Global Advisors | Quantified Strategy Consulting

“Generally speaking people hate change. It’s human nature. But change is super important. It’s inevitable. In fact, on my desk in my office I have a little plaque that says ‘Change or die.’ As a business leader, one of the perspectives you have to have is that you’ve got to constantly evolve and change.” – David Solomon – Goldman Sachs CEO

The quoted insight comes from David M. Solomon, Chief Executive Officer and Chairman of Goldman Sachs, a role he has held since 2018. It was delivered during a high-profile interview at The Economic Club of Washington, D.C., 30 October 2025, as Solomon reflected on the necessity of adaptability both personally and as a leader within a globally significant financial institution.

“We have very smart people, and we can put these [AI] tools in their hands to make them more productive… By using AI to reimagine processes, we can create operating efficiencies that give us a scaled opportunity to reinvest in growth.” – David Solomon – Goldman Sachs CEO

David Solomon, Chairman and CEO of Goldman Sachs, delivered the quoted remarks during an interview at the HKMA Global Financial Leaders’ Investment Summit on 4 November 2025, articulating Goldman’s strategic approach to integrating artificial intelligence across its global franchise. His comments reflect both personal experience and institutional direction: leveraging new technology to drive productivity, reimagine workflows, and reinvest operational gains in sustainable growth, rather than pursuing simplistic headcount reductions or technological novelty for its own sake.

Backstory and Context of the Quote

David Solomon’s statement arises from Goldman Sachs’ current transformation—“Goldman Sachs 3.0”—centred on AI-driven process re-engineering. Rather than employing AI simply as a cost-cutting device, Solomon underscores its strategic role as an enabler for “very smart people” to magnify their productivity and impact. This perspective draws on his forty-year career in finance, where successive waves of technological disruption (from Lotus 1-2-3 spreadsheets to cloud computing) have consistently shifted how talent is leveraged, but have not diminished its central value.

The immediate business context is one of intense change: regulatory uncertainty in cross-border transactions, rebounding capital flows into China post-geopolitical tension, and a high backlog of M&A activity, particularly for large-cap US transactions. In this environment, efficiency gains from AI allow frontline teams to refocus on advisory, origination, and growth while adjusting operational models at a rapid pace. Solomon’s leadership style—pragmatic, unsentimental, and data-driven—favours process optimisation, open collaboration, and the breakdown of legacy silos.

About David Solomon

Background:

• Born in Hartsdale, New York, in 1962; educated at Hamilton College with a BA in political science, then entered banking.
• Career progression: Held senior roles at Irving Trust, Drexel Burnham, Bear Stearns; joined Goldman Sachs in 1999 as partner, eventually leading the Financing Group and serving as co-head of the Investment Banking Division for a decade.
• Appointed President and COO in 2017, then CEO in October 2018 and Chairman in January 2019, succeeding Lloyd Blankfein.
• Brought a reputation for transformative leadership, advocating modernisation, flattening hierarchies, and integrating technology across every aspect of the firm’s operations.

Leadership and Culture:

• Solomon is credited with pushing through “One Goldman Sachs,” breaking down internal silos and incentivising cross-disciplinary collaboration.
• He has modernised core HR and management practices: implemented real-time performance reviews, loosened dress codes, and raised compensation for programmers.
• Personal interests—such as his sideline as DJ D-Sol—underscore his willingness to defy convention and challenge the insularity of Wall Street leadership.

Institutional Impact:

• Under his stewardship, Goldman has accelerated its pivot to technology—automating trading operations, consolidating platforms, and committing substantial resources to digital transformation.
• Notably, the current “GS 3.0” agenda focuses on automating six major workflows to direct freed capacity into growth, consistent with a multi-decade productivity trend.

Leading Theorists and Intellectual Lineage of AI-Driven Productivity in Business

Solomon’s vision is shaped and echoed by several foundational theorists in economics, management science, and artificial intelligence:

1. Clayton Christensen

• Theory: Disruptive Innovation—frames how technological change transforms industries not through substitution but by enabling new business models and process efficiencies.
• Relevance: Goldman Sachs’ approach to using AI to reimagine workflows and create new capabilities closely mirrors Christensen’s insights on sustaining versus disruptive innovation.

