Macro Impacts on Technological Innovation
One of the growing concerns about the advancements in artificial intelligence (AI) is that it will have adverse impacts on society as human workers are replaced by virtual ones.
Concerns about new technologies making people obsolete, however, are nothing new. And, while the likelihood is that technological developments will leave some sections of the economy behind (for example, I worked at a video rental store in high school, something my kids cannot wrap their heads around), it will also open up entirely new areas that we cannot fathom as yet (many jobs now did not exist 20 years ago). This concept is the whole idea behind “creative destruction”, a phrase coined by economist Joseph Schumpeter in the 1940s, in which technological innovation results in economic dynamism and spurs growth (and inhibiting such creative destruction in favour of supporting pre-existing structures is arguably a big reason why some countries’ economies stagnate).
Secondly, for the industries that persist by adapting and evolving with technological change, theory (and history) supports that technological innovations that generate productivity gains tend to result in greater employment in those areas rather than less.
A technology-driven boost to productivity means resources can be used more efficiently — fewer inputs are required for a given amount of output. Superficially, that would suggest lower levels on employment (i.e., less workers are needed to sustain levels of production); however, the technological advancements’ efficiency gains also have the impact of lowering the per-unit cost of production which, in turn, tends to reduce prices — thinking back to macroeconomics courses with aggregate supply and demand charts, the innovation has the impact of shifting the supply curve out to the right. Assuming that demand is sensitive to price (i.e., demand is price elastic and the demand curve is sloping downward), the supply-side-driven decline in price spurs greater demand for the output that supports increased demand for inputs, such as workers, that can more than offset any losses due to efficiency gains.
Illustrative Impact of Technological Innovation
D=demand curve; S1= initial supply curve; S2=supply curve after technological innovation; Q=quantity of good or service; P=price of good or service. Source: The author, Guardian Capital LP
This is the so-called “Jevons Paradox”, named after 19th-century economist William Stanley Jevons, who noted that improvements in the efficiency of coal use led to much wider consumption of coal rather than less — and history shows that this has expanded into other areas of the economy as well.
A simple example is Microsoft Excel’s impact on accounting and finance. Microsoft Excel was officially released for sale in September 1985, with the first Windows iteration made available in November 1987. In 1992, Excel introduced its auto-fill feature (automatically copy formula to other cells), and Visual Basic for Applications (VBA) programming to automate tasks was introduced in 1993 (as an aside, QuickBooks was first introduced by Intuit in 1992).
These developments substantially lowered the costs associated with business record-keeping, reporting and other financial analysis. However, rather than reducing the overall need for people to do these tasks, employment in these areas has steadily increased over the last three decades as demand for people that can adequately use the software and understand its output has increased in tandem with the lower cost points, making financial analysis services more accessible to a broader array of businesses (and this does not directly account for the people within businesses across various industries that serve analytical jobs that did not exist previously).
Employment in accounting, bookkeeping & payroll services, U.S.
(millions)
Shaded regions represent periods of U.S. recession; source: Guardian Capital, based on data from the U.S. Bureau of Labor Statistics to June 2026
I have noted before that my near-term expectation is that AI will represent the next step along the lines of Excel, in that it will help people and businesses better and more efficiently consolidate broader forms of information (rather than just data) to do better analysis and make better decisions — I am not quite sold on the idea that we are verging toward Skynet1 as yet.
Interestingly, there was a recent study by financial technology firm Ramp2 that showed that U.S. firms that have adopted AI most aggressively have seen headcounts rise by 10% on average over a two-year time horizon, with entry-level jobs at the most AI-skewed firms rising by a stronger 12%.
This echoes an oft-used phrase from Guardian Capital LP Managing Director and Head of i3 Investments™, Sri Iyer (borrowing from Sam Altman), “AI will not replace people, but people who know how to use AI will replace people who do not”. In Sri’s view, the future is likely less about humans competing with AI and more about humans who can effectively orchestrate AI to outperform those who cannot, with the most interesting potential trend being that many future jobs may not be about building AI, but about managing, governing, coaching, supervising, auditing, and collaborating with AI systems across every industry.
It may well end up being different this time, with respect to the impact on employment — and we are still in the early stages of this technological evolution — but that is not obvious yet…
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David Onyett-Jeffries
David Onyett-Jeffries is Vice President, Economics & Multi Asset Solutions, at Guardian Capital LP (GCLP). He provides macroeconomic guidance to GCLP and its affiliates. Additionally, he is a portfolio manager of GCLP’s multi-asset portfolios and funds and works closely with GCLP’s Directed Outcomes team.
1 Wikipedia, Skynet (Terminator), July 15, 2026, https://en.wikipedia.org/wiki/Skynet_(Terminator)
2 Ramp, Ramp Economics Lab, A New Look at AI’s Impact on Jobs. Ramp – Revelio: Firm-Level AI Spending and Workforce Adjustment, June 2026, https://ramp.com/data/ai-jobs-impact
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Published: July 15, 2026
