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November 30, 2017
The hidden AI revolution: How firms transform business processes
By: Chung-Sheng Li

We regularly hear about the marvels of artificial intelligence:

  • Robots that can play the violin

  • Self-driving cars

  • Go programs that can defeat the best humans

But beyond those “gee whiz” accomplishments, we might not be aware of the hidden AI transformation quietly happening inside many leading companies. This revolution might not be getting much media coverage, but it is no less profound.

What’s it all about? Let’s start by discussing the very ways in which companies do business.

In the past, firms relied on business processes based on myriad rules, standards and key performance indicators (KPI)s. For years, this approach was sufficient to help increase efficiency and cut costs.

However, markets have grown increasingly dynamic, leaving many companies with rigid operations that put them at a distinct disadvantage. By the time those organizations have implemented changes, the market (and customers) may have already moved on.

To gain agility, some leading companies use AI to migrate their business processes from rules-based systems to more flexible, outcome-driven approaches.

Previously, many executives were so busy concentrating on the “how” of their operations that they couldn’t properly focus on the “what” and “why” of their business. Advanced AI technology changes that. To appreciate the power of this new approach, consider how companies must often deal with fast-changing legal, environmental, and accounting requirements.

Because of such regulatory changes, organizations must continually update various business processes; in certain, highly demanding environments, a business would be at a huge disadvantage if it relied on rigid, rules-based systems.

Industry leaders are using AI to transform their internal business processes. Call it the hidden AI revolution.

The beauty of AI is that it can enable companies to automatically reconfigure certain processes on the fly to accommodate those changes.

For example, consider the recently adopted International Financial Reporting Standard 15, which provides accounting guidance for reporting revenues from contracts with customers.

IFRS 15 is outcome-based, with general principles for how a firm should recognize revenues as it fulfils a contract’s performance obligations. By contrast, current accounting standards, like the Generally Accepted Accounting Principles (GAAP), tend to be more rules-based.

IFRS 15 is scheduled to be implemented in early 2018, leaving some companies scrambling to handle the transition. For example, one large energy company now has a team of lawyers reviewing thousands of customer contracts to assess how best to book the revenue from those accounts. In this case, an AI system that could analyze those contracts would offer a considerable advantage, a business to automatically determine what revenue gets booked when.

To cite another example, in healthcare, doctors were governed by strict rules that dictated exactly what procedures were covered for certain conditions and how much organizations could charge for them.

Now, AI is enabling the industry to become better at preventative healthcare. This, then, helps support the transition to outcome-based approaches, such as “pay-for-performance” models, which offer doctors, hospitals and other medical providers certain financial incentives for meeting specific criteria, such as controlling a patient’s weight and blood pressure.

The bottom line: Companies that join this AI revolution will not only increase strategic agility and be better equipped to react quickly to market and regulatory changes. They will also be able to achieve step-level increases in performance, and perhaps uncover “game-changing” innovations.

The future, as we see it, is a clear question of disruptees versus disruptors: Those that continue to rely on traditional rules-based business processes risk becoming the former, vulnerable to the latter’s embrace of AI to deliver outcomes.

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