2. Erik Brynjolfsson & Andrew McAfee

• Theory: Race Against the Machine, The Second Machine Age—chronicled how digital automation augments human productivity and reconfigures the labour market, not just replacing jobs but reshaping roles and enhancing output.
• Relevance: Solomon’s argument for enabling smart people with better tools directly draws on Brynjolfsson’s proposition that the best organisational outcomes occur when firms successfully combine human and machine intelligence.

3. Michael Porter

• Theory: Competitive Advantage—emphasised how operational efficiency and information advantage underpin sustained industry leadership.
• Relevance: Porter’s ideas connect to Goldman’s agenda by showing that AI integration is not just about cost, but about improving information processing, strategic agility, and client service.

4. Herbert Simon

• Theory: Bounded Rationality and Decision Support Systems—pioneered the concept that decision-making can be dramatically improved by systems that extend the cognitive capabilities of professionals.
• Relevance: Solomon’s claim that AI puts better tools in the hands of talented staff traces its lineage to Simon’s vision of computers as skilled assistants, vital to complex modern organisations.

5. Geoffrey Hinton, Yann LeCun, Yoshua Bengio

• Theory: Deep Learning—established the contemporary AI revolution underpinning business process automation, language models, and data analysis at enterprise scale.
• Relevance: Without the breakthroughs made by these theorists, AI’s current generation—capable of augmenting financial analysis, risk modelling, and operational management—could not be applied as Solomon describes.

Synthesis and Strategic Implications

Solomon’s quote epitomises the intersection of pragmatic executive leadership and theoretical insight. His advocacy for AI-integrated productivity reinforces a management consensus: sustainable competitive advantage hinges not just on technology, but on empowering skilled individuals to unlock new modes of value creation. This approach is echoed by leading researchers who situate automation as a catalyst for role evolution, scalable efficiency, and the ability to redeploy resources into higher-value growth opportunities.

Goldman Sachs’ specific AI play is therefore neither a defensive move against headcount nor a speculative technological bet, but a calculated strategy rooted in both practical business history and contemporary academic theory—a paradigm for how large organisations can adapt, thrive, and lead in the face of continual disruption.

“Generally speaking people hate change. It’s human nature. But change is super important. It’s inevitable. In fact, on my desk in my office I have a little plaque that says ‘Change or die.’ As a business leader, one of the perspectives you have to have is that you’ve got to constantly evolve and change.” – David Solomon – Goldman Sachs CEO

The quoted insight comes from David M. Solomon, Chief Executive Officer and Chairman of Goldman Sachs, a role he has held since 2018. It was delivered during a high-profile interview at The Economic Club of Washington, D.C., 30 October 2025, as Solomon reflected on the necessity of adaptability both personally and as a leader within a globally significant financial institution.

His statement is emblematic of the strategic philosophy that has defined Solomon’s executive tenure. He uses the ‘Change or die’ principle to highlight the existential imperative for renewal in business, particularly in the context of technological transformation, competitive dynamics, and economic disruption.

Solomon’s leadership at Goldman Sachs has been characterised by deliberate modernisation. He has overseen the integration of advanced technology, notably in artificial intelligence and fintech, implemented culture and process reforms, adapted workforce practices, and expanded strategic initiatives in sustainable finance. His approach blends operational rigour with entrepreneurial responsiveness – a mindset shaped both by his formative years in high-yield credit markets at Drexel Burnham and Bear Stearns, and by his rise through leadership roles at Goldman Sachs.

His remark on change was prompted by questions of business resilience and the need for constant adaptation amidst macroeconomic uncertainty, regulatory flux, and the competitive imperatives of Wall Street. For Solomon, resisting change is an instinct, but enabling it is a necessity for long-term health and relevance — especially for institutions in rapidly converging markets.

