How is the rise of artificial intelligence and automation shaping the make-or-buy decision landscape?

The advent of AI and automation technologies has fundamentally altered the cost structures associated with the make-or-buy decision. Automation can significantly reduce labor costs and increase efficiency in production processes, tipping the scales in favor of making. For instance, a report by McKinsey highlighted that in sectors with high automation potential, such as manufacturing and logistics, the cost savings from reduced labor and improved efficiency can make in-house production more attractive. However, the initial investment in AI and automation technologies can be substantial, leading some organizations to prefer buying, especially if suppliers have already achieved economies of scale in automated production.

Moreover, AI and automation enhance the quality and consistency of outputs, reducing waste and rework. This improvement in Operational Excellence can justify the upfront investment in technology for in-house production. However, it requires a strategic assessment of the organization's ability to absorb and implement these technologies effectively compared to the capabilities of external suppliers.

From a cost perspective, organizations must also consider the long-term implications of AI and automation on their industry's labor market. As automation technologies become more prevalent, the cost of skilled labor for maintaining and operating these systems might increase, affecting the cost-benefit analysis of the make-or-buy decision.

AI and automation are not just operational tools; they are strategic assets that can drive Innovation and create Competitive Advantage. The decision to develop these capabilities in-house is often driven by the desire to control and customize these technologies to fit the organization's specific needs, fostering innovation. For example, Tesla's decision to develop its own AI chips for autonomous driving is a strategic move to differentiate its products and control its innovation pipeline.

However, the pace of technological change poses a challenge. Organizations choosing to make must continuously invest in upgrading their capabilities to stay ahead. This is where buying can offer an advantage, as it allows organizations to leverage the expertise and investments of specialized suppliers who are at the forefront of technological advancements. A partnership with AI and automation leaders can provide access to cutting-edge technology without the need for significant internal investment, as seen in the collaboration between healthcare companies and AI startups for drug discovery and diagnostics.

The strategic dimension of the make-or-buy decision also involves considering the risk of dependency on external suppliers for critical technology. In sectors where AI and automation capabilities are central to competitive positioning, relying on external sources can pose a significant risk to Operational Excellence and Strategic Flexibility. This risk must be balanced against the benefits of speed and access to advanced technology that buying provides.

Leading organizations across various industries are navigating the make-or-buy decision in the context of AI and automation with varying strategies. Amazon's development of its own AI-powered logistics and delivery systems exemplifies a strategic decision to make, aiming to control key technologies that drive its Competitive Advantage. On the other hand, small and medium-sized enterprises (SMEs) often lean towards buying, as seen in the widespread adoption of cloud-based AI services offered by companies like Google Cloud and Microsoft Azure. These services allow SMEs to leverage advanced AI capabilities without the need for substantial internal investment.

In the automotive industry, the trend is mixed. While companies like Tesla invest heavily in developing in-house AI capabilities for autonomous driving, others partner with tech companies to integrate existing AI technologies into their vehicles. This reflects a strategic assessment of the make-or-buy decision based on the company's core competencies, competitive strategy, and the strategic importance of AI and automation technologies in their value proposition.

Market research firms, including Gartner and Forrester, have noted an increasing trend towards hybrid strategies that combine making and buying. Organizations are developing core AI and automation capabilities in-house while partnering with external suppliers for complementary technologies. This approach allows organizations to maintain control over strategic assets while leveraging external innovation and scale advantages.