Summary.
Leading Wall Street research firm Evercore ISI, in collaboration with venture studio Visionary Future, embarked on a comprehensive study to understand the profound effects of Generative AI on businesses, the broader economy, and its integration into futureAs Generative AI (GenAI) technologies gain traction, they are becoming integral to boardroom strategies and operational tactics. Companies are keen to integrate these advancements, positioning themselves at the forefront of this AI-driven evolution. With the technology now poised to augment complex tasks across various industries, many leaders are thinking about how to navigate and leverage this transformative synergy between humans and AI for their own organizations.
Leading Wall Street research firm Evercore ISI, in collaboration with venture studio Visionary Future, embarked on a comprehensive study to understand the eprofound effects of Generative AI on businesses, the broader economy, and its integration into future workforces. They conducted an in-depth analysis of over 160 million jobs in order to produce analytical insight to help leaders navigate change.
Productivity’s Solution
AI’s advent can unlock solutions to pressing demographic challenges facing global economies. The shifting dynamics of increasing elderly populations and the decreasing number of working-age individuals necessitate growth and productivity enhancements — a gap that AI promises to bridge.
While U.S. productivity growth from 1960 to 2009 saw a steady rise in real GDP, the subsequent decade experienced a plateau, according to Evercore ISI. Productivity growth that’s been stuck at slightly over 1% real GDP for the past 15 years is concerning enough, but when combined with the changing composition of the workforce, global economies are facing serious structural challenges. Evercore ISI’s analysis shows not only that birth rates have peaked globally, but also that by 2027, more than one-third of global GDP will be generated in countries with declining populations. This implies that we will soon face a challenge of an ever-decreasing workforce supporting an aging population of retirees.
With AI’s influence, our projections suggest a potential resurgence in global GDP growth, envisioning a substantial boost to the global economy by 2032. AI will emerge not merely as a technological marvel, but as a beacon of hope in addressing demographic and productivity challenges.
The Evolution of White Collar Work
A few years back, a former MIT student showed us an intriguing application: by sending a hand-drawn image to an AI, within moments, a polished PowerPoint slide was generated and sent back. While this initially seemed like a novel approach to automate some tasks to improve efficiency, it was evident that the system was limited to only recreating the design, without adding any substantial content.
Recent advancements in Generative AI have accelerated to offer more comprehensive support, substantively enhancing the productivity of early adopting professionals. Even amidst challenges like the Covid pandemic, prominent management consultancies (including MBB, the Big Four, and Accenture) adapted, integrating AI to further empower their teams. In recent months, there’s been a notable trend, both in Wall Street and Main Street banks, to explore AI’s potential more deeply, with the aim of augmenting their workforce’s capabilities.
Our recent analysis emphasizes the potential of AI to augment high value, intellectually-demanding roles. Evercore ISI’s findings indicate that while all jobs in the U.S. have some level of AI exposure — roles with compensation over $100,000 annually may both be impacted by, and benefit more from, AI augmentation. For example, Harvard Business School (HBS) and Boston Consulting Group (BCG) recently released research suggesting that AI agents can improve low-performing BCG analysts more than already-high-performing BCG analysts.
Our analysis indicates that almost every job will in some way be impacted by AI. However, fully replacing workers with AI remains a perhaps-impossible outcome; for example, recent efforts to automate entire call-center operations via AI systems have stumbled when confronted by the fact that novel customer issues emerge, which AI is unable to solve. Where we have seen greater effectiveness is in productivity acceleration or productivity enhancement, such as when a senior software engineer is able to automate a significant portion of code development through use of AI systems, but then manually adjusts the code to optimize it. Our analysis assumes, in part, that a combination of moderately-paced corporate adoption rates and government policy interventions will prevent a more significant restructuring of the workforce than if AI were automated rapidly and broadly.
We believe the conversation should not be about whether GenAI will replace jobs, but rather about understanding how GenAI can enhance various business functions: humans + AI. As the Evercore strategy team readily points out, financial and market analytical roles like their own are amongst the jobs best positioned to use Generative AI to improve productivity through the implementation of Generative AI. Echoing this sentiment, the CEO of a prominent European company shared with Visionary Future that AI’s integration at his multibillion-euro enterprise is not limited to sales and marketing, but is gradually making its way into strategic functions like finance.
