AI is Transforming Industries – But How Will You Adopt It?

Artificial intelligence is rapidly revolutionizing industries from biotech to finance. But for managers looking to capitalize on AI’s potential, a critical strategic question looms: How will you adopt and implement AI systems at your firm?

A new study [1] from researchers in Europe sheds light on this important issue. The researchers investigated whether firms adopt AI technologies through purchasing off-the-shelf commercial software or by developing proprietary, custom solutions in-house. Surprisingly, their findings suggest these two sourcing strategies are often complementary rather than substitutes.

For scientific research, retail, finance, and manufacturing companies, investing in both off-the-shelf AI solutions and internal development initiatives appeared to go hand-in-hand. In-house software development helped firms effectively adapt, extend, and realize value from commercial AI packages.

As one researcher explained, “Developing in-house knowledge assets may help firms to better utilize innovations acquired elsewhere and evaluate new external innovations as they emerge.” In industries undergoing rapid AI-driven transformation, mastering both sourcing strategies seems to be advantageous.

However, this complementarity has an important implication: It suggests that for many firms, successfully adopting AI will require pursuing the “longest and most expensive path” of investing in both commercial solutions and internal AI expertise and development efforts. Given the scarcity of AI talent, the researchers caution that off-the-shelf software alone may not allow firms lacking in-house skills to obtain significant value from AI investments, at least in the short-term.

The findings have measurement implications as well. Many studies proxy for AI adoption by looking at a firm’s hiring of employees with AI skills and expertise. But with complementarities between external and internal sourcing, this skills-based approach may increasingly miss firms adopting AI through commercial software packages as they become more widely available.

While the researchers studied European firms across industries, the results are highly relevant for biotech managers. Scientific research was among the sectors exhibiting the strongest complementarities between in-house development and off-the-shelf software utilization for AI solutions.

So as you navigate your firm’s AI transformation journey, be aware that a hybrid sourcing model drawing upon both commercial packages and proprietary development initiatives could be optimal, despite the inherent challenges. Building this dual sourcing capability may position you to most effectively harness AI’s potential.

Of course, all industries and companies are different. The IT sector displayed substitution between sourcing strategies rather than complementarities in the study. But for most biotech research organizations, the findings suggest the path to powerful AI capabilities may require investments on multiple fronts.

References:

1. Hoffreumon C, Forman C, Van Zeebroeck N. Make or buy your artificial intelligence? Complementarities in technology sourcing. Journal of Economics & Management Strategy. 2024;33(2):452-79.