Snooze and you lose: Companies needs infrastructure for AI

AI is really exciting technology but McKinsey says up to 20 percent of companies struggle to even think about AI implementations.
31 July 2018 | 900 Shares

Companies who haven’t invested in infrastructure would find it harder to implement AI. Source: Shutterstock

Artificial Intelligence (AI) automates and accelerates several tasks in order to make business processes more efficient and productive.

Despite this, a McKinsey study has revealed that about two-thirds of companies are yet to test out any AI capabilities.

According to a post written by Jacques Bughin, Director of McKinsey Global Institute and Nicolas van Zeebroeck, Professor at the Solvay Brussels School of Economics and Management, Université Libre de Bruxelles, the main reason is the lack of digital infrastructure.

Data from McKinsey supports this – companies with a stronger base in core digital technologies – such as cloud computing, mobile, and web – were more likely to have adopted AI tools into their workflow.

“This digital substructure is still lacking in many companies, and that may be slowing the diffusion of AI,” wrote Bughin and Zeebroeck. “We estimate that only one in three companies had fully diffused the underlying digital technologies and that the biggest gaps were in more recent tools, such as big data, analytics, and the cloud.”

What this signifies is that AI technology cannot be deployed out of thin air. Instead, it is a part of a continuous investment that builds on previously deployed infrastructures.

In fact, Bughin and Zeebroeck noted that three-quarters of the companies that have adopted AI successfully, “depended on knowledge gained from applying and mastering existing digital capabilities to do so”. This means companies that have invested in big data and advanced analytics enjoy a headstart, while others lagged behind.

“This weak base, according to our estimates, has put AI out of reach for a fifth of the companies we studied,” they added.

Often, companies choose to adopt a “wait and see” attitude – if a technology is not yet proven, they can afford to put it off until a later date. Some believe they are able to “leapfrog to leadership positions without a need for early investments”.

In reality, the contrary is true. Waiting comes with risks, which can sometimes cost the company. McKinsey’s report observed that early movers are now raking in performance and revenue gains. Most are now in the second wave of investments into additional AI applications, which contributes further to their profits.

Numbers show that businesses that have invested heavily on AI are cashing in up to five percent more profit than industry averages. Meanwhile, companies that have not touched AI at all, are performing below average.

This is especially prominent in finance, “where AI and digital technologies are creating greater competitive differentiation”. In construction, where AI and digital strategies are relatively uncommon for now, the profit gap is much smaller.

Typically, any adoption of new technology follows the S-curve. A few industry heavyweights will first make a huge bet on it before others follow suit; any laggards will then be left behind, suffering damages.

“Executives are becoming aware of what is at stake… faced with AI-fueled competitive threats, companies are twice as likely to embrace AI as they were to adopt new technologies in past technology cycles,” Bughin and Zeebroeck stated.

While for the adoption of AI, industries are generally still at the beginning of the curve, soon this will accelerate. Many younger digital native companies are already quickly deploying AI and reaping the benefits.

With competition ramping up, some businesses are starting to see profits drained by other fast-moving companies. A strong base in digital capabilities allows companies to adopt AI quickly, while others will soon be left behind if they don’t prepare themselves for digital transformation.