As artificial intelligence and machine learning mature into go-to tools across industry, a few key points can guide companies to the greatest value.
It’s not a paint job, it’s an engine
As firms move past the novelty of artificial intelligence and machine learning and beyond experimenting with it as an add-on, leaders increasingly respect the technologies’ ability to power true change within their organizations.
Unfortunately, it’s a lesson that some firms stubbornly ignore to their detriment: some 40% of firms that continue to treat the technologies as siloed tools—ones sometimes generating reports and insights untethered from any plans to act on them—have seen no business gains from their investments in AI and ML, according to new research by MIT Sloan Management Review and Boston Consulting Group.
Why are companies’ experiences so varied, ranging from boldly successful to “bridge to nowhere”?
Value accrues from tying tech to strategy
Artificial intelligence’s richest value comes from aligning it seamlessly with the company’s strategy, a process that sees AI or any other technology as a supporter and enabler of strategy rather than as a driver of it.
For healthcare systems with a strategy of supporting revenue with quality measures and back-end excellence, for example, that might mean reducing diagnostic and prescribing errors, tightening coordination of care and finding unbilled or unreimbursed charges.
For law enforcement and counterterrorism organizations with a strategy of using digital artifacts to reduce crime and terrorism, artificial intelligence and machine learning can find patterns among billions of disparate communications, pointing to bad actors before they act.
Driving revenue wins over cost reduction
MIT’s research pinpoints the alignments that have transformed businesses the most, and driving revenue is a clear winner over cost reduction. While both are desirable and are pursued by firms with mature AI plans, the companies seeing the biggest wins are those that disrupt their current business processes on a large scale to capture the new revenues that AI and ML enable.
Routes to stronger revenues are as varied as the businesses themselves. Some companies will use AI to generate highly customized service packages for customers, while others will use it to design better physical products or to unravel complex scientific puzzles to accelerate drug development.
AI and ML will take over tasks, not jobs
Only about five percent of jobs in the U.S. are fully automatable with current technologies and therefore candidates to be replaced by artificial intelligence, machine learning, robotics and the like, according to recent findings by McKinsey.
Much more frequently, the technologies will undertake tasks, typically repetitive and often boring ones such as calculations, error-finding and pattern recognition as well as manual processes such as bill preparation and distribution. Reskilling employees to adapt to changed roles and workflows—often ones more interesting and challenging than prior ones—should be an integral part of each firm’s strategy.
Humans will still be in high demand for higher order roles involving creativity, social and emotional skills, critical thinking and strategy development.
Indeed, the very strategies that AI can empower are ones devised by the innovators whom it serves.