Deer Valley, Utah | August 5–7, 2024
2024 KPMG
Tech and Innovation Symposium
Six key insights finance leaders can use to shape their
action plans.
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Session recaps
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.
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Office Managing Partner
New England & Upstate New York,
KPMG US
John
Capone
Advisory Market Leader Principal
New England & Upstate New York, KPMG US
Femi
Obi
Principal
Strategic Planning and Investments,
KPMG US
Kevin
Bolen
Generative AI
See event highlights in this
3-minute video
GenAI was utilized in the creation of this image.
Managing Director and Head of Emerging Solutions
Enterprise Innovation, KPMG US
Richard Entrup
Principal
Technology Enablement & Automation,
KPMG US
Todd
Lohr
National Leader Enterprise Innovation
Enterprise Innovation, KPMG US
Cliff
Justice
We featured 50+ distinguished speakers across 22 sessions and 9 in-depth talks exploring some of today’s most pressing challenges and opportunities. Across the formal and informal discussions, four themes emerged:
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 2024 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 2025. 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
Vice Chair
Artificial Intelligence & Digital Innovation,
KPMG US
Steve
Chase
What’s Coming: Quantum Computing
Space Economy: Galaxy of Opportunities
Spatial Computing & Immersive Experiences
Tech Talk:
Apple Vision Pro
The Future of Sound
How to be Bold, Fast, Responsible on your Trusted AI journey
Decentralization and Proof of Personhood
Sustainability, Scalability, and AI at the Edge
In Conversation with LinkedIn Chief Economic Opportunity Officer, Aneesh Raman
Tech Talk: Enterprise LLM Strategy
Unleashing the Beast: How Optimized Compute is Revolutionizing AI
Reverberation: Your Musical Brain on Business
The Future of Enterprise Innovation: Harnessing the Power of Startups and New Technologies
An Alternative Paradigm: Democratizing the AI Innovation Landscape
The Board Director's Agenda
Economic Resilience in the Age of Technological Disruption
Transforming the Enterprise with AI: Strategic Advice from the Front Lines
Solving the Innovator's Dilemma
Video recap series Click to view recap video series
Indicates video recap available
Space Economy: Galaxy of Opportunities
Speakers: Zaheer Ali, Co-Founder and COO, Positon AI, and Professor, Thunderbird School of Global Management
Brian Miske, Principal, Growth & Strategy, KPMG
Takeaway 1: The space economy is expanding quickly in size and capabilities.
Miske noted that in 2021, multiple investment banks targeted the space economy to be about $1 trillion by 2040. In April 2024, the World Economic Forum (WEF) came out with a new report targeting $1.8 trillion—an 80% increase in just three years. What’s more, the WEF predicted the space market will reach that size by 2035.
He encouraged people to consider the space economy versus the space sector: "The economy is how we leverage all of those assets, data, and other elements and space-based assets for increased value across a multitude of different sectors." As an example, Ali pointed to new streams of data: "Twenty-five years ago, commercial companies didn’t have access to SAR (Synthetic Aperture Radar) and other types of data that would create a digital twin of any city on the planet to a 30-centimeter resolution. Just think about that for a second. This is unprecedented."
Takeaway 2: Data fusion is key to unlocking the potential of the space economy.
Data fusion, the process of integrating multiple data sources to produce more consistent, accurate, and useful information, is not a new concept. However, with the advent of space data, there is a renewed emphasis on its importance. The speakers discussed the transformative potential of fusing space data with other datasets, highlighting the role of AI in making sense of complex, multi-dimensional data. As Ali explained, “We now have a tool—GenAI—that can really help us leverage this in a way we’ve never done before.” Reflecting on the role of data fusion, Miske pointed out that it’s not just about the technology—it’s how can we look at data in very different ways to pull it apart.
Takeaway 3: Take advantage of data fusion—or risk being left behind.
Ali emphasized the importance of embracing data fusion: “Those companies that take advantage of it [and] those governments that take advantage of it are going to have a very sizable advantage—and those that don’t are going to be left behind.” Miske concurred, pointing out that organizations need to be agile and adaptive to a changing marketplace. Using data from space, they can be prepared to unearth unique opportunities and challenges using data.
Two potential applications of space-sourced data are predicting earthquakes and monitoring mining sites, both of which could provide significant operational and strategic benefits for companies. As Ali noted, “There were companies that moved assets well before the borders were crossed in Ukraine. How did they do that? They were leveraging data—commercial data from space—and they secured themselves, their position, got their people out of the way, (with) no tip-off from the government."
Further, he said, "Every company is going to either be touched by space, moved by space, or be a more than just terrestrial company moving forward. And if they don’t, they’re going to die."
Spatial Computing & Immersive Experiences
Moderator: Richard Entrup, Managing Director, Head of Emerging Solutions, Enterprise Innovation, KPMG LLP
Panelists: Joanna Popper, Executive Producer & Entertainment Executive
Josh Rush, Co-Founder and CEO, SURREAL Events
Ted Schilowitz, Futurist, Cinemmersion, Inc.
Takeaway 1: Spatial computing holds immense potential for enterprises.
Spatial computing and immersive experiences, particularly with the advent of Apple’s Vision Pro product, are poised for enterprise impact. Traditionally associated with gaming, these technologies are now finding applications across retail, manufacturing, real estate, healthcare, education, logistics, and financial services.
