itSMF Bulletin November 2021 | Page 11

How can you make all this possible? A well-designed application of AI and machine learning (ML) can surface insights from  large volumes of data  that people would otherwise be unable to use effectively.

An AISM solution helps enterprises meet expectations for a fast, accurate, and scalable service experience by providing a unified, open platform for AI-driven automated actions and workflows complemented by cross-domain visibility and operability.

 (See the differences  between AI & ML.)

Challenges of traditional service management

The  digital era has shone a harsh light on the limitations of traditional service management—especially ITSM. Manual processes create bottlenecks and can’t scale to deliver the agility to be successful in the market.

As incidents occur, traditional methods mean teams fall back on tribal

knowledge and educated guesses to identify the underlying problems, understand their business impact, and determine the best way forward. In the best cases, the organization relies on “heroes”—those handful of staffers with the right experience and the right instincts to perform the required miracles and restore service.

It goes without saying that this approach is fundamentally unscalable and tenuous. Most often, organizations become completely reactive, with never enough time to  analyze and solve root causes  and end up restoring service for the same issues over and over. And the more complex the environment? The more reactive it gets.

To deliver the service excellence needed for digital success today, organizations must evolve from dependence on heroes and serial processes that leave it mostly reactive, to a new approach—AISM.

Diagram 1