Deconstructing the Workforce
Evercore ISI consolidated a voluminous repository of academic and economic data spanning 160 million U.S. jobs, 20 industries, 250+ subsectors and 800+ occupations, examining how workers used 52 abilities in 41 activities to complete their jobs. These roles and responsibilities were then cross-referenced to a range of complex mental tasks in which AI has begun to perform as good or better than humans.
Their analysis found that cognitive abilities (such as information ordering and memorization) have higher AI exposure, meaning that AI is able to perform a task as well as or better than a human, while creative- or strength-based abilities (such as originality, oral expression, or explosive strength) have lower or no AI exposure. The more social interaction and empathy that a job requires, the less exposure it has to AI, and the more physical labor is entailed in a job, the less exposure it has to AI (subject, in the latter case, to the possibility of robotic automation). In an extreme example, ballet dancers have the least exposure to AI, in our analysis.
By understanding what artificial intelligence is good at, and what it is not good at, we can calculate which industries — and within the industry, which professions — are most susceptible to AI disruption.
AI exposure is high in high value-added service sector jobs such as legal; computer and mathematical; and business and financial operations occupations; while it’s low in more manufacturing-oriented sectors. This is notable insofar as many G7 economies migrated over the past 50 years from being primarily manufacturing-centric to being primarily services-driven.
On the whole, Evercore ISI estimated that GenAI-driven tools can leverage 32% of each job’s function on average across the entirety of the U.S. economy to improve productivity.
The former managing partner of a Tier 1 global law firm shared with Visionary Future that he feels AI adoption will be relatively slow in the legal profession. The CEO of a multibillion-dollar professional services firm expressed frustration that partners and practices were resistant to integrating it into their work, and that instilling a mindset shift among partners and practice groups to accept AI was his greatest challenge — not the applicability of AI to enhancing productivity.
However, in the realm of technology, AI’s potential is already manifesting. London-based entrepreneur David Lefevre provided some insights for us from his recent edtech venture, Tutello. By incorporating AI-driven tools such as GitHub Copilot and ChatGPT Code Interpreter, his development team’s productivity has tripled. Rather than employing traditional user testing methods such as having a human being interact with the software product, attempting to get it to accomplish something, or seeking to “break” it by entering nonsense inputs, AI agents have instead been instrumental for Tutello, underscoring the enhancement in operational efficiency.
Large companies stand to benefit even more than startups from Generative AI. One single company with over $10 billion in revenue that Visionary Future spoke with was anticipating more than $750 million of incremental EBITDA within five years through a combination of productivity enhancements and revenue growth (notably, just under half of the gains are from human+AI systems). Visionary Future’s analysis suggests that by 2032, more than seven times as much value will accrue to established enterprises versus startups, in terms of absolute market capitalization: $34 trillion for large companies versus $4.6 trillion for startups.
From Macro to Micro Across the Russell 3000: The Evercore AI Impact Navigator
Using the occupation and job exposure framework developed above, the Evercore ISI strategy team took macro theory into the tangible corporate realm. The Evercore AI Impact Navigator empowers investors and companies to examine workforce composition and assess leverage opportunities across a range of technology adoption scenarios. By entering any ticker symbol across the Russell 3000 into the tool, an instant visualized analysis of company workforce exposure to generative AI is calculated and broken down by job function.
The tool empowers business leaders to understand the potential that they may be capable of if they can shift mindsets and move their organization into a more AI-proficient stance. It can help them identify specific parts of their organization and functional areas where they should look to develop a strategic and operational plan to implement AI and human+AI systems.
In our advisory work at Visionary Future, we use this type of analysis during the diagnostic stage of a five-part approach to helping companies pivot into maximizing AI potential. We employ it as an input in shaping a broader AI strategy for the organization.
Boards and investors can use this type of benchmarking to understand where a company is positioned relative to where it should be, and act accordingly.
Envisioning a Collaborative Future
The growth narrative around AI transcends mere operational efficiencies. The authors’ discussions with global enterprises highlight a trend: the fusion of humans and AI will drive revenue growth. This human+AI paradigm is reminiscent of supportive digital agents like Iron Man’s J.A.R.V.I.S., emphasizing empowerment over replacement.
As we stand on the cusp of this transformative era, it’s clear that AI’s integration will reshape organizational and societal landscapes. However, with insightful frameworks and tools, we’re well-equipped to chart this evolving terrain.
The authors wish to thank the Evercore ISI strategy team, who conducted in-depth analysis on 3,000 companies and more than 160 million jobs to produce the Evercore AI Impact Navigator: Barak Hurvitz, Michael Chu and Steven Fandozzi.