"There are real jobs to be done, real business outcomes that can be had from this technology," Entrup said. Rush echoed the sentiment, detailing the development of his company’s spatial computing platform to create hyper-realistic web-based experiences for brands, clients, and partners.
Takeaway 2: Integrating AI and spatial computing broadens possibilities.
The integration of AI and spatial computing is seen as a game-changer, with the potential to significantly lower the costs and complexities associated with content creation in a 3D environment. This convergence is expected to democratize access to these technologies and unlock new opportunities for creativity and innovation. As Popper explained, GenAI makes it easier to generate the world, environment, and content for immersive experiences: “When you have generative AI, it makes that a lot easier, more affordable—which has been, in some cases, a barrier for adoption.” Rush emphasized the role of AI in enhancing training scenarios, explaining that with GenAI, you can go in through prompting and create new training scenarios. “This is one of the hard things: How do we create 1,000 different modules that might only need to be a few minutes long each—but do that at scale?” GenAI is unlocking new possibilities.
Takeaway 3: Enterprises still face barriers to widespread adoption.
Rush acknowledged that when working on projects with large enterprises, just setting up authentication can take a significant amount of time. Popper also noted that enterprises want bundled solutions—not individual hardware and software products. Schilowitz referred back to adoption of touchscreen mobile phones, which required a pivot from IT departments that had just mastered management of BlackBerry devices. He suggested that what’s needed is a clear value case—with enough difference between 2D and spatial computing to justify the latter.
Watch the video from this session here
Tech Talk: Apple Vision Pro
Mike Benza, Director, Enterprise Sales & Business Development, Apple
Takeaway 1: Spatial computing has transformative potential in the enterprise.
Benza highlighted how spatial computing is ushering in a new era by overlaying digital content in physical spaces. That has significant implications in various business sectors. This technology can support infinite canvas apps for work, unlocking more collaborative design, more effective training and simulation, and more efficient guided work. Benza invited attendees to imagine spatial computing in the workplace: “At your desk, you don't have a monitor. You don’t have a keyboard. You’re going to have virtual everything in front of you—and you can have all your applications open.” He also noted the added layer of security spatial computing brings: “Nobody can see over my shoulder, and with optic ID, unless somebody literally has [a] biometric scan of my iris, nobody’s going to be able to authenticate as me.”
Takeaway 2: Collaborative design is revolutionizing product design and development.
Benza discussed the impact of spatial computing on collaborative design. He spoke about how it enables faster iterations and more efficient approvals. He mentioned how companies are using the technology to accelerate feedback cycles and to engage customers even before physical products are available for their review.
Takeaway 3: Spatial computing can reshape training and simulation.
Benza highlighted the significant interest in the training and simulation areas of spatial computing, citing the increased training capacity and reduced training cost as major benefits. He shared examples of companies that are using Apple Vision Pro technology to drastically improve learning while increasing training capacity and reducing overall costs.
The Future of Sound
Jessica Powell, Co-Founder and CEO, AudioShake
Takeaway 1: AI technology can separate sound for more interactive, accessible audio.
Powell spoke about AudioShake’s innovative application of AI technology to audio and sound. Its technology uses AI to separate and extract different layers of sound (also known as stems) to make audio more interactive, editable, and accessible. “Sound is all around us, but we don’t really pay much attention to it until it breaks for us,” she explained. “But if you think about making audio more interactive and customizable—or being able to get different kinds of information that’s within audio—we’re still pretty early in all of this.”
Takeaway 2: Multiple industries can benefit from more accessible and valuable audio data.
Powell highlighted the numerous applications of AI-based sound separation technology in various industries, including entertainment, sports, manufacturing, and healthcare. By allowing for more granular editing and improved audio quality, this technology is unlocking new possibilities and making audio data more accessible and valuable. "We work with all the major label groups, most of the large film studios in the U.S., lots of little sports leagues and sports teams," she said. She also mentioned the technology’s potential in hospital environments and manufacturing facilities, where background noise often obscures important audio information.
Takeaway 3: AI opens the door to real-time audio editing and sound localization.
Powell discussed the exciting potential of real-time applications of AudioShake’s technology. Whether enhancing sound quality at a live concert or improving audio experience for viewers watching a streamed event, AI can be used in numerous ways to edit and enhance sound experiences in real time. She predicted that it won’t be long until we’re able to use AI tools to not only generate but also edit and adjust sound in real-time. She also highlighted the potential for real-time applications in accessibility, such as boosting and suppressing certain sounds in hearing aids to assist those with hearing difficulties.
Watch the video from this session here
How to Be Bold, Fast, and Responsible on Your Trusted AI Journey
Moderator: Bryan McGowan, US Trusted AI Leader, KPMG US
Panelists: Dr. Misty Blowers, CEO, Datalytica
Josh Gwyther, Head of AI Solutions Architecture, Google
Michael Park, SVP and Global Head of AI GTM, ServiceNow
Manoj Saxena, Founder, CEO & Chairman, TrustWise
Takeaway 1: Trust is fundamental to AI development and deployment.
Panelists explored the importance of establishing a layer of trust during the development and implementation of AI. Park emphasized that AI should be viewed as an enabler to an outcome rather than a standalone solution. He also asserted that trust should be designed into the platform from the beginning: "We design trust from the inside, in the platform itself, and the platform persists to every workflow that's stood up." Gwyther discussed the importance of due diligence in training data and ensuring data protection: “All the things we’ve been talking about—where is this data shared? Is it private? Where does it go?—we don’t even start a design phase until you get past the legal hurdles for identification.”