About David M. Solomon

• Born 1962, Hartsdale, New York.
• Hamilton College graduate (BA Political Science).
• Early career: Irving Trust, Drexel Burnham, Bear Stearns.
• Joined Goldman Sachs as a partner in 1999, advancing through financing and investment banking leadership.
• CEO from October 2018, Chairman from January 2019.
• Known for a modernisation agenda, openness to innovation and talent, commitment to client service and culture reform.
• Outside finance: Philanthropy, board service, and a second career as electronic dance music DJ “DJ D-Sol”, underscoring a multifaceted approach to leadership and personal renewal.

Theoretical Backstory: Leading Thinkers on Change and Organisational Adaptation

Solomon’s philosophy echoes decades of foundational theory in business strategy and organisational behaviour:

Charles Darwin (1809–1882)
While not a business theorist, Darwin’s principle of “survival of the fittest” is often cited in strategic literature to emphasise the adaptive imperative — those best equipped to change, survive.

Peter Drucker (1909–2005)
Drucker, regarded as the father of modern management, wrote extensively on innovation, entrepreneurial management and the need for “planned abandonment.” He argued, “The greatest danger in times of turbulence is not the turbulence; it is to act with yesterday’s logic.” Drucker’s legacy forms a pillar of contemporary change management, advising leaders not only to anticipate change but to institutionalise it.

John Kotter (b. 1947)
Kotter’s model for Leading Change remains a classic in change management. His eight-step framework starts with establishing a sense of urgency and is grounded in the idea that successful transformation is both necessary and achievable only with decisive leadership, clear vision, and broad engagement. Kotter demonstrated that people’s resistance to change is natural, but can be overcome through structured actions and emotionally resonant leadership.

Clayton Christensen (1952-2020)
Christensen’s work on disruptive innovation clarified how incumbents often fail by ignoring, dismissing, or underinvesting in change — even when it is inevitable. His concept of the “Innovator’s Dilemma” remains seminal, showing that leaders must embrace change not as an abstract imperative but as a strategic necessity, lest they be replaced or rendered obsolete.

Rosabeth Moss Kanter
Kanter’s work focuses on the human dynamics of change, the importance of culture, empowerment, and the “innovation habit” in organisations. She holds that the secret to business success is “constant, relentless innovation” and that resistance to change is deeply psychological, calling for leaders to engineer positive environments for innovation.

Integration: The Leadership Challenge

Solomon’s ethos channels these frameworks into practical executive guidance. For business leaders, particularly in financial services and Fortune 500 firms, the lesson is clear: inertia is lethal; organisational health depends on reimagining processes, culture, and client engagement for tomorrow’s challenges. The psychological aversion to change must be managed actively at all levels — from the boardroom to the front line.

In summary, the context of Solomon’s quote reflects not only a personal credo but also the consensus of generations of theoretical and practical leadership: only those prepared to “change or die” can expect to thrive and endure in an era defined by speed, disruption, and relentless unpredictability.

“If the firm grows and you expand and you can invest in other areas for growth, we’ll wind up with more jobs… we have at every step along the journey for the last forty years as technology has made us more productive. I don’t think it’s different this time [with AI].” – David Solomon – Goldman Sachs CEO

David Michael Solomon, born in 1962 in Hartsdale, New York, is an American investment banker and DJ, currently serving as the CEO and Chairman of Goldman Sachs. His journey into the financial sector began after he graduated with a BA in political science from Hamilton College. Initially, Solomon worked at Irving Trust Company and Drexel Burnham before joining Bear Stearns. In 1999, he moved to Goldman Sachs as a partner and became co-head of the High Yield and Leveraged Loan Business.

Solomon’s rise within Goldman Sachs was swift and strategic. He became the co-head of the Investment Banking Division in 2006 and held this role for a decade. In 2017, he was appointed President and Chief Operating Officer, and by October 2018, he succeeded Lloyd Blankfein as CEO. He became Chairman in January 2019.

Beyond his financial career, Solomon is known for his passion for music, producing electronic dance music under the alias “DJ D-Sol”. He has performed at various venues, including nightclubs and music festivals in New York, Miami, and The Bahamas.

