AI is revolutionizing business strategies and innovation. He emphasized that open systems and industry collaboration are crucial for enabling rapid AI advancements and flexible solutions. However, AI’s rising power demands present significant sustainability challenges, making thoughtful deployment and energy management essential. He highlighted the semiconductor industry’s efforts to build resilient, diverse supply chains to ensure resilience and security in AI hardware production. Ultimately, he reminded attendees that human expertise remains central, guiding how AI accelerates productivity, scientific discovery, and transformative change across industries.
Key takeaways:
AI is driving a fundamental shift in business innovation and strategy. AI is redefining how companies approach innovation, with a focus on rethinking processes and enhancing productivity, as is evident in areas ranging from everyday applications to scientific research.
Open systems and collaboration are crucial for AI innovation. Open standards and collaboration are essential for the successful deployment and innovation of AI technologies, allowing companies to choose the best solutions for their needs.
Managing AI's energy demands is a significant challenge. Thoughtful deployment of AI is critical for managing energy requirements and ensuring sustainability in the face of increasing adoption.
Memorable quotes:
"Open systems bring choice. You want maximum choice when it comes to what solution you're bringing and how you go about implementing it."
"For your people, if they're embracing AI, they're going to be 10X the engineer they were before deploying AI."
"AI is a complete game changer. Mixing traditional supercomputing with AI approximations for portions of the problem accelerates the time to invention."
How to move forward:
Focus on integrating AI thoughtfully, leveraging open systems, and managing energy demands.
Enhance productivity and drive innovation by adopting AI-native strategies and ensuring supply chain diversity.
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Summary:
Zulfi Alam, Corporate Vice President of Quantum at Microsoft, shared how quantum computing is set to revolutionize material science and chemistry by allowing simulations of electron-level properties previously impossible with classical machines. Microsoft’s breakthrough—a dual ion battery with 70 percent less lithium—demonstrates quantum’s real-world promise. He emphasized that the future lies in hybrid systems, where CPUs, GPUs, and QPUs work together, underpinned by robust error correction and a specialized quantum operating system. He urged corporations to adopt post-quantum cryptography now, preparing for rising quantum threats. As tools become more accessible, Microsoft remains at the forefront, helping organizations adapt their tech stacks for the quantum era and providing development toolkits and error correction tools that abstract the complexities of quantum algorithms, making it easier for developers to work with quantum computing.
Key takeaways:
Quantum computing revolutionizes material science and chemistry: Quantum computing offers unprecedented simulations of complex chemical reactions and material properties at the electron level.
Hybrid quantum-classical systems are the future: The development of quantum computing is not just about creating standalone quantum machines but about building hybrid systems that integrate both classical and quantum processing units.
Corporations must prepare for the risks associated with the quantum era: Corporations need to focus on post-quantum cryptography (PQC) and integrate quantum operating systems into their tech stacks.
Quantum computing development environments are becoming more accessible: The development environment for quantum computing is evolving to become more user-friendly and accessible, much like classical computing environments.
Memorable quotes:
"The first thing that corporations ought to be doing is post-quantum crypto. That is a classical algorithm that does not require a quantum machine that needs to happen very, very soon, and it's going to be a journey to implement those because most of the systems are not enabled for that."
"With 1 million physical qubits, you have more computational power than the entire planet put together and it can essentially solve any computation problem. That is where the power of the machine really shines in terms of changing the course of humanity."
"With a hybrid quantum/classical computing tool, you need artificial intelligence. This type of system end to end is going to be the one that's generating real value."
How to move forward
Prepare for the quantum era by implementing post-quantum cryptography and exploring the integration of quantum operating systems into your tech stack.
Explore the use cases that will be possible by integrating AI with hybrid quantum/classical computing systems.
Reduce the learning curve for quantum through abstraction and the use of AI tools.