Saxena agreed that establishing that layer of trust is critical, both upfront and throughout the AI lifecycle, adding “I think responsible AI is profitable AI—and without that, you’re not going to get it.”
Takeaway 2: AI systems require rigorous testing and red teaming for security.
Blowers spoke about the importance of testing and red teaming (that is, proactively testing AI system security to identify vulnerabilities, weaknesses, and potential risks). She pointed out that effective guardrails would vary for different AI systems and underscored the need for rigorous testing: "For a given application, an AI system needs to be tested and red teamed to make sure that it’s going to operate as intended in the environment in which you're going to place it."
Takeaway 3: Be aware of differences in how startups and large enterprises approach AI adoption.
The panelists noted a stark contrast between startups and large enterprises in terms of their approach to AI adoption. As Park put it, "Enterprises are scale and startups are speed. I think the biggest difference is when I’m working with a startup, they’re willing to take huge risks for speed… Whereas the incumbents, the Fortune 500, is the exact opposite. They don’t want to take any risk, if possible, in implementing this."
Watch the video from this session here
Decentralization and Proof of Personhood
Moderator: Richard Entrup, Managing Director, Head of Emerging Solutions, Enterprise Innovation, KPMG LLP
Panelists: Greg Genega, Manager, Digital Asset Management, KPMG US
Scott Stornetta, Partner, Yugen Partners, and Chairman, SureMark Digital
Trevor Traina, CEO and Founder, Kresus Labs
Takeaway 1: 2024 is shaping up to be a meaningful year for decentralized technologies.
Genega kicked off by suggesting that when looking back at the history of digital assets, 2024 will likely be viewed as the year blockchain digital assets grew into "adolescence." He mentioned the debut of nearly a dozen bitcoin spot ETFs as well as the House’s passage of the Financial Innovation and Technology for the 21st Century Act (FIT21), the first bipartisan legislation related to digital assets. These activities have occurred alongside increasing adoption across tokenization of real-world assets, global growth in payment stablecoins, and continuing evolution in the regulatory conversation.
Takeaway 2: There’s still a lot of untapped opportunity.
Genega explained that blockchains are global, Internet-native settlement layers, where you have ultimate assurances on the storage and transfer of digital assets. He and the other panelists see significant potential for blockchain technology to support real-world applications beyond cryptocurrency and non-fungible tokens (NFTs). The panelists also noted the need for better, safer tools that can’t be exploited by bots.
Stornetta mentioned the recent CrowdStrike attack and resulting outages—which did not affect any blockchain technologies: “If you’re looking for resiliency, I think the time is ripe for people to start thinking about the blockchain as not just supporting cryptocurrencies, but as a distributed ledger for the world that provides redundancy by its very nature. That, I think, is the undercurrent that the news media is not yet grasping.”
“Blockchain is just this profoundly elegant technology that underpins everything—that makes everything immutable and organized,” Traina said. “The blockchain continues to dazzle, and I think it is one of the most profoundly important things to happen… since the World Wide Web.” He argued that we have “barely scratched the surface” on blockchain’s value in immortalizing any contract or event.
Takeaway 3: Blockchain technology can help maintain or restore trust in key areas.
The panelists highlighted the potential of blockchain technology to restore trust in areas where confidence has been eroded, such as voting processes, and to ensure trust in developing areas, such as security for AI data and personal identity. Indeed, as technologies make it easier to spoof identities, the panelists all agreed that blockchain technology offers a solution to the issue of “proof of personhood”—that is, the ability to prove that someone is the unique human they claim to be.
Traina spoke about Worldcoin, the open-source protocol and cryptocurrency project aiming to create a global digital identity and financial network, as one example of progress on this front. For his part, Stornetta said, “A hundred years from now, individual people will still be the sources and sinks of economic activity. But how we get there—making sure that the uniqueness of the individual is preserved through this transition—it’s going to be a lot of fun, and it’s something that I think people should focus on sooner rather than later.”
Watch the video from this session here
Sustainability, Scalability, and AI at the Edge
Moderator: Todd Lohr, US Head of Technology Consulting, KPMG LLP
Panelists: Noel Kenehan, Lead, AI Center of Excellence, Google Cloud
Aparna Prabhakar, Senior Vice President, Strategy and Sustainability, Secure Power & Data Center, Schneider Electric
Sharon Zhou, CEO, Lamini AI
Takeaway 1: Power-hungry AI is fueling demand for energy.
Panelists all acknowledged increasing energy demand as AI continues to scale, with a major focus on finding energy-efficient solutions. Prabhakar stressed the importance of considering energy availability as part of the total cost of ownership (TCO) of AI systems: "It’s a good time to actually go and say, do I want to upgrade my micro data center? Do I want to think about more efficient infrastructure?" She warned of a potential mismatch between data center builds and utility provisions, indicating power availability as a major concern for the future of AI.
Takeaway 2: Open-source models and fine-tuning have roles in AI efficiency.