Context of the Quote

The quote highlights Solomon’s perspective on technology and job creation in the financial sector. He suggests that while technology, particularly AI, can enhance productivity and potentially lead to job reductions in certain areas, the overall growth of the firm will create more opportunities for employment. This view is rooted in his experience observing how technological advancements have historically led to increased productivity and growth for Goldman Sachs.

Leading Theorists on AI and Employment

Several leading theorists have explored the impact of AI on employment, with divergent views:

• Joseph Schumpeter is famous for his theory of “creative destruction,” which suggests that technological innovations often lead to the destruction of existing jobs but also create new ones. This cycle is seen as essential for economic growth and innovation.

• Klaus Schwab, founder of the World Economic Forum, has discussed the Fourth Industrial Revolution, emphasizing how AI and automation will transform industries. However, he also highlights the potential for new job creation in emerging sectors.

• Economists Erik Brynjolfsson and Andrew McAfee have written extensively on how technology can lead to both job displacement and creation. They argue that while AI may reduce certain types of jobs, it also fosters economic growth and new opportunities.

These theorists provide a backdrop for understanding Solomon’s optimistic view on AI’s impact on employment, focusing on the potential for growth and innovation to offset job losses.

Conclusion

David Solomon’s quote encapsulates his optimism about the interplay between technology and job creation. Focusing on the strategic growth of Goldman Sachs, he believes that technological advancements will enhance productivity and create opportunities for expansion, ultimately leading to more employment opportunities. This perspective aligns with broader discussions among economists and theorists on the transformative role of AI in the workplace.

“Markets run in cycles, and whenever we’ve historically had a significant acceleration in a new technology that creates a lot of capital formation and therefore lots of interesting new companies around it, you generally see the market run ahead of the potential. Are there going to be winners and losers? There are going to be winners and losers.” – David Solomon – Goldman Sachs CEO

The quote, “Markets run in cycles, and whenever we’ve historically had a significant acceleration in a new technology that creates a lot of capital formation and therefore lots of interesting new companies around it, you generally see the market run ahead of the potential. Are there going to be winners and losers? There are going to be winners and losers,” comes from a public discussion with David Solomon, CEO of Goldman Sachs, during Italian Tech Week in October 2025. This statement was made in the context of a wide-ranging interview that addressed the state of the US and global economy, the impact of fiscal stimulus and technology infrastructure spending, and, critically, the current investment climate surrounding artificial intelligence (AI) and other emergent technologies.

Solomon’s comments were prompted by questions around the record-breaking rallies in US and global equity markets and specifically the extraordinary market capitalisations reached by leading tech firms. He highlighted the familiar historical pattern: periods of market exuberance often occur when new technologies spur rapid capital formation, leading to the emergence of numerous new companies around a transformative theme. Solomon drew parallels with the Dot-com boom to underscore the cyclical nature of markets and to remind investors that dramatic phases of growth inevitably produce both outsized winners and significant casualties.

His insight reflects a seasoned banker’s view, grounded in empirical observation: while technological waves can drive periods of remarkable wealth creation and productivity gains, they also tend to attract speculative excesses. Market valuations in these periods often disconnect from underlying fundamentals, setting the stage for later corrections. The resulting market shake-outs separate enduring companies from those that fail to deliver sustainable value.

About David Solomon

David M. Solomon is one of the most prominent figures in global finance, serving as the CEO and Chairman of Goldman Sachs since 2018. Raised in New York and a graduate of Hamilton College, Solomon has built his reputation over four decades in banking—rising through leadership positions at Irving Trust, Drexel Burnham, and Bear Stearns before joining Goldman Sachs in 1999 as a partner. He subsequently became global head of the Financing Group, then co-head of the Investment Banking Division, playing a central role in shaping the firm’s capital markets strategy.

Solomon is known for his advocacy of organisational modernisation and culture change at Goldman Sachs—prioritising employee well-being, increasing agility, and investing heavily in technology. He combines traditional deal-making acumen with an openness to digital transformation. Beyond banking, Solomon has a notable side-career as a DJ under the name DJ D-Sol, performing electronic dance music at high-profile venues.