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Summary:
Brian Miske of KPMG and Kylie Ho of Blue Origin explored the booming space economy. With industry value projected at $1.8 trillion by 2035, a much lower cost of entry and surging private investment are transforming space into a frontier of commerce and innovation. Over the past 15 years, reusable rockets have lowered launch costs from $500 million to less than $100 million. Companies are encouraged to dedicate one percent of their R&D budgets to space initiatives, with opportunities in satellite data, microgravity manufacturing, and private space stations. The discussion highlighted that space assets are now essential for global connectivity, disaster prevention, and environmental monitoring. With the hope that the next generation will be inspired to participate more widely in the space industry, now is the time for organizations to experiment and define their space strategies.
Key takeaways:
The space industry is poised for significant growth: The Space Economy is being driven by reduced access costs and increased private investment.
Space technology is crucial for global connectivity and data collection: Space-based assets and satellite data play vital roles in environmental monitoring, disaster prevention, and global communication.
Inspiring the next generation is critical: There is an urgent need to diversify the space workforce and encourage more people to pursue careers in the space industry.
Memorable quotes:
The space industry is no longer just about rockets and astronauts; it is becoming a domain of exploration, commerce, and innovation. Space is the next generation or next layer of digital infrastructure." Brian Miske
"Microgravity or zero-g allows for the creation of materials and drugs that are impossible to develop on Earth, particularly in drug development and material science.” Kylie Ho
“As we transition to the concept of Space as a Service, private space stations could serve as platforms for R&D and manufacturing.” Brian Miske
"The way forward is moving heavy industry off of Earth, so you are not polluting the environment." Kylie Ho
How to move forward:
Start developing a space strategy by allocating resources to understand the potential applications of space technology in your industry.
Consider how you might apply satellite data for environmental monitoring and disaster prevention.
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Summary:
John Maeda of Microsoft used culinary metaphors to demystify AI in natural language processing, emphasizing the importance of context and cognition in creating intelligent AI systems. He highlighted how embedding models drives more accurate and diverse semantic understanding. By integrating retrieval augmentation generation (RAG), AI systems deliver context-rich, relevant outputs. LLMs’ ability to transform unstructured data into structured formats can automate tasks that would otherwise require manual intervention, such as filling out contact forms or creating data entries.
Key takeaways:
Newer embedding models enhance AI-driven search: Embedding models can improve the efficiency and accuracy of AI-driven search and retrieval.
Large Language Models excel at data structuring: LLMs can convert unstructured data into structured formats, which can be leveraged for various practical applications.
Context is critical with AI: A completion model without context can lead to "hallucination," or making up information that isn’t accurate. When context is added, models produce more relevant and accurate completion.
Memorable quotes:
"Large Language Models excel at converting unstructured data into structured formats, enhancing their practical applications and making it easier to work with and pass on to other systems."
“The concept of an ‘agent’ in AI is a byproduct of the model's ability to manipulate data and access real-world information."
How to move forward:
Integrate context into your models to avoid hallucinations.
Upgrade to newer embedding models to enhance search and retrieval capabilities.
Use Large Language Models for data structuring to improve productivity and efficiency in various applications.
Upgrade your embedding model to improve your retrieval augmentation generation.
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Summary:
Ted Shelton of Inflection AI led the final session of the Symposium, exploring the astonishing pace of AI development, from toddler-level intelligence in 2020 to near high school proficiency by 2023 to a future marked by super intelligence. The discussion highlighted the uneven distribution of AI advancements and the need for a resilient workforce that can adapt to these changes. - Super intelligence, which is substantially better than any human at everything, will challenge the traditional roles of humans in the workforce. And yet, it is critical to preserve human-centric values—personal relationships, creativity, and accountability. The session concluded with a powerful message: organizations must act now, harnessing AI's potential while safeguarding what makes us uniquely human in a rapidly changing world.
Key takeaways:
Human-machine collaboration is crucial: It is important to integrate AI into organizations through leadership, employee experimentation, and dedicated labs. This approach helps create a resilient workforce that can adapt to AI-driven changes.
Preserving human-centric values is essential: As AI evolves, Shelton stresses the importance of maintaining human-centric values to ensure that AI is used in ways that align with human interests and ethical standards.