The panelists touched on the potential of open-source models and fine-tuning techniques to improve the efficiency of AI systems. Noting that larger models are particularly power hungry, Zhou advocated for the use of "mixture of experts" models: "If you edit it with so much of your own data over time, which is small investments over time, you can get a model that is 400 billion parameters large, but it is at the cost, latency, speed, and efficiency of a tiny 8 billion-parameter model."
Zhou also explained, "We work with teams to take those big models and to adjust them so that they don’t hallucinate on proprietary data. And to do that process is actually very cheap and fast." Kenehan agreed with the importance of fine-tuning existing models rather than building new ones from scratch.
Takeaway 3: We need to balance AI’s power demands with growth and innovation.
Zhou commented on the impact of scaling laws on AI’s power consumption: "Compute plus data equals intelligence. And what scaling laws state is that if you pour more data and you pour more compute, you’re going to get more intelligence out." That has led to tension between AI’s increasing power demands and the need for growth and innovation.
Panelists emphasized the role of new technologies and strategies in achieving that balance. For example, Kenehan mentioned his company’s efforts to make data centers as sustainable and ecologically friendly as possible, including reducing the CO2 impact of operations. He also highlighted the importance of selecting the best, most power-efficient chips. Meanwhile, Prabhakar pointed out the demands that digital growth puts on the grid, highlighting the need for innovation in software, application, and infrastructure levels to achieve sustainability goals. She stressed that sustainability should not be an afterthought.
Watch the video from this session here
In Conversation with LinkedIn Chief Economic Opportunity Officer, Aneesh Raman
Speakers: Anu Puvvada, Partner, KPMG Studio Leader, KPMG US
Aneesh Raman, Chief Economic Opportunity Officer, LinkedIn
Takeaway 1: The future of work lies in tasks (not titles).
Raman emphasized the importance of looking beyond job titles as AI and other rapid technological advancements change the nature of work. In the future, jobs will be defined by the tasks that AI is going to perform; the tasks that humans will perform with AI; and the tasks that will remain unique to humans.
"Jobs are not titles. Jobs are tasks," he explained. "Everyone in this room right now can pretend you have no idea what your job title is, or that it is irrelevant in terms of defining who you are or what you do. You can then pretty quickly say, 'What are the top dozen tasks that I do every day?' Once you do that, if you realize you’re heavily in the first category [i.e., tasks AI is going to do], it’s time to upskill."
Takeaway 2: We’re moving toward a relationship economy.
Raman posed a question: “What can I predict will not change based on the past tens of thousands of years of humans at work?” He pointed to storytelling as a uniquely human skill—and underscored the significance of curiosity, compassion, and creativity when navigating the future of work. Despite advances in AI, these distinctly human traits remain irreplaceable and will become even more valuable. Indeed, the future of work will prioritize people skills and collaboration, moving toward a relationship economy.
Takeaway 3: We need to reimagine education and learning.
The conversation also touched on the need for educational institutions, learning companies, and corporations to evolve to meet the demands of an AI-driven future. The current status quo around learning is broken and needs to be reimagined to embrace the limitless potential of humans.
"Learning is something that for most people, they want to do and be done with," Raman said. But with the imminent changes brought about by AI, he emphasized that it would be critical to bridge this gap and realign learning with curiosity.
"We will have to reassign curiosity to learning for the sake of businesses doing well and people doing well," he noted.
In the end, he said, “Talent—not tech—is how companies are going to win.”
Watch the video from this session here
Enterprise LLM Strategy, Present Trends Across Industries and the Future
Sharon Zhou, CEO, Lamini AI
Takeaway 1: Enterprise use of large language models (LLMs) has significantly progressed, unlocking high-value use cases.
Zhou asserted that businesses are now past the exploratory phase with LLMs and are successfully implementing them in production. ("Finally, my parents knew what I worked on!" she joked.) "This year, I’ve seen a lot of folks actually ship things into production," she said. "Now, are they always the deepest use cases that drive top-line revenue? Not really, not all the time… but they are in production." She also predicted that these applications would become more complex and industry-specific, leading to cost reductions and potential new product lines.
Takeaway 2: Memory tuning can effectively address inaccuracies or "hallucinations."
Zhou discussed inaccurate outputs as one of the main obstacles to LLM adoption in businesses: "What has blocked those use cases previously? I think the number-one blocker that I see across companies is hallucinations in these models." She proposed memory tuning as a solution. She noted that memory tuning not only improves the accuracy of LLMs but also makes them smaller, cheaper, and faster, unlocking a new set of use cases.
Takeaway 3: Get great at building cross-functional teams.
Zhou stressed the importance of cross-functional teams in successfully implementing LLMs in businesses. She asserted that because LLMs are hard to evaluate, developers need to work closely with end users or subject-matter experts to ensure the effectiveness of their models. In her view, the ability to build cross-functional teams is a significant differentiator among companies aiming to adopt LLMs: "They need the people who are end users to somehow sit closely or at least collaborate well with the people developing this technology."
Watch the video from this session here
Unleashing the Beast: How Optimized Compute is Revolutionizing AI
Mark Heaps, SVP, Brand & Creative, Groq
Takeaway 1: Groq technology makes AI compute faster and more affordable.
Heaps demonstrated Groq’s innovative solution, which provides fast, efficient computation for AI applications by using language models to generate text in real-time. The key to this innovative solution lies in Groq’s language processing unit (LPU), a chip designed specifically for processing language data. The LPU chip, along with the larger Groq system, offers a scalable solution that can handle increasingly complex AI applications.