Solomon’s career reflects both the conservatism and innovative ambition associated with modern Wall Street leadership: an ability to see risk cycles clearly, and a willingness to pivot business models to suit shifts in technological and regulatory environments. His net worth in 2025 is estimated between $85 million and $200 million, owing to decades of compensation, equity, and investment performance.

Theoretical Foundations: Cycles, Disruptive Innovation, and Market Dynamics

Solomon’s perspective draws implicitly on a lineage of economic theory and market analysis concerning cycles of innovation, capital formation, and asset bubbles. Leading theorists and their contributions include:

• Joseph Schumpeter: Schumpeter’s theory of creative destruction posited that economic progress is driven by cycles of innovation, where new technologies disrupt existing industries, create new market leaders, and ultimately cause the obsolescence or failure of firms unable to adapt. Schumpeter emphasised how innovation clusters drive periods of rapid growth, investment surges, and, frequently, speculative excess.

• Carlota Perez: In Technological Revolutions and Financial Capital (2002), Perez advanced a model of techno-economic paradigms, proposing that every major technological revolution (e.g., steam, electricity, information technology) proceeds through phases: an initial installation period—characterised by exuberant capital inflows, speculation, and bubble formation—followed by a recessionary correction, and, eventually, a deployment period, where productive uses of the technology diffuse more broadly, generating deep-seated economic gains and societal transformation. Perez’s work helps contextualise Solomon’s caution about markets running ahead of potential.

• Charles Kindleberger and Hyman Minsky: Both scholars examined the dynamics of financial bubbles. Kindleberger, in Manias, Panics, and Crashes, and Minsky, through his Financial Instability Hypothesis, described how debt-fuelled euphoria and positive feedback loops of speculation can drive financial markets to overshoot the intrinsic value created by innovation, inevitably resulting in busts.

• Clayton Christensen: Christensen’s concept of disruptive innovation explains how emergent technologies, initially undervalued by incumbents, can rapidly upend entire industries—creating new winners while displacing former market leaders. His framework helps clarify Solomon’s points about the unpredictability of which companies will ultimately capture value in the current AI wave.

• Benoit Mandelbrot: Applying his fractal and complexity theory to financial markets, Mandelbrot challenged the notion of equilibrium and randomness in price movement, demonstrating that markets are prone to extreme events—outlier outcomes that, while improbable under standard models, are a recurrent feature of cyclical booms and busts.

Practical Relevance in Today’s Environment

The patterns stressed by Solomon, and their theoretical antecedents, are especially resonant given the current environment: massive capital allocations into AI, cloud infrastructure, and adjacent technologies—a context reminiscent of previous eras where transformative innovations led markets both to moments of extraordinary wealth creation and subsequent corrections. These cycles remain a central lens for investors and business leaders navigating this era of technological acceleration.

By referencing both history and the future, Solomon encapsulates the balance between optimism over the potential of new technology and clear-eyed vigilance about the risks endemic to all periods of market exuberance.

“AI really allows smart, talented, driven, sophisticated people to be more productive – to touch more people, have better information at their disposal, better analysis.” – David Solomon – Goldman Sachs CEO

David Solomon, CEO of Goldman Sachs, made the statement “AI really allows smart, talented, driven, sophisticated people to be more productive – to touch more people, have better information at their disposal, better analysis” during an interview at Italian Tech Week 2025, reflecting his conviction that artificial intelligence is redefining productivity and impact across professional services and finance.

David Solomon is one of the most influential figures in global finance, serving as Chairman and CEO of Goldman Sachs since 2018. Born in 1962 in Hartsdale, New York, Solomon’s early years were shaped by strong family values, a pursuit of education at Hamilton College, and a keen interest in sport and leadership. Solomon’s ascent in the industry began after stints at Irving Trust and Drexel Burnham, specialising early in commercial paper and junk bonds, then later at Bear Stearns where he played a central role in project financing. In 1999, he joined Goldman Sachs as a partner and quickly rose through the ranks—serving as Global Head of the Financing Group and later Co-Head of the Investment Banking Division for a decade.