Memorable quotes:
"The future is already here, it is just unevenly distributed." Quoting author William Gibson
"We are in a period of exponential change, and it's not OK to wait a year. It's not OK to wait a day. We actually need to be doing stuff now."
"There are three really important things that we should hang on to: personal relationships, creativity, and accountability."
"We need to build a very different kind of resilient workforce that is constantly experimenting."
“Leaders need to be willing to dive in and try to understand this and be supportive, provide the protection for people to make mistakes, and provide the funding to run fast and try different things. This involves creating a culture where employees can experiment with AI in their daily tasks, share their discoveries, and learn from each other.”
How to move forward:
Build a resilient workforce by encouraging experimentation with AI and providing leadership support.
Harness the potential of AI while preserving essential human values.
Establish a dedicated lab environment with a group of people that are taking whatever is the bleeding edge of this technology and experimenting with your business's problems in a safe way.
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Summary:
Nathaniel Whittemore led a panel that delved into how AI integration is reshaping organizations, not just by boosting efficiency but by redefining value, strategy, and human roles. The pivotal transition from traditional to agentic AI is expanding the technology’s impact and creating new opportunities for growth. The discussion highlighted how treating AI agents as digital employees demands new management models, robust change management, and authentic, transparent dialogue with the workforce. The human-technology interface must be designed for genuine collaboration, and that resistance to change is often the deepest among middle managers facing shifting incentives. Ultimately, the session concluded that blending AI and human strengths in customer service and beyond holds tremendous promise for future job growth and innovation.
Key takeaways:
AI adoption should focus on expanding impact beyond cost savings. AI’s true value lies in creating new opportunities and enhancing organizational capabilities.
Treating AI as digital employees requires significant organizational changes. More and more, AI models will be treated like employees, necessitating changes in organizational structures and roles, as well as consideration of how AI can best be integrated into existing workflows.
Human-technology collaboration is crucial for successful AI deployment. It is critical to design interfaces that facilitate effective collaboration between humans and AI systems.
Memorable quotes:
"The winners in the AI adoption race will be divided by how they handle human leadership and organizational dynamics issues, not by how good they are at adopting the fastest model." Nathaniel Whittemore
"I believe we will explode on the other side of this technological revolution with tremendous job growth. I know agents sort of call that into question, but the construct of transparency and authenticity and engaging employees’ voices in their own transformation will pay dividends." Steve Chase
"What we're trying to do is adjust the human interaction, because this all breaks if the remaining humans in the loop don't interact with agents in the way that we expected them to.” Bryan Ackermann
"With AI, you get to pick all three: faster, better, cheaper. And when we manage our business, we have a much fuller understanding of how end-to-end business flows." Steve Holden
How to move forward:
Develop strategies that prioritize human-technology collaboration, including managing AI models more like employees.
Approach change management with transparent communication from leadership and opportunities for employees to feel their voices are being heard.
Account for the fact that there will be global variations in AI adoption, which means local contexts need to be considered.
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Summary:
Led by KPMG’s Chad Seiler, leading board members and technology experts explored how boards of directors can balance the excitement of AI innovation with the realities of risk management and effective leadership. They emphasized the need for agility, experimentation, and bold strategy—urging boards to refresh their vision and support CEOs who embrace the AI revolution. Including tech-savvy voices was highlighted as key to staying competitive. The panel stressed that boards must champion purposeful, ethical use of AI and support organizational restructuring to remain ahead.
Key takeaways:
Board members must balance the excitement of AI innovation with practical risk management. While some teams are struggling to keep up, they need to be open to AI without getting distracted by it.
Companies must be agile and intentional in their AI strategies to stay competitive. Many companies are missing the bigger picture when it comes to AI and need to refresh their strategies.
Proactive understanding and experimentation with AI are crucial for effective guidance. Board members need to get hands-on with AI technology and embrace experimentation over perfection.