"When you network all of the LPUs together at thousands-of-chip scale, the system actually thinks it’s one chip," he explained. "So you’re just multiplying transistors and SRAM (Static Random Access Memory), and because of the linear nature of this, we can process those tokens unbelievably fast."
Takeaway 2: Groq's technology has real-world applications.
Heaps demonstrated how Groq’s technology could be used to rapidly generate a book on mindfulness for kids: "We're going to have a fluid and fluent conversation with our devices to try to drive this language interface," he said. Heaps also shared a personal story about how he used Groq to find emergency medical advice when his son was stung by a lionfish.
"When people talk about changing the world with AI, you don’t have to think of this magnanimous scale," he explained. "You think about all the micro steps you take to actually have an impact and actually have an influence."
Takeaway 3: Groq aims to bring the cost of compute to zero.
"About four months ago, we gave the world access to Groq technology via our GroqCloud completely for free," Heaps said. "Today, you can not only go use that chat, but you can dive into our developer console, get your own API keys, and start building applications yourself right now."
Heaps also mentioned a recent Series D fundraising round of $640 million, with plans to roll out 108,000 LPUs in AI inference compute centers. He emphasized the company’s commitment to manufacturing in North America, reducing any geopolitical risks: "We’re completely designed, engineered, and fabricated in North America, so we have none of the risks that are going on in various parts of the world today."
Watch the video from this session here
Reverberation: Your Musical Brain on Business
Speakers: Terry Stuart, Chief Innovation Officer, Reverberation LLC
Dr. Indre Viskontas, Cognitive Neuroscientist, Science Communicator and Opera Stage Director, University of San Francisco
Takeaway 1: Using music strategically at work can enhance productivity, creativity, and social bonding.
Stuart and Viskontas shared insights about the benefits of using music in the workplace. They emphasized that music can be a powerful tool for enhancing productivity, building social bonds, and fostering creativity. Via a video message, Reverberation Co-Founder Peter Gabriel shared, "Scientists have shown us that using music at work can play many different roles to make us better at what we do. For example, music seems to have the power to spawn creativity, to connect us better to co-workers, to clients.
Takeaway 2: Music can help bridge the gap between the arts and the sciences.
Reverberation delved into the intersection of music, neuroscience, and cognitive performance. The speakers highlighted how integrating music into education and business settings could bridge the gap between the arts and the sciences, improving cognitive functions.
“One of the things that we’re trying to break down is this notion of, ‘your kids go through school, and they either go into the tech and the science side, or they go into the arts,’” Stuart said. “And what we now know with the neuroscience is, if you actually have science and you’re using music—whether it’s learning an instrument, singing in a choir, or any of those kinds of things—you’re actually lighting up more parts of your brain.”
Viskontas echoed this, noting that there is value in learning to play an instrument—even if you’re playing badly: “It can teach your brain to strategically switch between which network is in control of your thinking, whether it’s executive control or this mind-wandering network,” she said.
Takeaway 3: Music can be used as a strategic tool beyond leisure and entertainment.
The Reverberation team explored the idea of music as a strategic tool, not just for leisure and entertainment, but with a specific purpose in mind, such as enhancing physical fitness, reducing stress, improving sleep, and even fostering creativity. As Viskontas explained, "Music is a multimodal cuing superpower."
Watch the video from this session here
The Future of Enterprise Innovation: Harnessing the Power of Startups and New Technologies
Moderator: Andrew Matuszak
Panelists: Nick Adams, Managing Partner and Co-Founder, Differential Ventures
Adam Branch, CEO, Rhino.ai & Incentive Technology Group
Gamiel Gran, Chief Commercial Officer, Enterprise GenAI, Mayfield Fund
Karen Wang, Principal Investor, Deutsche Bank Venture Capital
Takeaway 1: Large organizations can leverage early-stage startups to drive innovation
Panelists discussed the potential of early-stage startups (particularly in AI) to be harnessed by larger organizations in their pursuit of innovation. They emphasized that startups often bring a unique perspective and cutting-edge technologies that can significantly benefit large organizations.
Adams said that his organization is looking for startups that can help solve problems related to manual, repetitive processes, labor shortages, and margin compression from competitors: "We are very much early-stage investors. We’re usually the first institutional money into a company."
Branch highlighted the importance of clearly setting and meeting expectations when startups collaborate with larger organizations.
"Honesty is obviously key; you have to be honest both with yourself and with the folks you’re working with," he added.
Matuszak noted "the importance of setting clear expectations and realistic expectations, establishing good communication between the parties, and probably most importantly, aligning on the strategic objectives of why you’re getting into this relationship to begin with."
Takeaway 2: Regulation plays a critical role when adopting emerging technologies.
Panelists acknowledged the critical role that regulation plays when adopting emerging technologies like AI. They noted that understanding and managing regulatory challenges is integral to the successful integration of these technologies into large organizations.
Wang pointed out the importance of considering regulatory aspects before investing in AI startups.
"As a bank, we are regulated entities, so regulation is super important to us," she said. She also mentioned that startups need to comply with standard policies and regulations to be able to work with large entities like banks.
Takeaway 3: There’s still a gap between hype and reality.
Panelists offered insights into what they see as the prospects and challenges in AI adoption. Gran expressed excitement about AI’s potential to remake industries and harkened back to cloud computing services in 2006: "Data centers got remade. We rethought the data layer… the security layer. We think AI has sort of the same grist, if you will, the same opportunity."