His leadership is marked by an emphasis on modernisation, talent development, and integrating technology into the financial sector. Notably, Solomon has overseen increased investments in digital platforms and has reimagined work culture, including reducing working hours and implementing real-time performance review systems. Outside his professional life, Solomon is distinctively known for his passion for music, performing as “DJ D-Sol” at major electronic dance music venues, symbolising a leadership style that blends discipline with creative openness.

Solomon’s remarks on AI at Italian Tech Week are rooted in Goldman Sachs’ major investments in technology: with some 12,000 engineers and cutting-edge AI platforms, Solomon champions the view that technology not only streamlines operational efficiency but fundamentally redefines the reach and ability of talented professionals, providing richer data, deeper insights, and more effective analysis. He frames AI as part of a long continuum—from the days of microfiche and manual records to today’s instant, voice-powered analytics—positioning technology as both a productivity enabler and an engine for growth.

Leading Theorists and Context in AI Productivity

Solomon’s thinking sits at the crossroads of key theoretical advances in artificial intelligence and productivity economics. The transformation he describes draws extensively from foundational theorists and practitioners who have shaped our understanding of AI’s organisational impact:

• Herbert Simon: A founder of artificial intelligence as a discipline, Simon’s concept of “bounded rationality” highlighted that real-world decision making could be fundamentally reshaped by computational power. Simon envisioned computers extending the limits of human cognition, a concept directly echoed in Solomon’s belief that AI produces leverage for talented professionals.

• Erik Brynjolfsson: At MIT, Brynjolfsson has argued that AI is a “general purpose technology” like steam power or electricity, capable of diffusing productivity gains across every sector through automation, improved information processing, and new business models. His work clarifies that the impact of AI is not in replacing human value, but augmenting it, making people exponentially more productive.

• Andrew Ng: As a pioneer in deep learning, Ng has emphasised the role of AI as a productivity tool: automating routine tasks, supporting complex analysis, and dramatically increasing the scale and speed at which decisions can be made. Ng’s teaching at Stanford and public writings focus on making AI accessible as a resource to boost human capability rather than a substitute.

• Daron Acemoglu: The MIT economist challenges overly optimistic readings, arguing that the net benefits of AI depend on balanced deployment, policy, and organisational adaptation. Acemoglu frames the debate on whether AI will create or eliminate jobs, highlighting the strategic choices organisations must make—a theme Solomon directly addresses in his comments on headcount in banking.

• Geoffrey Hinton: Widely known as “the godfather of deep learning,” Hinton’s research underpins the practical capabilities of AI systems—particularly in areas such as data analysis and decision support—that Solomon highlights as crucial to productive professional services.

Contemporary Application and Analysis

The productivity gains Solomon identifies are playing out across multiple sectors:

• In financial services, AI-driven analytics enable deeper risk management, improved deal generation, and scalable client engagement.
• In asset management and trading, platforms like Goldman Sachs’ own “Assistant” and generative coding tools (e.g., Cognition Labs’ Devin) allow faster, more nuanced analysis and automation.
• The “power to touch more people” is realised through personalised client service, scalable advisory, and rapid market insight, bridging human expertise and computational capacity.

Solomon’s perspective resonates strongly with current debates on the future of work. While risks—such as AI investment bubbles, regulatory uncertainty, and workforce displacement—are acknowledged, Solomon positions AI as a strategic asset: not a threat to jobs, but a catalyst for organisational expansion and client impact, consistent with the lessons learned through previous technology cycles.

Theoretical Context Table

Essential Insights

• AI’s impact is cumulative and catalytic, empowering professionals to operate at far greater scale and depth than before, as illustrated by Solomon’s personal technological journey—from manual information gathering to instantaneous AI-driven analytics.
• The quote’s context reflects the practical reality of AI at the world’s leading financial institutions, where technology spend rivals infrastructure, and human-machine synergy is central to strategy.
• Leading theorists agree: real productivity gains depend on augmenting human capability, strategic deployment, and continual adaptation—principles explicitly recognised in Solomon’s operational philosophy and in global best practice.