The right leadership is essential for navigating the AI revolution. It is critical to have the right CEO to lead the company throughout the AI era, although it can be challenging to convince CEOs in highly regulated industries to embrace AI.
Memorable quotes:
"It couldn't be more exciting to be a board member right now, and there's so much to think about and so much to be on top of." Chad Seiler
“It is important for leaders to be open to change and not let fear hold them back.” Carine Clark
“Boards should focus on how to help companies play to win rather than just avoid losing." Chris Fralic
“The question is, do we have the right CEO to lead us, not just today, but into the future. Helping management teams see their way while they deliver today and dream for tomorrow is one of the biggest challenges we have." Tami Irwin
“A lot of companies are missing the bigger picture when it comes to AI. It’s important to have a strategy refresh, and board members should consider what to do if the enemy is out there building a new company to do what we do today.” Toby Redshaw
How to move forward:
Build a culture of experimentation and agility while ensuring you have the right leadership and talent in place to navigate the AI revolution.
Be proactive in understanding and experimenting with AI.
Challenge the status quo and take responsibility for remaining relevant.
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Summary:
Phil Isom of KPMG moderated a panel that explored how AI is reshaping venture capital, with rapid innovation and new investment challenges. The discussion highlighted the urgent need for radical collaboration between startups and enterprises and emphasized the importance of trust and data governance in AI adoption. The panel stressed that the entire IT stack is being remade, which is creating opportunities for startups to disrupt traditional industries. These startups are expanding into previously ignored verticals, such as legal tech and home services, due to the potential of AI to create significant value. Finally, as the IT landscape transforms, investors are looking for founders with vision, charisma, and technical depth.
Key takeaways:
The venture capital landscape is evolving rapidly with AI. The pace of technological change is making investment horizons more challenging, with an influx of capital from IPOs and a growing focus on AI-driven solutions.
Radical collaboration between startups and enterprises is becoming essential. Startups that work closely with large enterprises can engineer products that are purpose-built for their needs.
Trust and data governance are critical for AI adoption. It is critical to build trust with customers regarding AI solutions, although data governance and security are significant hurdles for AI deployment in large corporations.
Memorable quotes:
"With AI in particular, you have to demonstrate to people that an agent does what you think it's going to do consistently.” Michael Dauber
"I think we're entering an age of more radical collaboration between startups and between enterprises.” James Higa
"Being a design partner with an early-stage company is a best practice because you can help engineer a product to be more purpose-built for you." Gamiel Gran
"As fast as it has been going on this last year, it's about to get a lot worse.” Lee Haney
How to move forward:
Endeavor to build strategic partnerships between startups and enterprises.
Leverage AI-driven innovations while addressing critical issues such as trust, data governance, and security.
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Summary:
JJ Malfettone of KPMG led a panel on how AI-native software is reshaping business operations, with products built on AI from inception, not retrofitted. The discussion focused on rapid prototyping, the rise of outcome-based pricing, the importance of human-in-the-loop design for enterprise trust, and seamless integration with legacy workflows. AI is upending traditional scaling models, enabling companies to boost revenue and productivity with leaner teams, while embedding service components to accelerate customer adoption.
Key takeaways:
AI-native products are transforming business operations: AI-native software is revolutionizing how businesses approach product development, making it faster and more efficient.
Outcome-based pricing is gaining traction: Traditional pricing models are being reconsidered in favor of outcome-based and usage-based pricing.
Human-in-the-loop design is crucial: Enterprises are cautious about fully autonomous AI systems, preferring designs that incorporate human oversight.
Integration capabilities are key to success: Despite the innovation brought by AI, practical integration with existing legacy systems remains crucial for market success.
Memorable quotes:
"You build a product on AI as your backbone. It's not something you're plugging into." Matty Beckerman
"We have embraced the concepts of both usage- and outcome-based pricing. Customers want to pay for outcomes. This approach helps in building trust and demonstrating the tangible benefits of AI solutions.” Rohit Gupta
"While everyone is trying to build the next shiny object, the enterprise architecture is still a legacy that hasn't changed. If your product does not integrate well with the workflows, you're not getting off the ground." Amit Patel
“From a contract perspective, you need to make sure customers can do an apples-to-apples comparison because they may not know the complexities of token use and all of that." Tushar Shah
How to move forward:
Prioritize developing AI-native products that incorporate human-in-the-loop design patterns and outcome-based pricing models.