While there was an acknowledgment of the vast potential of AI to revolutionize various sectors, they also brought attention to areas where the hype has not yet matched reality.
Beyond that, Adams mentioned the energy grid and quantum computing as two examples: "Some of the tools, technology, and things we’re seeing in the energy and grid world are still ahead of what’s realistic in that environment."
Meanwhile, Wang pointed to the increasing importance of security in the age of AI—specifically noting the rise of deepfakes and synthetic texts, audios, and images as growing threats.
An Alternative Paradigm: Democratizing AI Innovation
Moderator: Kevin Bolen, Principal, Strategic Planning and Investments, KPMG US
Panelists: Anik Bose, Managing Partner, BGV Ventures, and Founder, Ethical AI Governance Group (EAIGG)
Olivia Gambelin, Author, AI Ethicist, and Founder, Ethical Intelligence
Tobias Yergin, Director of Product, Strategic Operation, Walmart
Takeaway 1: AI is not primarily a technical problem; it’s a people and process problem.
During the panel discussion, Gambelin emphasized the importance of considering the human impact at the outset of AI strategies. She described the common mistake of treating responsible AI and ethics as an afterthought: "Imagine… going through all the processes of creating an AI product, getting it ready to ship... and then there’s some guy saying, 'Hey, you did it wrong. Go back and fix it.'"
Gambelin suggested shifting ethics and values conversations into the design phases so these considerations are addressed from the start. She also cautioned against viewing AI and responsible AI as solely a technical problem to solve.
"When it comes to adoption or development of AI, the biggest levers of change and indicators for success are within the people and process layer," she noted.
Takeaway 2: Effective AI integration requires consideration of human-centric factors.
Yergin discussed the importance of considering the human element in integrating AI into workflows. He emphasized that end users are not programmers and stressed the significance of adaptability in AI tools to fit the learning capabilities of the user and the environment.
"What if you actually had the capability to have a microphone on that device that you’re interacting with, and you knew that the front end of a store was operating at 65 decibels?" he asked. "It should be a true multimodal experience, and it should be adaptive based on the person, their learning capabilities, the way that they learn, as well as the environment."
He also pointed out the potential security risks with each addition of new language capabilities, algorithms, and features—all of which present new attack vectors. He suggested that a potential solution could be new systems that catch bugs and security vulnerabilities as they occur in real-time.
Takeaway 3: AI has the potential to solve AND cause problems.
Bose discussed emerging startups that are using AI to solve the challenges that AI technology itself is generating, such as data quality and integration issues.
"The long pole in the tent is data cleansing," he noted. "A lot of the quality work is being done on the post-training data…. it’s all human in the loop, a way to address data quality in a much different way." He also mentioned opportunities for AI innovation in data integration: "If you look at unstructured data, you don’t have any frontend ETL pipelines. How are you going to manage this? We believe there’s going to be a lot of innovation in that layer with using AI to try and solve that."
The Board Director’s AI Agenda
Moderator: Par Edin, Board Committee Chair, Global Lead Partner, and Innovation leader for Deal Advisory & Strategy, KPMG
Panelists: Jonathan Brill, Business Futurist
Anna Catalano, Board Director, Governance Expert, Speaker, and Advisor
Takeaway 1: The pace of change in technology and AI is accelerating, necessitating an evolution in board governance and decision-making.
Panelists highlighted the need for board members to keep abreast of rapid technological advancements. Catalano said that’s true even for board directors like herself, who don’t have a technical background. Brill echoed this sentiment, stating that board members needed to "get on the ground" to see what’s happening in the world.
Catalano also discussed the need for boards to change their traditional structures and approaches, which have been used for 30 years. She added, "I also think the voices around the room need to change."
Brill stressed the importance of understanding historical risks and disruptions to be better prepared for future ones.
“We’re moving into a world of deharmonization,” he explained. “And that means that what’s more likely is that changes in the world—not changes in your market—will disrupt you.”
Takeaway 2: Board directors need to help in managing the narrative with investors.
Panelists agreed on the necessity of communicating effectively with investors, especially in periods of technological innovation and change.
"You need to be communicating on a regular basis, not just once a year or once a quarter," Catalano said. "As long as they understand what the story is, they will decide if this is the kind of company they want to invest in."
Brill cited examples from Hollywood to draw an analogy on how to make a story real and enticing for the audience: “There’s a lot of value in tying film narrative to your technology narrative. I've never seen a shift like AI or touchscreens happen without it happening [in a movie], too.”
Takeaway 3: Risk is about more than downside; also consider the risk of missed opportunities.
The panelists touched upon the idea of redefining risk—not just as potential negative outcomes, but also as missed opportunities for growth and innovation. Catalano stated, “I always get upset that risk is always talked about in the negative… there’s a huge part of missing what’s happening that’s considered a risk.”
Brill encouraged boards to think long-term and prepare for changes that could disrupt the company: "How do you innovate for disruption?" He also expressed concern about boards’ ability to adapt quickly enough to the pace of change, stating, "How did so many companies miss the change that happened quicker than they thought it would?"
Watch the video from this session here
Economic Resilience in the Age of Technological Disruption
Diane Swonk, Chief Economist, KPMG
Takeaway 1: While economists are increasingly confident about the role of AI in boosting productivity, benefits may not be fully realized until 2030.
