Relatively few firms so far have been able to quantify artificial intelligence productivity gains. But that has been the case for computing in general and the internet: it takes time for innovations to transform business processes. In other words, associated and complementary intangible capital also must be created.
Studying the productivity impact of computerization on 527 large U.S. firms over 1987-1994, professors Erik Brynjolfsson, MIT Sloan School of Management and Lorin Hitt, University of Pennsylvania, Wharton School found that computerization measured over a five-year to seven-year period found productivity and output contributions up to five times greater than over a one-year period.
“The results suggest that the observed contribution of computerization is accompanied by relatively large and time-consuming investments in complementary inputs, such as organizational capital,” the researchers say.
We could note the same trend with regards to the internet: productivity did not improve quickly, as whole business processes had to be revised.
Study | Period / data | What it found | Relevance to the paradox |
Brynjolfsson and Hitt, 1996, "Paradox Lost?" | Firm-level IT spending | Found substantial returns to information systems investment at the firm level despite weak aggregate evidence. | Early evidence that the "paradox" could be a measurement or aggregation problem. (PubsOnline) |
Brynjolfsson and Hitt, 2000, "Beyond Computation" | Firm-level/case evidence | IT's value depended heavily on organizational transformation and intangible investments. | Probably the most important conceptual explanation for why technology's benefits arrive with a lag. (American Economic Association) |
Brynjolfsson and Hitt, 2003, "Computing Productivity" | ~600 U.S. firms, 1987–94 | Returns to computers were 2–5 times greater over seven years than one year. | Strong evidence that complementary investments take years to generate their full payoff. (ResearchGate) |
Oliner and Sichel, 2000 | U.S. economy | IT accounted for roughly two-thirds of the acceleration in productivity growth between the first and second halves of the 1990s. | By the late 1990s, the productivity payoff of IT had become visible at the macro level. (Federal Reserve) |
Stiroh, 2002 | 61 U.S. industries | Productivity acceleration was greatest in IT-producing and IT-intensive industries. | Shows diffusion beyond the technology-producing sector. (Federal Reserve Bank of New York) |
Barua et al., 2004, "Net-Enabled Business Value" | >1,000 firms | Internet-enabled capabilities improved operational performance and ultimately financial performance; supplier/customer readiness mattered greatly. | Direct evidence that Internet adoption plus complementary organizational capabilities generated business value. (AIS eLibrary) |
López Sánchez et al., 2006 | 464 Spanish firms | Both IT investment and workplace Internet use were associated with higher productivity. | Direct firm-level evidence of an Internet-productivity relationship. (ScienceDirect) |
Bloom, Sadun and Van Reenen, 2007/2012 | U.S. and European multinationals | U.S. firms obtained substantially greater productivity from IT, largely because of superior management practices. | Powerful evidence that management complements technology. (National Bureau of Economic Research) |
Quirós Romero and Rodríguez Rodríguez, 2010 | 2,168 Spanish manufacturing firms, 2000–05 | E-buying significantly improved firm efficiency. | Shows that specific Internet-enabled processes, rather than "Internet adoption" generally, mattered. (ScienceDirect) |
Huang and Liu, Taiwan e-commerce study, 2013 | Taiwanese manufacturing firms, 1999–2002 | E-commerce and R&D both raised productivity; their combination was complementary, with network effects. | Internet value increased when combined with other forms of innovation. (ScienceDirect) |
Najarzadeh, Rahimzadeh and Reed, 2014 | 108 countries, 1995–2010 | Internet use had a statistically significant positive relationship with labor productivity. | Evidence that the Internet's productivity effects eventually appeared at the macro level. (ScienceDirect) |
Beyond all that, some productivity enhancements are difficult to measure, especially when the capabilities do not have a price tag, and are usable without extra charge, such as search, email, navigation, maps or social media.
How do we capture the value of increases in consumer choice, reduced transaction costs, reduced search costs, easier price comparison, better product matching or enhanced convenience?
A corollary might be that the Internet and other general-purpose technologies such as electricity become less visible precisely as their economic importance increases. In other words, the technology becomes embedded in all products and services and becomes less visible as a result.
So organizational performance enhancements are increasingly difficult to isolate from overall organizational prowess.
In the case of AI, organizations might already be getting substantial value from AI through:
employees completing tasks faster
better-quality work
broader scope of work
fewer errors
faster customer responses
employees handling more work without additional hiring
better and faster software development
faster research and analysis
improved sales and marketing.
But such improvements are tough to quantify; more qualitative than quantitative in terms of output.
The upshot is that we should not be surprised when few organizations can point to quantitative output gains using accounting practices. First of all, it is too early for the big results to be proven. Also, some of the immediate gains are difficult to impossible to quantify in output, cash flow or profit figures.
It will take time, even if investors are impatient.
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