Ensure seamless integration with existing enterprise systems.
Explore new business models that capitalize on the productivity and efficiency gains offered by AI.
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2025 Tech and Innovation Symposium
event highlights
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Rewiring the Enterprise
Cliff Justice, National Leader of Enterprise Innovation, KPMG US
The Geopolitical Landscape
Cliff Justice, National Leader of Enterprise Innovation, KPMG US
Gina Raimondo, former US Secretary of Commerce and Governor of Rhode Island
Reframing the Climate Debate
Steve Koonin, Senior Fellow, Stanford University and Hoover Institute; former Undersecretary for Science at the US Department of Energy
From Content to Context: The Rise of Agentic AI in the Enterprise
May Habib, CEO and co-founder of Writer
Lauren Boyman, Chief Marketing Officer and Principle, KPMG
Powering AI with Nuclear
Jacob DeWitte, CEO of Oklo
Adapting at Scale Through the Lens of a Tech Pioneer
Phil Wiser, Executive Vice President and Chief Technology Officer, Paramount
Richard Entrup, Head of Emerging Solutions at KPMG
Unpacking the "KPMG 2025 Futures Report"
Stephanie Kim, Executive Director, Enterprise Innovation, KPMG
Reframing Frontiers of Innovation
Peter Diamandis, co-founder of BOLD Capital Partners, cofounder and Vice Chairman of Celularity, and the executive founder of Singularity University
Future of SaaS
Todd Lohr, National Managing Principal for Clients and Markets, KPMG
Vibe Coding
Jerry Liu, co-founder and CEO of LlamaIndex Swami Chandrasekaran, Global Head of AI & Data Labs, KPMG
Navigating the Energy Crossroads: Innovation, Risk, and Reinvention
Mark Lashier, CEO and Chairman, Phillips 66
Cliff Justice, National Leader of Enterprise Innovation, KPMG US
What's Next in Quantum
Scott Crowder, VP, Quantum Leader, IBM
From Investment to Inference in an Instant
Chris Stephens, VP and Field CTO, Groq
Global Head and US Vice Chair
Artificial Intelligence and
Digital Innovation,
KPMG US
Steve
Chase
AI Adoption, Agents, and AGI/ASI
Chad Seiler, Consulting Industry Leader for Technology, Media and Telecommunications, KPMG
Yvette Kanouff, Partner, JC2 Ventures
Sharon Zhou, VP of AI, AMD
Navigating Digital Assets
Greg Genega, Audit/Digital Assets Leader, KPMG
Anthony Tuths, Senior Partner, Asset Management Tax, KPMG
Trevor Traina, Chief Business Officer, Tools for Humanity
Scott Stornetta, Chairman/Founder, SureMark Digital
Jody Mettler, President, BitGo Trust
The Year in Review
Jason Calacanis, Investor, Host of All-In Podcast
The Future of Everything
Jason Calacanis, Investor, Host of All-In Podcast
Peter Diamandis, co-founder of BOLD Capital Partners, cofounder and Vice Chairman of Celularity, and the executive founder of Singularity University
Ted Shelton, AI strategist and author of Infinite Future
Salim Ismail, Co-founder and Chairman, OpenExO
AI Goverance in the Agentic Era
Kelly Combs, Managing Director, US Trusted AI Dev. and Deployment Leader, KPMG
Jonathan Dambrot, CEO and co-founder of Cranium AI
Innovation and Trends in Advanced Manufacturing
Claudia Saran, U.S. Sector Leader, Industrial Manufacturing, KPMG
Lerrel Pinto, Co-Founder, Stealth Robotics Company
Ethan Karp, President & CEO, MAGNET
Open and Sustainable Compute for the AI Era
Mark Papermaster, CTO & EVP, AMD
Engineering the Quantum Future: Microsoft's Approach
Zulfi Alam, Corporate Vice President of Quantum, Microsoft
The Space Economy
Brian Miske, Americas Space Lead & US Ignition Leader, KPMG
Kylie Ho, Senior Director of Strategy, Blue Origin
AI at the Edge
Scott Lawrence, SVP & Chief Product Officer, Verizon Business
Takeaway 1: X.