Swonk highlighted the potential of GenAI, noting that while the technology is already influencing individual firms, the gap between innovation and commercialization remains. She acknowledged that AI has the potential to increase the productivity of the least productive workers, thus leveling income inequalities. But it will also change the nature of jobs and potentially create new ones. Swonk emphasized that the shift toward AI-powered productivity is not linear and suggested it may take until 2030 for the most significant effects to be felt.
“This sort of hybrid analysis is coming out—that every time we’ve had one of these kinds of waves, it’s also generated a whole new spectrum of jobs.”
Takeaway 2: The U.S. economy remains in an expansion phase despite many Americans feeling like the country is still in a recession.
Swonk shed light on the dissonance between economic data and public sentiment, explaining that high inflation rates and rising living costs have left many feeling financially strained even as the broader economy shows ongoing signs of growth. Swonk also pointed out that political polarization has led to differing perceptions of the economy.
"We all now view the economy through the lenses of our partisan affiliation. If it’s your party [in the White House], then you feel better about the economy."
Takeaway 3: The Federal Reserve is poised to respond to economic challenges; achieving a "soft landing" will be a complex process.
Swonk compared the Federal Reserve’s task to that of an Olympic athlete aiming for a perfect landing. She expressed confidence in the Fed’s ability to course-correct and prevent a full-blown recession but acknowledged that the journey would be rocky.
"A soft landing is what’s considered a very rare ‘gold medal’ in central banking," she said. “But they’re not easy. The Fed needs to step up to the challenge, and it needs to face its critics." She added that while the Fed might currently be feeling regret for not having cut rates sooner, it now has plenty of room to do so. She predicted that the Fed might cut rates by half a percent in September and by 1% by the end of the year.
“The good news is [the Fed] finally [has] a lot of room to cut rates to get there. They will. They can. The whole world is watching.”
Watch the video from this session here
Transforming the Enterprise with AI: Strategic Advice from the Front Lines
Moderator: Steve Chase, Vice Chair, Artificial Intelligence & Digital Innovation, KPMG US
Panelists: Linda Avery, Co-Founder, LiveFire AI
Una Fox, Chief Data & Analytics Officer, Aristocrat
Anju Gupta, Vice President, Data Science/AI/ML, Northwestern Mutual
Takeaway 1: Enterprises must manage the shift from experimental AI to deliberate application of AI.
Chase kicked off the discussion by noting, “If we’re not disrupting ourselves, someone’s going to come disrupt us—and we’ve got this opportunity to maximize AI right now.”
In light of that, panelists discussed the need to move from just "experimenting" with AI to implementing it intentionally for business advantage. Avery, a former Chief Data and Analytics Officer, mentioned the need for a “path to value” focusing on how to optimize the roadmap to drive ROI.
"There has to be a move toward deliberate application of AI," she said. "And I think we’re getting to a point where there’s impatience with all this experimentation."
Gupta added, "Don't look for ROI right away. It's going to take time, but we are confident it will happen."
Takeaway 2: Organizations must manage AI responsibly and ethically.
The panelists emphasized the need for a centralized function to ensure safe, responsible, and ethical deployment of AI solutions. Gupta highlighted the fundamental responsibility of leaders driving AI initiatives to ensure ethical deployment.
"Every large company [has] thousands of vendors, and every vendor, I can guarantee you, is adding an AI plugin," she noted. "We are essentially going after and looking at all the vendors and understanding what is on their roadmap." Gupta also pointed out that her team works closely with the enterprise architecture team to glean their view of every AI solution they are building.
Takeaway 3: The Chief Data Officer (CDO) and Chief Data and Analytics Officer (CDAO) are key to driving AI initiatives.
The role of CDOs and CDAOs in leading AI initiatives was another key point of discussion. Panelists highlighted the need for these roles to oversee the different technology strategies to create a coherent strategy. Avery argues that the core of the issue belongs to the CDAO, as it’s all about insights and how they get applied through technology and human intelligence.
"A year ago, I read about a survey where they interviewed boards of 100 large-cap and mid-cap firms, and only 50% of them had ever had AI on their agendas, and 40% of them had no idea whether or not their company had an AI strategy,” Avery said. Other panelists agreed that today, boards or CEOs no longer have a choice not to have AI on their agenda due to its potential and the time it takes to realize ROI.
Takeaway 4: Democratizing data for insights and decision making remains a critical challenge.
Gupta pointed out the consistent struggle across companies to democratize their data. She emphasized the need for a centralized platform: "Metrics and insights need to be centralized, and I think that the data team needs to focus on a single source of truth for what’s making the bottom-line revenue for the company," she said. Panelists agreed that data and insights should be the primary focus of a CDO’s office, but also acknowledged the challenge in achieving this goal across organizations.
Takeaway 5: Leaders must balance innovation and risk in implementing AI.
The panelists also discussed the importance of balancing innovation and risk when implementing AI, particularly in highly regulated industries. They emphasized the need to educate boards and leadership teams about AI and its potential benefits while also considering the risks associated with it.
Fox, who works in a regulated organization, said, “The biggest question from our board—they will always think about risk first when it comes to our business and regulators.” She said they recognized the need to be educated about the technology, as well as the urgency of making sure employees use it appropriately.
"The biggest challenge for us, and I imagine it's the same for any enterprise content company, is the copyright issues," Fox said.
Solving the Innovator's Dilemma
Salim Ismail, Founder, OpenExO, and Author, Exponential Organizations
Takeaway 1: Technology is accelerating at an exponential rate, and organizations need to adapt quickly to remain relevant.
Ismail emphasized the rapid acceleration of technological advancements and the need for organizations to adapt quickly to remain relevant. He highlighted the concept of Exponential Organizations, which can scale their operations as fast as technology can scale.
Ismail also mentioned how legacy organizations often struggle with disruptive innovation. That’s because they are designed for efficiency and predictability, whereas the present and future require agility, flexibility, and speed. He emphasized the need for organizations to transform their leadership and organizational structure to be more adaptable and flexible.
“A hundred years ago, anything important happened within a day’s walk. Today, something that happens in Tokyo affects us in minutes.”
Takeaway 2: The concept of abundance is transforming businesses and society.
Ismail elaborated on the concept of abundance, a phenomenon in which certain resources or technologies become so cheap and widespread that they fundamentally transform businesses and society. He pointed out that traditionally, businesses thrived on selling scarcity.
"We have a dozen technologies today, all operating on this doubling pattern," he explained. These technologies, which can disrupt industries, are becoming more accessible and less expensive. This is creating a new landscape where advanced technologies are not exclusive to large corporations or governments but are accessible to anyone, anywhere.
He further explained how the cost of many technologies—from DNA sequencing to solar energy—has continued to drop drastically. This drop in cost is facilitating the digitization of various sectors, leading to disruptive changes. From healthcare to education, this shift toward abundance is transforming industries and promises to bring profound societal changes.
"The problem with humanity is our emotions are paleolithic, our institutions are medieval, and our technology is godlike."
Takeaway 3: Exponential Organizations innovate at the edge, outside the core organization.
Finally, Ismail emphasized the importance of innovating at the edge of your organization—in other words, outside the core organization. At the edge, disruptive innovations can be explored and implemented without being stifled by the organization’s internal structures or resistance to change.
"I've been in the boardroom of probably 150 of the Fortune 500," he said. "I've never seen it work to do disruptive innovation in the core organization."
Ismail cited examples of companies that have successfully launched disruptive innovations at the edge of their organizations. He suggested that large organizations should adopt a similar approach—launching these innovations at the edge and tracking a portfolio approach. The low cost and high potential of these disruptive innovations at the edge present an opportunity for organizations to continually adapt and remain relevant in the rapidly changing technological landscape.
“The cost of doing disruptive innovation is now near zero. So, I’d even drop the amount of disruptive innovation at the edge—but have the organizational courage that if something starts to succeed, spin it off, don’t bring it in, because invariably you’ll kill it.”
Watch the video from this session here
Watch the video from this session here
What’s Coming: Quantum Computing
Moderator: Stephanie Kim, Executive Director, Enterprise Innovation, KPMG
Panelists: Aaron Kemp, US Quantum Leader, KPMG LLP
Richard Padbury, Global Lead, IBM Quantum Commercial Ecosystem
Takeaway 1: Quantum computing is enhancing, not replacing, classical computing.
Quantum computing is a new paradigm in technology. It’s not going to replace classical systems; rather, it will augment and solve problems classical systems can’t. As such, quantum will occupy its own place within the computing environment—filling gaps that neither classical computing nor AI can address. Padbury explained, “[In] classical computing, a single bit can only be a one or a zero. But quantum bits—or qubits—can actually be represented as a combination of both.”
Takeaway 2: Quantum computing has real-world applications.
According to Padbury, IBM was one of the first organizations to put quantum computers on the cloud. He said that this new tool and new way of thinking might help us solve problems that we’ve not even considered yet. Already quantum systems are being used to solve problems, such as optimizing batteries for electric vehicles and conducting cancer research. Kemp pointed to other examples, including opportunities to optimize fraud detection and logistics management: "We’re working with clients on the logistics of, how do we move needed supplies into an area after a hurricane?" Panelists also discussed the intersection of quantum and AI, with quantum computing being used to improve algorithms and help train models. Padbury noted that his organization also uses AI to help in mapping classical problems to a quantum computer.
Takeaway 3: Quantum computing will disrupt cybersecurity.
Panelists stressed that quantum computing is revolutionizing the field of cybersecurity and cryptography. They discussed the risks of “harvest now, decrypt later”—a practice in which certain nation-states are actively collecting RSA-encrypted data with the intention of deciphering it in the future using advanced quantum systems. Kemp warned that the largest cryptographic migration in history is approaching due to the advent of post-quantum cryptography.
"Post-quantum cryptography is coming, and there’s a lot of prework that you can do," he advised. He mentioned reading a paper in which the authors had factored a 48-bit number and estimate they can crack RSA 2048 with 347 logical qubits.
Takeaway 4: Start investing in quantum skills.
Both panelists expressed concerns about the need for a quantum workforce and urged organizations to start preparing now.
"The estimate is, we will be 50% short of a quantum workforce by next year," Kemp said. "So we’ve got to figure out the training, we’ve got to figure out how to get kids interested in this and really shore up what’s going to be a transformative technology as we move down the road." Padbury urged leaders to start now: "Let's start having the conversation. Let’s start identifying opportunities and don’t wait."
Watch the video from this session here