Xx
Takeaway 2: X.
Xx
Cozy Cooking with AI
John Maeda, VP Engineering, Head of Computational Design/AI Platform, Microsoft
Cutting Through the Clutter
Nathaniel Whittemore, Host, The AI Daily Brief
Realities of Enterprise AI Deployment
Nathaniel Whittemore, Host, The AI Daily Brief
Steve Chase, Global Head & US Vice Chair of AI & Digital Innovation, KPMG
Bryan Ackermann, Head of AI Strategy & Transformation, Korn Ferry
Steve Holden, SVP & Head of Single Family Analytics, Fannie Mae
Boardroom to Breakthrough: Navigating Innovation at the Top
Chad Seiler, U.S. Consulting Industry Leader for Technology, Media and Telecommunications, KPMG
Carine Clark, CEO, First Colony Mortgage; Board member, Nelnet Bank and MX
Tami Irwin, Former CEO of Verizon Business; Board member, John Deere
Chris Fralic, Board Partner at First Round Capital
Toby Redshaw, President/CEO, Verus Advisory; Board member, VANTIQ
Navigating the Innovation Economy: VC Perspectives
Phil Isom, Global Head of M&A, KPMG
Lee Haney, Partner, Greylock
James Higa, Founder & Managing Partner, Offline Ventures
Gamiel Gran, Chief Business Officer, Mayfield
Michael Dauber, General Partner, Amplify Partners
Building and Scaling AI-Native Products
JJ Malfettone, Senior Director, KPMG Ventures
Matty Beckerman, Founder and CEO, IRCODE
Rohit Gupta, Founder and CEO, Auditoria.AI
Amit Patel, Partner, Plug and Play Tech Center
Tushar Shah, Chief Product Officer, Unifore
AI and IP - A Legal Perspective
Professor Christa Laser, Tenured Professor of Intellectual Property Law and Innovation at Cleveland State University College of Law
The Road to Superintelligence
Ted Shelton, AI Strategist, Inflection AI
The Geopolitical Landscape
Stephanie Kim, KPMG
Jacob DeWitte, Oklo
Steve Koonin,
Hoover Institution
Mary Habib, WRITER
Cliff Justice, KPMG
Sharon Zhou, AMD and Yvette Kanouff, JC2 Ventures
Phil Wiser, Paramount
Peter Diamandis
Oracle, Workday, ServiceNow, Salesforce
Jerry Liu, LlamaIndex and Swami Chandrasekaran, KPMG
Mark Lashier, Phillips 66
Scott Crowder, IBM
Tools for Humanity, SureMark Digital, BitGo Trust
Jason Calacanis,
All in Podcast
Ted Shelton, Infinite Future
Chris Stevens, Groq
Jason Calacanis, Salim Ismail, Peter Diamandis, Ted Shelton
Jonathan Dambrot, Cranium
Lerrel Pinto, NYU and Dr. Ethan Krap, MAGNET
Mark Papermaster, AMD
Zulfi Alam, Microsoft
Kylie Ho, Blue Origin
Scott Lawrence, Verizon
John Maeda, Microsoft
Nathaniel Whittemore,
AI Daily Brief
Nathaniel Whittemore, Korn Ferry, Fannie Mae, KPMG
Carine Clark, Tammi Erwin. Chris Fralic, Toby Redshaw
Greylock, Offline Ventures, Mayfield, Amplify Partners
IRCODE, Auditoria.ai, Plug and Play, Unifore
Christa Laser, Cleveland State University